Soil moisture variability over Odra watershed: Comparison between SMOS and GLDAS data

NASA Astrophysics Data System (ADS)

Zawadzki, Jaroslaw; Kędzior, Mateusz

2016-03-01

Monitoring of temporal and spatial soil moisture variability is an important issue, both from practical and scientific point of view. It is well known that passive, L-band, radiometric measurements provide best soil moisture estimates. Unfortunately as it was observed during Soil Moisture and Ocean Salinity (SMOS) mission, which was specially dedicated to measure soil moisture, these measurements suffer significant data loss. It is caused mainly by radio frequency interference (RFI) which strongly contaminates Central Europe and even in particularly unfavorable conditions, might prevent these data from being used for regional or watershed scale analysis. Nevertheless, it is highly awaited by researchers to receive statistically significant information on soil moisture over the area of a big watershed. One of such watersheds, the Odra (Oder) river watershed, lies in three European countries - Poland, Germany and the Czech Republic. The area of the Odra river watershed is equal to 118,861 km2 making it the second most important river in Poland as well as one of the most significant one in Central Europe. This paper examines the SMOS soil moisture data in the Odra river watershed in the period from 2010 to 2012. This attempt was made to check the possibility of assessing, from the low spatial resolution observations of SMOS, useful information that could be exploited for practical aims in watershed scale, for example, in water storage models even while moderate RFI takes place. Such studies, performed over the area of a large watershed, were recommended by researchers in order to obtain statistically significant results. To meet these expectations, Centre Aval de Traitement des Donnes SMOS (CATDS), 3-days averaged data, together with Global Land Data Assimilation System (GLDAS) National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab (NOAH) model 0.25 soil moisture values were used for statistical analyses and mutual

SMOS reveals the signature of Indian Ocean Dipole events

NASA Astrophysics Data System (ADS)

Durand, Fabien; Alory, Gaël; Dussin, Raphaël; Reul, Nicolas

2013-12-01

The tropical Indian Ocean experiences an interannual mode of climatic variability, known as the Indian Ocean Dipole (IOD). The signature of this variability in ocean salinity is hypothesized based on modeling and assimilation studies, on account of scanty observations. Soil Moisture and Ocean Salinity (SMOS) satellite has been designed to take up the challenge of sea surface salinity remote sensing. We show that SMOS data can be used to infer the pattern of salinity variability linked with the IOD events. The core of maximum variability is located in the central tropical basin, south of the equator. This region is anomalously salty during the 2010 negative IOD event, and anomalously fresh during the 2011 positive IOD event. The peak-to-peak anomaly exceeds one salinity unit, between late 2010 and late 2011. In conjunction with other observational datasets, SMOS data allow us to draw the salt budget of the area. It turns out that the horizontal advection is the main driver of salinity anomalies. This finding is confirmed by the analysis of the outputs of a numerical model. This study shows that the advent of SMOS makes it feasible the quantitative assessment of the mechanisms of ocean surface salinity variability in the tropical basins, at interannual timescales.

ESAC RFI Survey in the SMOS 1400-1427MHz Passive Band

NASA Astrophysics Data System (ADS)

Castillo-Fraile, Manuel; Uranga, Ekhi

2016-08-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was launched on 2 November 2009, and it is the ESA second Earth Explorer Opportunity mission. After 6 years of successful Operations, the status of the SMOS mission is excellent, and it is providing very reliable acquisition, nominal and NRT data processing, archiving, and dissemination services of Level 1 and Level 2 processed data around the entire Planet. However, SMOS observations are significantly affected by RF interferences in several World areas. In this context, a new RFI detection and monitoring tool has been implemented at ESAC to provide to the national radiofrequency authorities with a proper detection and localization method of the illegal ground emitters in order to ensure the protection of the SMOS 1400- 1427MHz Passive Band for scientific applications.

Strategies for Validating and Directions for Employing SMOS Data, in the Cal-Val Project SWEX (3275)

NASA Astrophysics Data System (ADS)

Marczewski, Wojciech; Usowicz, Boguslaw; Usowicz, Jerzy; Romanov, Sergey; Maryskevych, Oksana; Nastula, Jolanta; Slominski, Jan; Zawadzki, Jaroslaw

2009-11-01

Earth land surface target of observations is naturally diversified in its physical and bio-physical properties. SMOS observation of SM (Soil Moisture) is highly dependent on proper physical and environmental data necessary, because SM is retrieved from the directly observable BT (Brightness Temperature) on the basis of these external data. That way, SMOS realizes a real data fusion performed NRT (Nearly Real Time) and thus needs validating. Global range of SMOS observations makes it generalizing the diversity on complex way engaging technical, modelling and organizational means. That is a new quality of EO (Earth Observations) in the matter of managing diversity of the target. The paper presents several proofs on employing external data by means of the SMOS software tools, for L1c and L2 data levels. Authors take validation in few selected sites in Poland, and describe their strategy for employing external data from ASAR, MERIS, and other auxiliary sources. Finally the conclusions come to understanding of a use of SMOS data, and seek ways of referencing SM in large scales to known results of the gravitational Mission GRACE.

Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

NASA Astrophysics Data System (ADS)

Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi

2014-05-01

soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide 'memory' in the climate and hydrological system; the water retained in the soil after a rainfall event is temporally more persistent than the rainfall event itself, and has a greater persistence during periods of low precipitation. Besides, the Normalized Difference Vegetation Index (NDVI) from MODIS is used as an indicator of vegetation activity and growth. The NDVI time series are expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. Understanding the relationships between SSMA and NDVI concurrent time series should provide new insight about the sensitivity of land biomes to drought.

Surface Runoff Estimation Using SMOS Observations, Rain-gauge Measurements and Satellite Precipitation Estimations. Comparison with Model Predictions

NASA Astrophysics Data System (ADS)

Garcia Leal, Julio A.; Lopez-Baeza, Ernesto; Khodayar, Samiro; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Kuligowski, Robert; Herrera, Eddy

Surface runoff is defined as the amount of water that originates from precipitation, does not infiltrates due to soil saturation and therefore circulates over the surface. A good estimation of runoff is useful for the design of draining systems, structures for flood control and soil utilisation. For runoff estimation there exist different methods such as (i) rational method, (ii) isochrone method, (iii) triangular hydrograph, (iv) non-dimensional SCS hydrograph, (v) Temez hydrograph, (vi) kinematic wave model, represented by the dynamics and kinematics equations for a uniforme precipitation regime, and (vii) SCS-CN (Soil Conservation Service Curve Number) model. This work presents a way of estimating precipitation runoff through the SCS-CN model, using SMOS (Soil Moisture and Ocean Salinity) mission soil moisture observations and rain-gauge measurements, as well as satellite precipitation estimations. The area of application is the Jucar River Basin Authority area where one of the objectives is to develop the SCS-CN model in a spatial way. The results were compared to simulations performed with the 7-km COSMO-CLM (COnsortium for Small-scale MOdelling, COSMO model in CLimate Mode) model. The use of SMOS soil moisture as input to the COSMO-CLM model will certainly improve model simulations.

Why is SMOS Drier than the South Fork In-situ Soil Moisture Network?

NASA Astrophysics Data System (ADS)

Walker, V. A.; Hornbuckle, B. K.; Cosh, M. H.

2014-12-01

Global maps of near-surface soil moisture are currently being produced by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite mission at 40 km. Within the next few months NASA's Soil Moisture Active Passive (SMAP) satellite mission will begin producing observations of near-surface soil moisture at 10 km. Near-surface soil moisture is the water content of the first 3 to 5 cm of the soil. Observations of near-surface soil moisture are expected to improve weather and climate forecasts. These satellite observations must be validated. We define validation as determining the space/time statistical characteristics of the uncertainty. A standard that has been used for satellite validation is in-situ measurements of near-surface soil moisture made with a network of sensors spanning the extent of a satellite footprint. Such a network of sensors has been established in the South Fork of the Iowa River in Central Iowa by the USDA ARS. Our analysis of data in 2013 indicates that SMOS has a dry bias: SMOS near-surface soil moisture is between 0.05 to 0.10 m^3m^{-3} lower than what is observed by the South Fork network. A dry bias in SMOS observations has also been observed in other regions of North America. There are many possible explanations for this difference: underestimation of vegetation, or soil surface roughness; undetected radio frequency interference (RFI); a retrieval model that is not appropriate for agricultural areas; or the use of an incorrect surface temperature in the retrieval process. We will begin our investigation by testing this last possibility: that SMOS is using a surface temperature that is too low which results in a drier soil moisture that compensates for this error. We will present a comparison of surface temperatures from the European Center for Medium-range Weather Forecasting (ECMWF) used to retrieve near-surface soil moisture from SMOS measurements of brightness temperature, and surface temperatures in the South Fork

Evaluation of SMOS soil moisture products over the CanEx-SM10 area

USDA-ARS?s Scientific Manuscript database

The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have be...

Towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations

NASA Astrophysics Data System (ADS)

Bircher, Simone; Richaume, Philippe; Mahmoodi, Ali; Mialon, Arnaud; Fernandez-Moran, Roberto; Wigneron, Jean-Pierre; Demontoux, François; Jonard, François; Weihermüller, Lutz; Andreasen, Mie; Rautiainen, Kimmo; Ikonen, Jaakko; Schwank, Mike; Drusch, Mattias; Kerr, Yann H.

2017-04-01

evaluated using the default dielectric model for mineral soils is ongoing for the "organic" L-MEB version. Additionally, in order to decide where a soil moisture retrieval using the "organic" dielectric model should be triggered, information on soil organic matter content in the soil surface layer has to be considered in the retrieval algorithm. For this purpose, SoilGrids (www.soilgrids.org) providing soil organic carbon content (SOCC) in g/kg is under study. A SOCC threshold based on the relation between the SoilGrids' SOCC and the presence of organic soil surface layers (relevant to alter the microwave L-band emissions from the land surface) in the SoilGrids' source soil profile information has to be established. In this communication, we present the current status of the above outlined studies with the objective to advance towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations.

An approach to constructing a homogeneous time series of soil mositure using SMOS

USDA-ARS?s Scientific Manuscript database

Overlapping soil moisture time series derived from two satellite microwave radiometers (SMOS, Soil Moisture and Ocean Salinity; AMSR-E, Advanced Microwave Scanning Radiometer - Earth Observing System) are used to generate a soil moisture time series from 2003 to 2010. Two statistical methodologies f...

Evaluation of SMAP Level 2 Soil Moisture Algorithms Using SMOS Data

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann; Shi, J. C.

2011-01-01

The objectives of the SMAP (Soil Moisture Active Passive) mission are global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolution, respectively. SMAP will provide soil moisture with a spatial resolution of 10 km with a 3-day revisit time at an accuracy of 0.04 m3/m3 [1]. In this paper we contribute to the development of the Level 2 soil moisture algorithm that is based on passive microwave observations by exploiting Soil Moisture Ocean Salinity (SMOS) satellite observations and products. SMOS brightness temperatures provide a global real-world, rather than simulated, test input for the SMAP radiometer-only soil moisture algorithm. Output of the potential SMAP algorithms will be compared to both in situ measurements and SMOS soil moisture products. The investigation will result in enhanced SMAP pre-launch algorithms for soil moisture.

Microwave-derived soil moisture over Mediterranean land uses: from ground-based radiometry to SMOS first observations

NASA Astrophysics Data System (ADS)

Saleh, Kauzar; Antolín, Carmen; Juglea, Silvia; Kerr, Yann; Millán-Scheiding, Cristina; Novello, Nathalie; Pardé, Mickael; Wigneron, Jean-Pierre; Zribi, Mehrez; López-Baeza, Ernesto

2010-05-01

plant growing cycle. 2) Airborne-based experiments. 2.1) ESA's SMOS Rehearsal 2008. For this campaign an area of 100 km2 of vineyards in winter-like conditions was flown on four days using the EMIRAD radiometer. Soil moisture could be retrieved with good accuracy but only after surface roughness was determined. In fact, the campaign highlighted that close to specular modelling of the surface reflectivity using 0-6 cm measurements of soil moisture underestimated the surface emission. This was observed also in other airborne data sets (Saleh et al. 2009). 2.2) CNES CAROLS campaigns. In 2009, the L-band CAROLS radiometer was flown on three occasions over an area of 1500 km2 covering vineyards, shrub land and Mediterranean pine forest. Main results of CAROLS 2009 will be presented in this communication, and the emphasis will be on comparing local to regional scale results given that CAROLS flights were performed at ~4000 m above the surface. For soil moisture, SVAT-derived, field soil moisture, and surface-type derived soil moisture will be used as ground truth. 3) SMOS data Finally, the results of the above mentioned experiments concerning L-MEB parameterisations will be the basis for comparisons between simulated brightness temperatures (TB) and measured TBs from SMOS at the VAS site. These exercises will be conducted in order to have an assessment of the L-MEB performance in a highly studied and monitored area, and to help pinpointing future areas of investigation in microwave radiometry. References Cano A., Saleh K., Wigneron J.P., Antolín C., Balling J., Kerr Y.H., Kruszewski A., Millán-Scheiding C., Søbjaerg S.S., Skou N., López-Baeza E. (2009), The SMOS Medierranean Ecosystem L-band experiment (MELBEX-I) over natural shrubs, Remote Sensing of Environment, in press. Saleh K., Kerr Y.H., Richaume P., Escorihuela, M.J., Panciera R., Delwart S., Walker J., Boulet G., Maisongrande P., Wursteisen P., Wigneron, J.P. (2009), Soil moisture retrievals at L-band using a two

Statistical characterization of global Sea Surface Salinity for SMOS level 3 and 4 products

NASA Astrophysics Data System (ADS)

Gourrion, J.; Aretxabaleta, A. L.; Ballabrera, J.; Mourre, B.

2009-04-01

The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency will soon provide sea surface salinity (SSS) estimates to the scientific community. Because of the numerous geophysical contamination sources and the instrument complexity, the salinity products will have a low signal to noise ratio at level 2 (individual estimates??) that is expected to increase up to mission requirements (0.1 psu) at level 3 (global maps with regular distribution) after spatio-temporal accumulation of the observations. Geostatistical methods such as Optimal Interpolation are being implemented at the level 3/4 production centers to operate this noise reduction step. The methodologies require auxiliary information about SSS statistics that, under Gaussian assumption, consist in the mean field and the covariance of the departures from it. The present study is a contribution to the definition of the best estimates for mean field and covariances to be used in the near-future SMOS level 3 and 4 products. We use complementary information from sparse in-situ observations and imperfect outputs from state-of-art model simulations. Various estimates of the mean field are compared. An alternative is the use of a SSS climatology such as the one provided by the World Ocean Atlas 2005. An historical SSS dataset from the World Ocean Database 2005 is reanalyzed and combined with the recent global observations obtained by the Array for Real-Time Geostrophic Oceanography (ARGO). Regional tendencies in the long-term temporal evolution of the near-surface ocean salinity are evident, suggesting that the use of a SSS climatology to describe the current mean field may introduce biases of magnitude similar to the precision goal. Consequently, a recent SSS dataset may be preferred to define the mean field needed for SMOS level 3 and 4 production. The in-situ observation network allows a global mapping of the low frequency component of the variability, i.e. decadal, interannual and seasonal

Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Reichle, Rolf H.

2016-01-01

Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40 degree incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval

Comparison of SMOS and Aquarius Sea Surface Salinity and Analysis of Possible Causes for the Differences

NASA Technical Reports Server (NTRS)

Dinnat, E. P.; Boutin, J.; Yin, X.; Le Vine, D. M.; Waldteufel, P.; Vergely, J. -L.

2014-01-01

Two ongoing space missions share the scientific objective of mapping the global Sea Surface Salinity (SSS), yet their observations show significant discrepancies. ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometers to measure emission from the sea surface and retrieve SSS. Significant differences in SSS retrieved by both sensors are observed, with SMOS SSS being generally lower than Aquarius SSS, except for very cold waters where SMOS SSS is the highest overall. Figure 1 is an example of the difference between the SSS retrieved by SMOS and Aquarius averaged over one month and 1 degree in longitude and latitude. Differences are mostly between -1 psu and +1 psu (psu, practical salinity unit), with a significant regional and latitudinal dependence. We investigate the impact of the vicarious calibration and some components of the retrieval algorithm used by both mission on these differences.

Neural network retrieval of soil moisture: application to SMOS

NASA Astrophysics Data System (ADS)

Rodriguez-Fernandez, Nemesio; Richaume, Philippe; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Kolasssa, Jana; Jimenez, Carlos; Cabot, Francois; Mahmoodi, Ali

2014-05-01

We present an efficient statistical soil moisture (SM) retrieval method using SMOS brightness temperatures (BTs) complemented with MODIS NDVI and ASCAT backscattering data. The method is based on a feed-forward neural network (hereafter NN) trained with SM from ECMWF model predictions or from the SMOS operational algorithm. The best compromise to retrieve SM with NNs from SMOS brightness temperatures in a large fraction of the swath (~ 670 km) is to use incidence angles from 25 to 60 degrees (in 7 bins of 5 deg width) for both H and V polarizations. The correlation coefficient (R) of the SM retrieved by the NN and the reference SM dataset (ECMWF or SMOS L3) is 0.8. The correlation coefficient increases to 0.91 when adding as input MODIS NDVI, ECOCLIMAP sand and clay fractions and one of the following data: (i) active microwaves observations (ASCAT backscattering coefficient at 40 deg incidence angle), (ii) ECMWF soil temperature. Finally, the correlation coefficient increases to R=0.94 when using a normalization index computed locally for each latitude-longitude point with the maximum and minimum BTs and the associated SM values from the local time series. Global maps of SM obtained with NNs reproduce well the spatial structures present in the reference SM datasets, implying that the NN works well for a wide range of ecosystems and physical conditions. In addition, the results of the NNs have been evaluated at selected locations for which in situ measurements are available such as the USDA-ARS watersheds (USA), the OzNet network (AUS) and USDA-NRCS SCAN network (USA). The time series of SM obtained with NNs reproduce the temporal behavior measured with in situ sensors. For well known sites where the in situ measurement is representative of a 40 km scale like the Little Washita watershed, the NN models show a very high correlation of (R = 0.8-0.9) and a low standard deviation of 0.02-0.04 m3/m3 with respect to the in situ measurements. When comparing with all the in

SMOS Soil Moisture Data Assimilation in the NASA Land Information System: Impact on LSM Initialization and NWP Forecasts

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Case, Jonathan L.; Zavodsky, Bradley

2015-01-01

Land surface models are important components of numerical weather prediction (NWP) models, partitioning incoming energy into latent and sensitive heat fluxes that affect boundary layer growth and destabilization. During warm-season months, diurnal heating and convective initiation depend strongly on evapotranspiration and available boundary layer moisture, which are substantially affected by soil moisture content. Therefore, to properly simulate warm-season processes in NWP models, an accurate initialization of the land surface state is important for accurately depicting the exchange of heat and moisture between the surface and boundary layer. In this study, soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) satellite radiometer are assimilated into the Noah Land Surface Model via an Ensemble Kalman Filter embedded within the NASA Land Information System (LIS) software framework. The output from LIS-Noah is subsequently used to initialize runs of the Weather Research and Forecasting (WRF) NWP model. The impact of assimilating SMOS retrievals is assessed by initializing the WRF model with LIS-Noah output obtained with and without SMOS data assimilation. The southeastern United States is used as the domain for a preliminary case study. During the summer months, there is extensive irrigation in the lower Mississippi Valley for rice and other crops. The irrigation is not represented in the meteorological forcing used to drive the LIS-Noah integration, but the irrigated areas show up clearly in the SMOS soil moisture retrievals, resulting in a case with a large difference in initial soil moisture conditions. The impact of SMOS data assimilation on both Noah soil moisture fields and on short-term (0-48 hour) WRF weather forecasts will be presented.

Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture

NASA Astrophysics Data System (ADS)

Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.

2016-06-01

Terrestrial evaporation is an essential variable in the climate system that links the water, energy and carbon cycles over land. Despite this crucial importance, it remains one of the most uncertain components of the hydrological cycle, mainly due to known difficulties to model the constraints imposed by land water availability on terrestrial evaporation. The main objective of this study is to assimilate satellite soil moisture observations from the Soil Moisture and Ocean Salinity (SMOS) mission into an existing evaporation model. Our over-arching goal is to find an optimal use of satellite soil moisture that can help to improve our understanding of evaporation at continental scales. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used to simulate evaporation fields over continental Australia for the period September 2010-December 2013. SMOS soil moisture observations are assimilated using a Newtonian Nudging algorithm in a series of experiments. Model estimates of surface soil moisture and evaporation are validated against soil moisture probe and eddy-covariance measurements, respectively. Finally, an analogous experiment in which Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture is assimilated (instead of SMOS) allows to perform a relative assessment of the quality of both satellite soil moisture products. Results indicate that the modelled soil moisture from GLEAM can be improved through the assimilation of SMOS soil moisture: the average correlation coefficient between in situ measurements and the modelled soil moisture over the complete sample of stations increased from 0.68 to 0.71 and a statistical significant increase in the correlations is achieved for 17 out of the 25 individual stations. Our results also suggest a higher accuracy of the ascending SMOS data compared to the descending data, and overall higher quality of SMOS compared to AMSR-E retrievals over Australia. On the other hand, the effect of soil moisture data

The ESA SMOS Validation Rehearsal Campaign at the Valencia Anchor Station Area in the Framework of the SMOS Cal/Val AO Project no. 3252

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.

2009-04-01

Since 2001, the Valencia Anchor Station is currently being prepared for the validation of SMOS land products. The site has recently been selected by the Mission as a core validation site, mainly due to the reasonable homogeneous characteristics of the area which make it appropriate to undertake the validation of SMOS Level 2 land products during the Mission Commissioning Phase, before attempting more complex areas. Close to SMOS launch, ESA defined and designed the SMOS Validation Rehearsal Campaign Plan with the purpose of repeating the Commissioning Phase execution with all centers, all tools, all participants, all structures, all data available, assuming that all tools and structures are ready and trying to produce as close as possible the post-launch conditions. The aim was to test the readiness, the ensemble coordination and the speed of operations to be able to avoid as far as possible any unexpected deficiencies of the plan and procedure during the real Commissioning Phase campaigns. For the rehearsal activity which successfully took place in April 2008, a control area of 10 x 10 km2 was chosen at the Valencia Anchor Station study area where a network of ground soil moisture measuring stations is being set up based on the definition of homogeneous physio-hydrological units, attending to climatic, soil type, lithology, geology, elevation, slope and vegetation cover conditions. These stations are linked via a wireless communication system to a master post accessible via internet. Complementary to the ground measurements, flight operations were performed over the control area using the Helsinki University of Technology TKK Short Skyvan research aircraft. The payload for the campaign consisted of the following instruments: (i) L-band radiometer EMIRAD (Technical University of Denmark, TUD), (ii) HUT-2D L-band imaging interferometric radiometer (TKK), (iii) PARIS GPS reflectrometry system (Institute for Space Studies of Catalonia, IEEC), (iv) IR sensor (Finnish

Fibre optics in the SMOS mission

NASA Astrophysics Data System (ADS)

Kudielka, K.; Benito-Hernández, F. J.; Rits, W.; Martin-Neira, M.

2017-11-01

Launched on November 2nd, 2009, SMOS (Soil Moisture, Ocean Salinity) is the second Earth Explorer Opportunity mission developed as part of ESA's Living Planet Programme. It demonstrates a completely new type of instrument - a large, deployable synthetic-aperture microwave radiometer [1]. RUAG Space, Switzerland, as a subcontractor of EADS Astrium, Spain, has provided the instrument's fibreoptic harness, which interconnects the central data processor with all 69 microwave receivers, as well as 12 auxiliary units on board. For reasons explained in Section 3, SMOS is the first European mission extensively using both fibre-optic clock distribution and data transmission in space. In Section 2, we present an overview of the scientific goals of SMOS, and describe the payload's basic function. There from we derive the rationale and the design of the fibre-optic harness (Section 3). In Section 4 all development, manufacturing, and test activities are summarised, which culminated in the successful delivery of all flight units to EADS Astrium by October 2006. We present the major test results obtained with the flight harness (Section 5), and conclude with a short summary of the higher-level activities, which lead to successful launch and commissioning of the SMOS satellite (Section 6).

Retrieve sea surface salinity using principal component regression model based on SMOS satellite data

NASA Astrophysics Data System (ADS)

Zhao, Hong; Li, Changjun; Li, Hongping; Lv, Kebo; Zhao, Qinghui

2016-06-01

The sea surface salinity (SSS) is a key parameter in monitoring ocean states. Observing SSS can promote the understanding of global water cycle. This paper provides a new approach for retrieving sea surface salinity from Soil Moisture and Ocean Salinity (SMOS) satellite data. Based on the principal component regression (PCR) model, SSS can also be retrieved from the brightness temperature data of SMOS L2 measurements and Auxiliary data. 26 pair matchup data is used in model validation for the South China Sea (in the area of 4°-25°N, 105°-125°E). The RMSE value of PCR model retrieved SSS reaches 0.37 psu (practical salinity units) and the RMSE of SMOS SSS1 is 1.65 psu when compared with in-situ SSS. The corresponding Argo daily salinity data during April to June 2013 is also used in our validation with RMSE value 0.46 psu compared to 1.82 psu for daily averaged SMOS L2 products. This indicates that the PCR model is valid and may provide us with a good approach for retrieving SSS from SMOS satellite data.

SMOS salinity retrieval by using Support Vector Regression (SVR)

NASA Astrophysics Data System (ADS)

Katagis, Thomas; Fernández-Prieto, Diego; Marconcini, Mattia; Sabia, Roberto; Martinez, Justino

2013-04-01

The Soil Moisture and Ocean Salinity (SMOS) mission was launched in November 2009 within the framework of the European Space Agency (ESA) Living Planet programme. Over the oceans, it aims at providing Sea Surface Salinity (SSS) maps with spatial and temporal coverage adequate for large scale oceanography. A comprehensive inversion scheme has been defined and implemented in the operational retrieval chain to allow proper SSS estimates in a single satellite overpass (L2 product) from the multi-angular brightness temperatures (TBs) measured by SMOS. Such SMOS operational L2 salinity processor minimizes the difference between the measured and modeled TBs, including additional constraints on Sea Surface Temperature (SST) and wind speed auxiliary fields. In particular, by adopting a maximum-likelihood Bayesian approach, the inversion scheme retrieves salinity under an iterative convergence loop. However, despite the implemented iterative technique is well established and robust, it is still prone to limitations; for instance, the presence of local minima in the cost function cannot be excluded. Moreover, previous studies have demonstrated that the background and observational terms of the cost function are not properly balanced and this is likely to introduce errors in the retrieval procedure. In order to overcome such potential drawbacks, in this study it is proposed a novel approach for the SSS estimation based on the ɛ-insensitive Support Vector Regression (SVR), where both SMOS L1 measurements and auxiliary parameters are used as input. The SVR technique already proved capable of high generalization and robustness in a variety of different applications, with a limited complexity in handling the learning phase. Notably, instead of minimizing the observed training error, it attempts to minimize the generalization error bound so as to achieve generalized performance. For this purpose, the original input domain is mapped into a higher dimensionality space (where the

Reconstruction from EOF analysis of SMOS salinity data in Mediterranean Sea

NASA Astrophysics Data System (ADS)

Parard, Gaelle; Alvera-Azcárate, Aida; Barth, Alexander; Olmedo, Estrella; Turiel, Antonio; Becker, Jean-Marie

2017-04-01

Sea Surface Salinity (SSS) data from the Soil Moisture and Ocean Salinity (SMOS) mission is reconstructed in the North Atlantic and the Mediterranean Sea using DINEOF (Data Interpolating Empirical Orthogonal Functions). We used the satellite data Level 2 from SMOS Barcelona Expert Centre between 2011 and 2015. DINEOF is a technique that reconstructs missing data and removes noise by retaining only an optimal set of EOFs. DINEOF analysis is used to detect and remove outliers from the SMOS SSS daily field. The gain obtained with DINEOF method and L2 SMOS data give a higher spatial and temporal resolution between 2011 and 2015, allow to study the SSS variability from daily to seasonal resolution. In order to improve the SMOS salinity data reconstruction we combine with other parameters measured from satellite such chlorophyll, sea surface temperature, precipitation and CDOM variability. After a validation of the SMOS satellite data reconstruction with in situ data (CTD, Argo float salinity measurement) in the North Atlantic and Mediterranean Sea, the main SSS processes and their variability are studied. The gain obtained with the higher spatial and temporal resolution with SMOS salinity data give assess to study the characteristics of oceanic structures in North Atlantic and Mediterranean Sea.

The Impact of Dielectric Constant Model and Surface Reference on Differences Between SMOS and Aquarius Sea Surface Salinity

NASA Technical Reports Server (NTRS)

Dinnat, E. P.; Boutin, J.; Yin, X.; LeVine, D. M.

2014-01-01

Two ongoing space missions share the scientific objective of mapping the global Sea Surface Salinity (SSS), yet their observations show significant discrepancies. ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometers to measure emission from the sea surface and retrieve SSS. Significant differences in SSS retrieved by both sensors are observed, with SMOS SSS being generally lower than Aquarius SSS, except for very cold waters where SMOS SSS is the highest overall. Figure 1 is an example of the difference between the SSS retrieved by SMOS and Aquarius averaged over one month and 1 degree in longitude and latitude. Differences are mostly between -1 psu and +1 psu (psu, practical salinity unit), with a significant regional and latitudinal dependence. We investigate the impact of the vicarious calibration and retrieval algorithm used by both mission on these differences.

SMOS data and extreme events

NASA Astrophysics Data System (ADS)

Kerr, Yann; Wigneron, Jean-Pierre; Ferrazzoli, Paolo; Mahmoodi, Ali; Al-Yaari, Amen; Parrens, Marie; Bitar, Ahmad Al; Rodriguez-Fernandez, Nemesio; Bircher, Simone; Molero-rodenas, Beatriz; Drusch, Matthias; Mecklenburg, Susanne

2017-04-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface (with an accuracy goal of 0.04 m3/m3), vegetation water content over land, and ocean salinity. These geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge at a global scale is of interest for climatic and weather researches, and in particular in improving model forecasts. The Soil Moisture and Ocean Salinity mission has now been collecting data for over 7 years. The whole data set has been reprocessed (Version 620 for levels 1 and 2 and version 3 for level 3 CATDS) while operational near real time soil moisture data is now available and assimilation of SMOS data in NWP has proved successful. After 7 years it seems important to start using data for having a look at anomalies and see how they can relate to large scale events. We have also produced a 15 year soil moisture data set by merging SMOS and AMSR using a neural network approach. The purpose of this communication is to present the mission results after more than seven years in orbit in a climatic trend perspective, as through such a period anomalies can be detected. Thereby we benefit from consistent datasets provided through the latest reprocessing using most recent algorithm enhancements. Using the above mentioned products it is possible to follow large events such as the evolution of the droughts in North America, or water fraction evolution over the Amazonian basin. In this occasion we will focus on the analysis of SMOS and ancillary products anomalies to reveal two climatic trends, the temporal evolution of water storage over the Indian continent in relation to rainfall anomalies, and the global impact of El Nino types of events on the general water storage distribution. This presentation shows in detail the use of long term data sets

How Different are SMOS Morning and Evening Observations?

NASA Astrophysics Data System (ADS)

Rowlandson, T. L.; Hornbuckle, B. K.

2010-12-01

The Soil Moisture Ocean Salinity (SMOS) satellite was launched by the European Space Agency in November, 2009, to make measurements of soil moisture at L-band in a 40 km x 40 km footprint, making passes over the north central region of the United States at 6am and 6pm approximately, with the intent of having passes at least every 3 days. No comparisons between 6am and 6pm have been made. The NASA Soil Moisture Active Passive (SMAP) intends to use only 6am data because of concerns of the quality of the data for 6pm passes. Brightness temperature outputs of the SMOS data were examined for both the 6am and 6pm passes to determine if changes in measurement exist for days when there is no rainfall. Changes in the brightness temperature can result from changes in internal water content of the crop, which we currently do not have the ability to accurately determine, presence of external water on the canopy, which in this study will be limited to dew, changes in canopy and soil temperature, and changes in soil moisture. The first step taken in this project was to investigating changes between the 6am and 6pm measurements that may result from the presence of dew on the canopy. Land and airborne L-band radiometers have shown that dew on a crop canopy provides a source of error in the measurements of surface soil moisture. The magnitude and sign of the error appears to be crop dependent. The empirical model of RH>90% has been used extensively to simulate dew duration. At the Iowa Validation site in Ames, Iowa, relative humidity was measured above the crop canopy, in both corn and soybeans, and within the crop canopy. Comparisons were made between the relative humidity measured above the canopy to that measured within the canopy at 3 locations within the field. These values were also compared to relative humidity measured at a standard weather station near the field site. These measurements were used to define a more appropriate relative humidity threshold for the central

SMOS Measurements Preliminary Validation: Objectives and Approach

NASA Astrophysics Data System (ADS)

Sabia, Roberto; Gourrion, Jerome; Gabarró, Carolina; Talone, Marco; Portabella, Marcos; Ballabrera, Joaquim; Lopez de Aretxabaleta, Alfredo; Camps, Adriano; Monerris, Alessandra; Font, Jordi

2010-05-01

strategy to mitigate the scene-dependent bias found in the SMOS measurements. The comparison of TB departures distributions will be performed within specific classes, aiming at reducing the degrees of freedom of the measurement. Namely, the data will be sorted according to the incidence angle, the wind speed, the across-track distance, the radiometric accuracy and the spatial resolution. Concerning SSS, in turn, the proposed activities will involve inter-comparisons with various external salinity sources. As a further classification, external sources can be distinguished into data coming from models and data collected in-situ. The validation strategy foresees the comparison of SSS misfit (retrieved SSS minus ground-truth SSS) distributions within specific classes. This will be performed sorting geographical areas (different oceans, different zonal frames) and geophysical conditions (e.g. low/high surface temperature, wind speed and SSS conditions). Specific comparisons with in-situ data coming from oceanographic cruises transects and from VOS (Voluntary Observatory Ships) are foreseen, as well as against moored buoys, profilers, and drifters. These data will be arranged in specific match-up datasets, to properly organize the spatio-temporal collocation of the SMOS and in-situ measurements. The possibility of using model solutions for validation will also be considered. Model data are obtained from hindcast simulations from available prediction systems. Concerning the salinity retrieval inversion scheme, efforts will be devoted to the optimization of both the GMF (Geophysical Model Function) and the minimization cost function. With the increase of data availability, the semi-empirical GMF in the ocean salinity Level 2 operational processor will be improved, in particular the roughness-dependent TB term. The introduction of non-linear relationships in the semi-empirical roughness model is a likely extension of this formulation. The prospective approach is to develop, at a

Optimization of a Radiative Transfer Forward Operator for Simulating SMOS Brightness Temperatures over the Upper Mississippi Basin, USA

NASA Technical Reports Server (NTRS)

Lievens, H.; Verhoest, N. E. C.; Martens, B.; VanDenBerg, M. J.; Bitar, A. Al; Tomer, S. Kumar; Merlin, O.; Cabot, F.; Kerr, Y.; DeLannoy, G. J. M.;

Comparison Between AQUARIUS and SMOS brightness temperatures for Heterogeneous Land Areas

NASA Astrophysics Data System (ADS)

Benlloch, Amparo; Lopez-Baeza, Ernesto; Tenjo, Carolina; Navarro, Enrique

2016-07-01

Intercomparison between Aquarius and SMOS brightness temperatures (TBs) over land surfaces is more challenging than over oceans because land footprints are more heterogeneous. In this work we are comparing Aquarius and SMOS TBs under coherente conditions obtained both by considering similar areas, according to land uses and by stratifying by means of TVDI (Temperature Vegetation Dryness Index) that accounts for the dynamics of the vegetation instead of assuming static characteristics as in the previous approches. The area of study was chosen in central Spain where we could get a significant number of matches between both instruments. The study period corresponded to 2012-2014. SMOS level-3 data were obtained from the Centre Aval de Traitement des Données SMOS (CATDS) and Aquarius' from the Physical Oceanography Distributed Active Archive Center (PODAAC). Land uses were obtained from the Spanish SIOSE facility (Sistema de Informacion de Ocupacion del Suelo en España) that uses a scale of 1:25.000 and polygon geometrical structure layer. SIOSE is based on panchromatic and multispectral 2.5 m resolution SPOT-5 images together with Landsat-5 images and orthophotos from the Spanish Nacional Plan of Aerial Orthophotography (PNOA). TVDI values were obtained from MODIS operational products of land surface temperature and NDVI. SMOS ascending TBs were compared to inner-beam Aquarius descending half-orbit TBs coinciding over the study area at 06:00 h. The Aquarius inner beam has an incidence angle of 28,7º and SMOS data were considered for the 27,5º incidence angle. The SMOS products corresponded to version 2.6x (data before 31st Oct 2013) and version 2.7x (data after 1st Jan 2014). Intersections between both footprints were analysed under conditions of similar areas, land uses and TVDI values. For the latter (land uses/TVDI), a linear combination of SMOS land uses/TVDI was obtained to match the larger Aquarius footprint. A more physical approach is also under way

Fresh Water River discharges as observed by SMOS in the Arabian Sea and the Bay of Bengal

NASA Astrophysics Data System (ADS)

Olmedo, Estrella; Ballabrera-Poy, Joaquim; Turiel, Antonio

2017-04-01

filtering criteria is implemented, SMOS provides coherent SSS measurements close to the coast, and especially in these regions of the Indian Ocean, providing near real-time information suitable for validation and ocean data assimilation. References: [1] Font, J., Camps, A., Borges, A., Martin-Neira, M., Boutin, J., Reul, N., Kerr, Y., Hahne, A., and Mechlenburg, S. (2010). SMOS: the challenging sea surface salinity measurement from space. Proceedings of the IEEE, 98:649. [2] Olmedo, E., Martínez, J., Turiel, A., Ballabrera-Poy, J., and Portabella, M., (2017), "Debiased Non-Bayesian retrieval: a novel approach to SMOS Sea Surface Salinity, Remote Sensing of Environment, under review. [3] Zweng, M.M, J.R. Reagan, J.I. Antonov, R.A. Locarnini, A.V. Mishonov, T.P. Boyer, H.E. Garcia, O.K. Baranova, D.R. Johnson, D.Seidov, M.M. Biddle, 2013. World Ocean Atlas 2013, Volume 2: Salinity. S. Levitus, Ed., A. Mishonov Technical Ed.; NOAA Atlas NESDIS 74, 39 pp [4] Dai, A., and K. E. Trenberth, (2002): Estimates of freshwater discharge from continents: Latitudinal and seasonal variations. J. Hydrometeorol., 3, 660-687 [5] Dai, A., T. Qian, K. E. Trenberth, and J. D Milliman, (2009): Changes in continental freshwater discharge from 1949-2004. J. Climate, 22, 10, 2773-2792 [6] Bonjean F. and G.S.E. Lagerloef, (2002): Diagnostic model and analysis of the surface currents in the tropical Pacific ocean, J. Phys. Oceanogr., 32, 2,938-2,954 [7] Donlon, C. J., M. Martin, J. D. Stark, J. Roberts-Jones, E. Fiedler and W. Wimmer, (2011). The perational Sea Surface Temperature and Sea Ice analysis (OSTIA). Remote Sensing of the Environment. doi: 10.1016/j.rse.2010.10.017 2011. [8] Martin, M.J., A. Hines and M.J. Bell, (2007). Data assimilation in the FOAM operational short-range ocean forecasting system: a description of the scheme and its impact. Q.J.R. Meteorol. Soc., 133:981-995. [9] John D. Stark, Craig J. Donlon, Matthew J. Martin and Michael E. McCulloch, (2007), OSTIA : An operational

Tropical Pacific sea surface salinity variability derived from SMOS data: Comparison with in-situ observations.

NASA Astrophysics Data System (ADS)

Ballabrera, Joaquim; Hoareau, Nina; Umbert, Marta; Martínez, Justino; Turiel, Antonio

2013-04-01

reprocessing campaign released to the SMOS user community on March 2011. During the period under study, the equatorial Pacific has been in a quasi-continuous La Niña state. During the cold phases of ENSO, positive anomalies of SSS are expected with the largest anomalous values in the western warm-fresh pool. The anomalies derived from the SMOS data do indeed display a positive anomaly. The persistence of the feature, its geographical pattern, the time modulation of the anomaly amplitude indicate, and its resemblance with in situ observations indicate this novel observation technology is currently able to capture seasonal and interannual signatures of climate interest.

Posterior uncertainty of GEOS-5 L-band radiative transfer model parameters and brightness temperatures after calibration with SMOS observations

NASA Astrophysics Data System (ADS)

De Lannoy, G. J.; Reichle, R. H.; Vrugt, J. A.

2012-12-01

Simulated L-band (1.4 GHz) brightness temperatures are very sensitive to the values of the parameters in the radiative transfer model (RTM). We assess the optimum RTM parameter values and their (posterior) uncertainty in the Goddard Earth Observing System (GEOS-5) land surface model using observations of multi-angular brightness temperature over North America from the Soil Moisture Ocean Salinity (SMOS) mission. Two different parameter estimation methods are being compared: (i) a particle swarm optimization (PSO) approach, and (ii) an MCMC simulation procedure using the differential evolution adaptive Metropolis (DREAM) algorithm. Our results demonstrate that both methods provide similar "optimal" parameter values. Yet, DREAM exhibits better convergence properties, resulting in a reduced spread of the posterior ensemble. The posterior parameter distributions derived with both methods are used for predictive uncertainty estimation of brightness temperature. This presentation will highlight our model-data synthesis framework and summarize our initial findings.

The Aquarius Salinity Product: Intercomparison with SMOS and In-Situ Observations and Importance of the Ocean Surface Roughness Correction

NASA Astrophysics Data System (ADS)

Meissner, Thomas; Hilburn, Kyle; Wentz, Frank; Gentemann, Chelle

2013-04-01

The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to an accuracy of 0.2 psu. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. This first part of the presentation gives an overview over the major features of the Version 2.1 Aquarius Level 2 salinity retrieval algorithm: 1. Antenna pattern correction: spillover and cross polarization contamination. 2. Correction for the drift of the Aquarius internal calibration system. 3. Correction for intruding celestial radiation, foremost from the galaxy. 4. Correction for effects of the wind roughened ocean surface. We then present a thorough validation study for the salinity product, which consists in a 3-way intercomparison between Aquarius, SMOS and in-situ buoy salinity measurements. The Aquarius - buy comparison shows that that the Aquarius Version 2.1 salinity product is very close to meet the aforementioned mission requirement of 0.2 psu. We demonstrate that in order to meet this accuracy it is crucial to use the L-band scatterometer for correcting effects from the wind roughened ocean surface, which turns out to be the major driver in the salinity retrieval uncertainty budget. A surface roughness correction algorithm that is based solely on auxiliary input of wind fields from numerical weather prediction models (e.g. NCEP, ECMWF) is not sufficient to meet the stringent Aquarius mission requirement, especially at wind speeds above 10 m/s. We show that presence of the Aquarius L-band scatterometer together with the L-band radiometer allows the retrieval of an Aquarius wind speed product whose accuracy matches or exceeds that of other common ocean wind speeds (WindSat, SSMIS). By comparing SMOS and Aquarius salinity fields with the in-situ observations we assess the importance of the roughness correction

SMOS and AMSR-2 soil moisture evaluation using representative monitoring sites in southern Australia

NASA Astrophysics Data System (ADS)

Walker, J. P.; Mei Sun, M. S.; Rudiger, C.; Parinussa, R.; Koike, T.; Kerr, Y. H.

2016-12-01

The performance of soil moisture products from AMSR-2 and SMOS were evaluated against representative surface soil moisture stations within the Yanco study area in the Murrumbidgee Catchment, in southeast Australia. AMSR-2 Level 3 (L3) soil moisture products retrieved from two sets of brightness temperatures using the Japanese Aerospace exploration Agency (JAXA) and the Land Parameter Retrieval Model (LPRM) algorithms were included. For the LPRM algorithm, two different parameterization methods were applied. In the case of SMOS, two versions of the SMOS L3 soil moisture product were assessed. Results based on using "random" and representative stations to evaluate the products were contrasted. The latest versions of the JAXA (JX2) and LPRM (LP3) products were found to perform better than the earlier versions (JX1, LP1 and LP2). Moreover, soil moisture retrieval based on the latter version of brightness temperature and parameterization scheme improved when C-band observations were used, as opposed to the X-band data. Yet, X-band retrievals were found to perform better than C-band. Inter-comparing AMSR-2 X-band products from different acquisition times showed a better performance for 1:30 pm overpasses whereas SMOS 6:00 am retrievals were found to perform the best. The mean average error (MAE) goal accuracy of the AMSR-2 mission (MAE < 0.08 m3/m3) was met by both versions of the JAXA products, the LPRM X-band products retrieved from the reprocessed version of brightness temperatures, and both versions of SMOS products. Nevertheless, none of the products achieved the SMOS target accuracy of 0.04 m3/m3. Finally, the product performance depended on the statistics used in their evaluation; based on temporal and absolute accuracy JX2 is recommended, whereas LP3 X-band 1:30 pm and SMOS2 6:00 am are recommended based on temporal accuracy alone.

Smos Land Product Validation Activities at the Valencia Anchor Station

NASA Astrophysics Data System (ADS)

Lopez-Baeza, Ernesto

ABSTRACT Soil moisture is a key parameter controlling the exchanges between the land surface and the atmosphere. In spite of being important for weather and climate modeling, this parameter is not well observed at a global scale. The SMOS (Soil Moisture and Ocean Salinity) Mission was designed by the European Space Agency (ESA) to measure soil moisture over continental surfaces as well as surface salinity over the oceans. Since 2001, the Valencia Anchor Station is currently being prepared for the validation of SMOS land products, namely soil moisture content and vegetation water content. The site has recently been selected by the Mission as a core validation site, mainly due to the reasonable homogeneous characteristics of the area which make it appropriate to undertake the validation of SMOS Level 2 land products during the Mission Commissioning Phase, before attempting more complex areas. Close to SMOS launch, ESA has defined and designed a SMOS V alidation Rehearsal C ampaign P lan which purpose is to repeat the Commissioning Phase execution with all centers, all tools, all participants, all structures, all data available, assuming all tools and structures are ready and trying to produce as close as possible the post-launch conditions. The aim is to test the readiness, the ensemble coordination and the speed of operations, and to avoid as far as possible any unexpected deficiencies of the plan and procedure during the real C ommissioning P hase campaigns. For the rehearsal activity, a control area of 10 x 10 km2 has been chosen at the Valencia Anchor Station study area where a network of ground soil moisture measuring stations is being set up based on the definition of homogeneous physio-hydrological units, attending to climatic, soil type, lithology, geology, elevation, slope and vegetation cover conditions. These stations are linked via a wireless communication system to a master post accessible via internet. The ground soil moisture stations will also be used

Inter-Comparison of SMAP, SMOS and GCOM-W Soil Moisture Products

NASA Astrophysics Data System (ADS)

Bindlish, R.; Jackson, T. J.; Chan, S.; Burgin, M. S.; Colliander, A.; Cosh, M. H.

2016-12-01

The Soil Moisture Active Passive (SMAP) mission was launched on Jan 31, 2015. The goal of the SMAP mission is to produce soil moisture with accuracy better than 0.04 m3/m3 with a revisit frequency of 2-3 days. The validated standard SMAP passive soil moisture product (L2SMP) with a spatial resolution of 36 km was released in May 2016. Soil moisture observations from in situ sensors are typically used to validate the satellite estimates. But, in situ observations provide ground truth for limited amount of landcover and climatic conditions. Although each mission will have its own issues, observations by other satellite instruments can be play a role in the calibration and validation of SMAP. SMAP, SMOS and GCOM-W missions share some commonnalities because they are currently providing operational brightness temperature and soil moisture products. SMAP and SMOS operate at L-band but GCOM-W uses X-band observations for soil moisture estimation. All these missions use different ancillary data sources, parameterization and algorithm to retrieve soil moisture. Therefore, it is important to validate and to compare the consistency of these products. Soil moisture products from the different missions will be compared with the in situ observations. SMAP soil moisture products will be inter-compared at global scales with SMOS and GCOM-W soil moisture products. The major contribution of satellite product inter-comparison is that it allows the assessment of the quality of the products over wider geographical and climate domains. Rigorous assessment will lead to a more reliable and accurate soil moisture product from all the missions.

Improving Soil Moisture Estimation through the Joint Assimilation of SMOS and GRACE Satellite Observations

NASA Technical Reports Server (NTRS)

Girotto, Manuela

2018-01-01

Observations from recent soil moisture dedicated missions (e.g. SMOS or SMAP) have been used in innovative data assimilation studies to provide global high spatial (i.e., approximately10-40 km) and temporal resolution (i.e., daily) soil moisture profile estimates from microwave brightness temperature observations. These missions are only sensitive to near-surface soil moisture 0-5 cm). In contrast, the Gravity Recovery and Climate Experiment (GRACE) mission provides accurate measurements of the entire vertically integrated terrestrial water storage (TWS) column but, it is characterized by low spatial (i.e., 150,000 km2) and temporal (i.e., monthly) resolutions. Data assimilation studies have shown that GRACE-TWS primarily affects (in absolute terms) deeper moisture storages (i.e., groundwater). In this presentation I will review benefits and drawbacks associated to the assimilation of both types of observations. In particular, I will illustrate the benefits and drawbacks of their joint assimilation for the purpose of improving the entire profile of soil moisture (i.e., surface and deeper water storages).

SMOS sea surface salinity maps of the Arctic Ocean

NASA Astrophysics Data System (ADS)

Gabarro, Carolina; Olmedo, Estrella; Turiel, Antonio; Ballabrera-Poy, Joaquim; Martinez, Justino; Portabella, Marcos

2016-04-01

Salinity and temperature gradients drive the thermohaline circulation of the oceans, and play a key role in the ocean-atmosphere coupling. The strong and direct interactions between the ocean and the cryosphere (primarily through sea ice and ice shelves) is also a key ingredient of the thermohaline circulation. The ESA's Soil Moisture and Ocean Salinity (SMOS) mission, launched in 2009, has the objective measuring soil moisture over the continents and sea surface salinity over the oceans. Although the mission was originally conceived for hydrological and oceanographic studies [1], SMOS is also making inroads in the cryospheric monitoring. SMOS carries an innovative L-band (1.4 GHz, or 21-cm wavelength), passive interferometric radiometer (the so-called MIRAS) that measures the electromagnetic radiation emitted by the Earth's surface, at about 50 km spatial resolution wide swath (1200-km), and with a 3-day revisit time at the equator, but a more frequent one at the poles. Although the SMOS radiometer operating frequency offers almost the maximum sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) variations, this is rather low, , i.e.,: 90% of ocean SSS values span a range of brightness temperatures of only 5K at L-band. This sensitivity is particularly low in cold waters. This implies that the SSS retrieval requires high radiometric performance. Since the SMOS launch, SSS Level 3 maps have been distributed by several expert laboratories including the Barcelona Expert Centre (BEC). However, since the TB sensitivity to SSS decreases with decreasing sea surface temperature (SST), large retrieval errors had been reported when retrieving salinity values at latitudes above 50⁰N. Two new processing algorithms, recently developed at BEC, have led to a considerable improvement of the SMOS data, allowing for the first time to derive SSS maps in cold waters. The first one is to empirically characterize and correct the systematic biases with six

SMOS near-real-time soil moisture product: processor overview and first validation results

NASA Astrophysics Data System (ADS)

Rodríguez-Fernández, Nemesio J.; Muñoz Sabater, Joaquin; Richaume, Philippe; de Rosnay, Patricia; Kerr, Yann H.; Albergel, Clement; Drusch, Matthias; Mecklenburg, Susanne

2017-10-01

Measurements of the surface soil moisture (SM) content are important for a wide range of applications. Among them, operational hydrology and numerical weather prediction, for instance, need SM information in near-real-time (NRT), typically not later than 3 h after sensing. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite is the first mission specifically designed to measure SM from space. The ESA Level 2 SM retrieval algorithm is based on a detailed geophysical modelling and cannot provide SM in NRT. This paper presents the new ESA SMOS NRT SM product. It uses a neural network (NN) to provide SM in NRT. The NN inputs are SMOS brightness temperatures for horizontal and vertical polarizations and incidence angles from 30 to 45°. In addition, the NN uses surface soil temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS). The NN was trained on SMOS Level 2 (L2) SM. The swath of the NRT SM retrieval is somewhat narrower (˜ 915 km) than that of the L2 SM dataset (˜ 1150 km), which implies a slightly lower revisit time. The new SMOS NRT SM product was compared to the SMOS Level 2 SM product. The NRT SM data show a standard deviation of the difference with respect to the L2 data of < 0.05 m3 m-3 in most of the Earth and a Pearson correlation coefficient higher than 0.7 in large regions of the globe. The NRT SM dataset does not show a global bias with respect to the L2 dataset but can show local biases of up to 0.05 m3 m-3 in absolute value. The two SMOS SM products were evaluated against in situ measurements of SM from more than 120 sites of the SCAN (Soil Climate Analysis Network) and the USCRN (US Climate Reference Network) networks in North America. The NRT dataset obtains similar but slightly better results than the L2 data. In summary, the NN SMOS NRT SM product exhibits performances similar to those of the Level 2 SM product but it has the advantage of

Spatial variability of soil moisture retrieved by SMOS satellite

NASA Astrophysics Data System (ADS)

Lukowski, Mateusz; Marczewski, Wojciech; Usowicz, Boguslaw; Rojek, Edyta; Slominski, Jan; Lipiec, Jerzy

2015-04-01

Standard statistical methods assume that the analysed variables are independent. Since the majority of the processes observed in the nature are continuous in space and time, this assumption introduces a significant limitation for understanding the examined phenomena. In classical approach, valuable information about the locations of examined observations is completely lost. However, there is a branch of statistics, called geostatistics, which is the study of random variables, but taking into account the space where they occur. A common example of so-called "regionalized variable" is soil moisture. Using in situ methods it is difficult to estimate soil moisture distribution because it is often significantly diversified. Thanks to the geostatistical methods, by employing semivariance analysis, it is possible to get the information about the nature of spatial dependences and their lengths. Since the Soil Moisture and Ocean Salinity mission launch in 2009, the estimation of soil moisture spatial distribution for regional up to continental scale started to be much easier. In this study, the SMOS L2 data for Central and Eastern Europe were examined. The statistical and geostatistical features of moisture distributions of this area were studied for selected natural soil phenomena for 2010-2014 including: freezing, thawing, rainfalls (wetting), drying and drought. Those soil water "states" were recognized employing ground data from the agro-meteorological network of ground-based stations SWEX and SMUDP2 data from SMOS. After pixel regularization, without any upscaling, the geostatistical methods were applied directly on Discrete Global Grid (15-km resolution) in ISEA 4H9 projection, on which SMOS observations are reported. Analysis of spatial distribution of SMOS soil moisture, carried out for each data set, in most cases did not show significant trends. It was therefore assumed that each of the examined distributions of soil moisture in the adopted scale satisfies

The SWEX at the area of Eastern Poland: Comparison of soil moisture obtained from ground measurements and SMOS satellite data*

NASA Astrophysics Data System (ADS)

Usowicz, J. B.; Marczewski, W.; Usowicz, B.; Lukowski, M. I.; Lipiec, J.; Slominski, J.

2012-04-01

Soil moisture, together with soil and vegetation characteristics, plays an important role in exchange of water and energy between the land surface and the atmospheric boundary layer. Accurate knowledge of current and future spatial and temporal variation in soil moisture is not well known, nor easy to measure or predict. Knowledge of soil moisture in surface and root zone soil moisture is critical for achieving sustainable land and water management. The importance of SM is so high that this ECV is recommended by GCOS (Global Climate Observing System) to any attempts of evaluating of effects the climate change, and therefore it is one of the goals for observing the Earth by the ESA SMOS Mission (Soil Moisture and Ocean Salinity), globally. SMOS provides its observations by means of the interferometric radiometry method (1.4 GHz) from the orbit. In parallel, ten ground based stations are kept by IA PAN, in area of the Eastern Wall in Poland, in order to validate SMOS data and for other ground based agrophysical purposes. Soil moisture measurements obtained from ground and satellite measurements from SMOS were compared using Bland-Altman method of agreement, concordance correlation coefficient (CCC) and total deviation index (TDI). Observed similar changes in soil moisture, but the values obtained from satellite measurements were lower. Minor differences between the compared data are at higher moisture contents of soil and they grow with decreasing soil moisture. Soil moisture trends are maintained in the individual stations. Such distributions of soil moisture were mainly related to soil type. * The work was financially supported in part by the ESA Programme for European Cooperating States (PECS), No.98084 "SWEX-R, Soil Water and Energy Exchange/Research", AO3275.

SMOS after 2 YEARS and a half in orbit

NASA Astrophysics Data System (ADS)

Kerr, Y.; Richaume, P.; Wigneron, J.-P.; Waldteufel, P.; Mecklenburg, S.; Cabot, F.; Boutin, J.; Font, J.; Reul, N.

2012-04-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface (with an accuracy goal of 0.04 m3/m3) and ocean salinity. These two geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge at a global scale is of interest for climatic and weather researches in particular in improving models forecasts. The purpose of this communication is to present the mission results after more than two years in orbit as well as some outstanding results already obtained. A special attention will be devoted to level 2 products. Modeling multi-angular brightness temperatures is not straightforward. The radiative model transfer model L-MEB (L-band Microwave Emission) is used over land while different models with different approaches as to the modeling of sea surface roughness are used over ocean surfaces. Over land the approach is based on semi-empirical relationships, adapted to different type of surface. The model computes a dielectric constant leading to surface emissivity. Surface features (roughness, vegetation) are also considered in the models. However, considering SMOS spatial resolution a wide area is seen by the instrument with strong heterogeneity. The L2 soil moisture retrieval scheme takes this into account. Brightness temperatures are computed for every classes composing a working area. A weighted function is applied for the incidence angle and the antenna beam. Once the brightness temperature is computed for the entire working area, the minimizing process starts. If no soil moisture is derived (not attempted or process failed) a dielectric constant is still derived from an simplified modeled (the cardioid model). SMOS data enabled very quickly to infer Sea surface salinity fields. As salinity retrieval is quite challenging, retrieving it enable to assess very

Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil moisture retrievals

NASA Astrophysics Data System (ADS)

Tian, Siyuan; Tregoning, Paul; Renzullo, Luigi J.; van Dijk, Albert I. J. M.; Walker, Jeffrey P.; Pauwels, Valentijn R. N.; Allgeyer, Sébastien

2017-03-01

The accuracy of global water balance estimates is limited by the lack of observations at large scale and the uncertainties of model simulations. Global retrievals of terrestrial water storage (TWS) change and soil moisture (SM) from satellites provide an opportunity to improve model estimates through data assimilation. However, combining these two data sets is challenging due to the disparity in temporal and spatial resolution at both vertical and horizontal scale. For the first time, TWS observations from the Gravity Recovery and Climate Experiment (GRACE) and near-surface SM observations from the Soil Moisture and Ocean Salinity (SMOS) were jointly assimilated into a water balance model using the Ensemble Kalman Smoother from January 2010 to December 2013 for the Australian continent. The performance of joint assimilation was assessed against open-loop model simulations and the assimilation of either GRACE TWS anomalies or SMOS SM alone. The SMOS-only assimilation improved SM estimates but reduced the accuracy of groundwater and TWS estimates. The GRACE-only assimilation improved groundwater estimates but did not always produce accurate estimates of SM. The joint assimilation typically led to more accurate water storage profile estimates with improved surface SM, root-zone SM, and groundwater estimates against in situ observations. The assimilation successfully downscaled GRACE-derived integrated water storage horizontally and vertically into individual water stores at the same spatial scale as the model and SMOS, and partitioned monthly averaged TWS into daily estimates. These results demonstrate that satellite TWS and SM measurements can be jointly assimilated to produce improved water balance component estimates.

On the Balancing of the SMOS Ocean Salinity Retrieval Cost Function

NASA Astrophysics Data System (ADS)

Sabia, R.; Camps, A.; Portabella, M.; Talone, M.; Ballabrera, J.; Gourrion, J.; Gabarró, C.; Aretxabaleta, A. L.; Font, J.

2009-04-01

producing spurious retrievals. In [4] it has been studied the impact of the different auxiliary salinity uncertainties in the accuracy of the retrieval. It has been shown that using physically-consistent salinity field uncertainties of the order of less than 0.5 psu (either as the standard deviation of the considered SSS field or as the standard deviation of the misfit between the original and the auxiliary SSS field) the SSS term turns out to be too constraining. A half-way solution could be envisaged by using empirical weights (regularization factors) which could smooth the overall influence of the SSS term still using the auxiliary fields with their corresponding physically-sounded uncertainties. This operation should be performed for the SST and wind speed term as well. The need for a comprehensive balancing of the different terms included in the cost function is also stressed by recent studies [5], which point out that the even the observational term (TBs) will need to be properly weighted by an effective ratio, taking into account the specific correlation patterns existing in the MIRAS measurements. Simulated data using the SMOS End-to-end Processor Simulator (SEPS), in its full-mode, including the measured antenna patterns for each antenna and all the instrument errors, are used in this study. The salinity retrieval process and the SSS maps (for each satellite overpass) are performed with UPC SMOS-Level 2 Processor Simulator (SMOS-L2PS). The relative weight for each of the terms included in the cost function (observational and background terms) is assessed in different cost function configurations. Regularization factors are introduced to ensure that SMOS information content is fully exploited. Preliminary results on the cost function balancing will be shown at the conference. References [1] Font, J., G. Lagerloef, D. Le Vine, A. Camps, and O.Z. Zanife, The Determination of Surface Salinity with the European SMOS Space Mission, IEEE Trans. Geosci. Remote Sens., 42

The Integration of SMOS Soil Moisture in a Consistent Soil Moisture Climate Record

NASA Astrophysics Data System (ADS)

de Jeu, Richard; Kerr, Yann; Wigneron, Jean Pierre; Rodriguez-Fernandez, Nemesio; Al-Yaari, Amen; van der Schalie, Robin; Dolman, Han; Drusch, Matthias; Mecklenburg, Susanne

2015-04-01

Recently, a study funded by the European Space Agency (ESA) was set up to provide guidelines for the development of a global soil moisture climate record with a special emphasis on the integration of SMOS. Three different data fusion approaches were designed and implemented on 10 year passive microwave data (2003-2013) from two different satellite sensors; the ESA Soil Moisture Ocean Salinity Mission (SMOS) and the NASA/JAXA Advanced Scanning Microwave Radiometer (AMSR-E). The AMSR-E data covered the period from January 2003 until Oct 2011 and SMOS data covered the period from June 2010 until the end of 2013. The fusion approaches included a neural network approach (Rodriguez-Fernandez et al., this conference session HS6.4), a regression approach (Wigneron et al., 2004), and an approach based on the baseline algorithm of ESAs current Climate Change Initiative soil moisture program, the Land Parameter Retrieval Model (Van der Schalie et al., this conference session HS6.4). With this presentation we will show the first results from this study including a description of the different approaches and the validation activities using both globally covered modeled datasets and ground observations from the international soil moisture network. The statistical validation analyses will give us information on the temporal and spatial performance of the three different approaches. Based on these results we will then discuss the next steps towards a seamless integration of SMOS in a consistent soil moisture climate record. References Wigneron J.-P., J.-C. Calvet, P. de Rosnay, Y. Kerr, P. Waldteufel, K. Saleh, M. J. Escorihuela, A. Kruszewski, 'Soil Moisture Retrievals from Bi-Angular L-band Passive Microwave Observations', IEEE Trans. Geosc. Remote Sens. Let., vol 1, no. 4, 277-281, 2004.

Uncertainty Quantification of GEOS-5 L-band Radiative Transfer Model Parameters Using Bayesian Inference and SMOS Observations

NASA Technical Reports Server (NTRS)

DeLannoy, Gabrielle J. M.; Reichle, Rolf H.; Vrugt, Jasper A.

2013-01-01

Uncertainties in L-band (1.4 GHz) radiative transfer modeling (RTM) affect the simulation of brightness temperatures (Tb) over land and the inversion of satellite-observed Tb into soil moisture retrievals. In particular, accurate estimates of the microwave soil roughness, vegetation opacity and scattering albedo for large-scale applications are difficult to obtain from field studies and often lack an uncertainty estimate. Here, a Markov Chain Monte Carlo (MCMC) simulation method is used to determine satellite-scale estimates of RTM parameters and their posterior uncertainty by minimizing the misfit between long-term averages and standard deviations of simulated and observed Tb at a range of incidence angles, at horizontal and vertical polarization, and for morning and evening overpasses. Tb simulations are generated with the Goddard Earth Observing System (GEOS-5) and confronted with Tb observations from the Soil Moisture Ocean Salinity (SMOS) mission. The MCMC algorithm suggests that the relative uncertainty of the RTM parameter estimates is typically less than 25 of the maximum a posteriori density (MAP) parameter value. Furthermore, the actual root-mean-square-differences in long-term Tb averages and standard deviations are found consistent with the respective estimated total simulation and observation error standard deviations of m3.1K and s2.4K. It is also shown that the MAP parameter values estimated through MCMC simulation are in close agreement with those obtained with Particle Swarm Optimization (PSO).

Faraday Rotation for SMOS Retrievals of Ocean Salinity and Soil Moisture

NASA Technical Reports Server (NTRS)

El-Nimri, Salem; Le Vine, David M.

2016-01-01

Faraday rotation is a change in polarization as radiation propagates from the surface through the ionosphere to the sensor. At L-band (1.4 GHz) this change can be significant and can be important for the remote sensing of soil moisture and ocean salinity from space. Consequently, modern L-band radiometers (SMOS, Aquarius and SMOS) are polarimetric to measure Faraday rotation in situ so that a correction can be made. This is done using the ratio of the third and second Stokes parameters. In the case of SMOS this procedure has produced very noisy estimates. An alternate procedure is reported here in which the total electron content is estimated and averaged to reduce noise.

Droughts and floods monitoring in Poland with SMOS, SEVIRI and model data

NASA Astrophysics Data System (ADS)

Kotarba, A. Z.; Stankiewicz, K.; Słomiński, J.; Słomińska, E.; Marczewski, W.

2012-04-01

Droughts and floods represent the extreme cases of hydrological regime. Both significantly influence ecological processes in the environment as well as socio-economic situation of human activity. Measurements of soil moisture and rainfall is being recognized as fundamental for droughts and floods monitoring. We used Soil Moisture and Ocean Salinity (SMOS) L2 soil moisture data and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) rain rate approximation to evaluate the intensity and extend of droughts/floods events in Poland in 2010 and 2011. SEVIRI Multi-Sensor Precipitation Estimate rain rates were used for calculation of monthly rain accumulation (24 SEVIRI L2 datasets per day), then projected to match SMOS spatial reference. Based on SEVIRI data, monthly sum of precipitation was estimated for each SMOS DGG cell within area of interest (the ROI covers Poland and the closest neighborhood). At the DGG level, SMOS SM and SEVIRI precipitation data were compared for each month since May 2010. Nearly two year series provided a background for droughts and floods events. Final L3 products of SMOS SM and SEVIRI precipitation were compared with operational, traditionally-developed drought risk maps, in order to evaluate the degree of agreement between remotely sensed products and models calculated with surface-based measurements only.

Rainfall estimation over-land using SMOS soil moisture observations: SM2RAIN, LMAA and SMART algorithms

NASA Astrophysics Data System (ADS)

Massari, Christian; Brocca, Luca; Pellarin, Thierry; Kerr, Yann; Crow, Wade; Cascon, Carlos; Ciabatta, Luca

2016-04-01

Recent advancements in the measurement of precipitation from space have provided estimates at scales that are commensurate with the needs of the hydrological and land-surface model communities. However, as demonstrated in a number of studies (Ebert et al. 2007, Tian et al. 2007, Stampoulis et al. 2012) satellite rainfall estimates are characterized by low accuracy in certain conditions and still suffer from a number of issues (e.g., bias) that may limit their utility in over-land applications (Serrat-Capdevila et al. 2014). In recent years many studies have demonstrated that soil moisture observations from ground and satellite sensors can be used for correcting satellite precipitation estimates (e.g. Crow et al., 2011; Pellarin et al., 2013), or directly estimating rainfall (SM2RAIN, Brocca et al., 2014). In this study, we carried out a detailed scientific analysis in which these three different methods are used for: i) estimating rainfall through satellite soil moisture observations (SM2RAIN, Brocca et al., 2014); ii) correcting rainfall through a Land surface Model Assimilation Algorithm (LMAA) (an improvement of a previous work of Crow et al. 2011 and Pellarin et al. 2013) and through the Soil Moisture Analysis Rainfall Tool (SMART, Crow et al. 2011). The analysis is carried within the ESA project "SMOS plus Rainfall" and involves 9 sites in Europe, Australia, Africa and USA containing high-quality hydrometeorological and soil moisture observations. Satellite soil moisture data from Soil Moisture and Ocean Salinity (SMOS) mission are employed for testing their potential in deriving a cumulated rainfall product at different temporal resolutions. The applicability and accuracy of the three algorithms is investigated also as a function of climatic and soil/land use conditions. A particular attention is paid to assess the expected limitations soil moisture based rainfall estimates such as soil saturation, freezing/snow conditions, SMOS RFI, irrigated areas

Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets

USDA-ARS?s Scientific Manuscript database

Two satellites are currently monitoring surface soil moisture (SM) from L-band observations: SMOS (Soil Moisture and Ocean Salinity), a European Space Agency (ESA) satellite that was launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration...

Using SMOS brightness temperature and derived surface-soil moisture to characterize surface conditions and validate land surface models.

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Piles, Maria; Gelati, Emiliano; de Rosnay, Patricia

2017-04-01

The SMOS satellite, operated by ESA, observes the surface in the L-band. On continental surface these observations are sensitive to moisture and in particular surface-soil moisture (SSM). In this presentation we will explore how the observations of this satellite can be exploited over the Iberian Peninsula by comparing its results with two land surface models : ORCHIDEE and HTESSEL. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies. When comparing the surface-soil moisture of the models with the product derived operationally by ESA from SMOS observations similar results are found. The spatial correlation over the IP between SMOS and ORCHIDEE SSM estimates is poor (ρ 0.3). A single value decomposition (SVD) analysis of rainfall and SSM shows that the co-varying patterns of these variables are in reasonable agreement between both products. Moreover the first three SVD soil moisture patterns explain over 80% of the SSM variance simulated by the model while the explained fraction is only 52% of the remotely sensed values. These results suggest that the rainfall-driven soil moisture variability may not account for the poor spatial correlation between SMOS and ORCHIDEE products. Other reasons have to

Comparisons of evening and morning SMOS passes over the Midwest United States

USDA-ARS?s Scientific Manuscript database

This study investigates differences in the soil moisture product and brightness temperatures between 6 pm and 6 am local solar time, when the SMOS passes for a region in north-central Iowa. This region consists of 69 SMOS pixels and has uniform land-cover, consisting of maize and soybean row crops. ...

Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC

NASA Astrophysics Data System (ADS)

Ebrahimi-Khusfi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-05-01

This study was carried out to evaluate possible improvements of the soil moisture (SM) retrievals from the SMAP observations, based on the synergy between SMAP and SMOS. We assessed the impacts of the vegetation and soil roughness parameters on SM retrievals from SMAP observations. To do so, the effects of three key input parameters including the vegetation optical depth (VOD), effective scattering albedo (ω) and soil roughness (HR) parameters were assessed with the emphasis on the synergy with the VOD product derived from SMOS-IC, a new and simpler version of the SMOS algorithm, over two years of data (April 2015 to April 2017). First, a comprehensive comparison of seven SM retrieval algorithms was made to find the best one for SM retrievals from the SMAP observations. All results were evaluated against in situ measurements over 548 stations from the International Soil Moisture Network (ISMN) in terms of four statistical metrics: correlation coefficient (R), root mean square error (RMSE), bias and unbiased RMSE (UbRMSE). The comparison of seven SM retrieval algorithms showed that the dual channel algorithm based on the additional use of the SMOS-IC VOD product (selected algorithm) led to the best results of SM retrievals over 378, 399, 330 and 271 stations (out of a total of 548 stations) in terms of R, RMSE, UbRMSE and both R & UbRMSE, respectively. Moreover, comparing the measured and retrieved SM values showed that this synergy approach led to an increase in median R value from 0.6 to 0.65 and a decrease in median UbRMSE from 0.09 m3/m3 to 0.06 m3/m3. Second, using the algorithm selected in a first step and defined above, the ω and HR parameters were calibrated over 218 rather homogenous ISMN stations. 72 combinations of various values of ω and HR were used for the calibration over different land cover classes. In this calibration process, the optimal values of ω and HR were found for the different land cover classes. The obtained results indicated that the

SMOS+RAINFALL: Evaluating the ability of different methodologies to improve rainfall estimations using soil moisture data from SMOS

NASA Astrophysics Data System (ADS)

Pellarin, Thierry; Brocca, Luca; Crow, Wade; Kerr, Yann; Massari, Christian; Román-Cascón, Carlos; Fernández, Diego

2017-04-01

Recent studies have demonstrated the usefulness of soil moisture retrieved from satellite for improving rainfall estimations of satellite based precipitation products (SBPP). The real-time version of these products are known to be biased from the real precipitation observed at the ground. Therefore, the information contained in soil moisture can be used to correct the inaccuracy and uncertainty of these products, since the value and behavior of this soil variable preserve the information of a rain event even for several days. In this work, we take advantage of the soil moisture data from the Soil Moisture and Ocean Salinity (SMOS) satellite, which provides information with a quite appropriate temporal and spatial resolution for correcting rainfall events. Specifically, we test and compare the ability of three different methodologies for this aim: 1) SM2RAIN, which directly relate changes in soil moisture to rainfall quantities; 2) The LMAA methodology, which is based on the assimilation of soil moisture in two models of different complexity (see EGU2017-5324 in this same session); 3) The SMART method, based on the assimilation of soil moisture in a simple hydrological model with a different assimilation/modelling technique. The results are tested for 6 years over 10 sites around the world with different features (land surface, rainfall climatology, orography complexity, etc.). These preliminary and promising results are shown here for the first time to the scientific community, as also the observed limitations of the different methodologies. Specific remarks on the technical configurations, filtering/smoothing of SMOS soil moisture or re-scaling techniques are also provided from the results of different sensitivity experiments.

Upper-soil moisture inter-comparison from SMOS's products and land surface models over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Polcher, Jan; Barella-Ortiz, Anaïs; Aires, Filipe; Balsamo, Gianpaolo; Gelati, Emiliano; Rodríguez-Fernández, Nemesio

2015-04-01

Soil moisture is a key state variable of the hydrological cycle. It conditions runoff, infiltration and evaporation over continental surfaces, and is key for forecasting droughts and floods. It plays thus an important role in surface-atmosphere interactions. Surface Soil Moisture (SSM) can be measured by in situ measurements, by satellite observations or modelled using land surface models. As a complementary tool, data assimilation can be used to combine both modelling and satellite observations. The work presented here is an inter-comparison of retrieved and modelled SSM data, for the 2010 - 2012 period, over the Iberian Peninsula. The region has been chosen because its vegetation cover is not very dense and includes strong contrasts in the rainfall regimes and thus a diversity of behaviours for SSM. Furthermore this semi-arid region is strongly dependent on a good management of its water resources. Satellite observations correspond to the Soil Moisture and Ocean Salinity (SMOS) retrievals: the L2 product from an optimal interpolation retrieval, and 3 other products using Neural Network retrievals with different input information: SMOS time indexes, purely SMOS data, or addition of the European Advanced Scaterometer (ASCAT) backscattering, and the Moderate-Resolution Imaging Spectrometer (MODIS) surface temperature information. The modelled soil moistures have been taken from the ORCHIDEE (ORganising Carbon and Hydrology In Dynamic EcosystEms) and the HTESSEL (Hydrology-Tiled ECMWF Scheme for Surface Exchanges over Land) land surface models. Both models are forced with the same atmospheric conditions (as part of the Earth2Observe FP7 project) over the period but they represent the surface soil moisture with very different degrees of complexity. ORCHIDEE has 5 levels in the top 5 centimetres of soil while in HTESSEL this variable is part of the top soil moisture level. The two types of SMOS retrievals are compared to the model outputs in their spatial and temporal

Exploiting the synergy between SMAP and SMOS to improve brightness temperature simulations and soil moisture retrievals in arid regions

NASA Astrophysics Data System (ADS)

Ebrahimi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-02-01

The objective of this study was to exploit the synergy between SMOS and SMAP based on vegetation optical depth (VOD) to improve brightness temperature (TB) simulations and land surface soil moisture (SM) retrievals in arid regions of the world. In the current operational algorithm of SMAP (level 2), vegetation water content (VWC) is considered as a proxy to compute VOD which is calculated by an empirical conversion function of NDVI. Avoiding the empirical estimation of VOD, the SMOS algorithm is used to retrieve simultaneously SM and VOD from TB observations. The present study attempted to improve SMAP TB simulations and SM retrievals by benefiting from the advantages of the SMOS (L-MEB) algorithm. This was achieved by using a synergy method based on replacing the default value of SMAP VOD with the retrieved value of VOD from the SMOS multi angular and bi-polarization observations of TB. The insitu SM measurements, used as reference SM in this study, were obtained from the International Soil Moisture Network (ISMN) over 180 stations located in arid regions of the world. Furthermore, four stations were randomly selected to analyze the temporal variations in VOD and SM. Results of the synergy method showed that the accuracy of the TB simulations and SM retrievals was respectively improved at 144 and 124 stations (out of a total of 180 stations) in terms of coefficient of determination (R2) and unbiased root mean squared error (UbRMSE). Analyzing the temporal variations in VOD showed that the SMOS VOD, conversely to the SMAP VOD, can better illustrate the presence of herbaceous plants and may be a better indicator of the seasonal changes in the vegetation density and biomass over the year.

A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm

NASA Astrophysics Data System (ADS)

Fernandez-Moran, R.; Wigneron, J.-P.; De Lannoy, G.; Lopez-Baeza, E.; Parrens, M.; Mialon, A.; Mahmoodi, A.; Al-Yaari, A.; Bircher, S.; Al Bitar, A.; Richaume, P.; Kerr, Y.

2017-10-01

This study focuses on the calibration of the effective vegetation scattering albedo (ω) and surface soil roughness parameters (HR, and NRp, p = H,V) in the Soil Moisture (SM) retrieval from L-band passive microwave observations using the L-band Microwave Emission of the Biosphere (L-MEB) model. In the current Soil Moisture and Ocean Salinity (SMOS) Level 2 (L2), v620, and Level 3 (L3), v300, SM retrieval algorithms, low vegetated areas are parameterized by ω = 0 and HR = 0.1, whereas values of ω = 0.06 - 0.08 and HR = 0.3 are used for forests. Several parameterizations of the vegetation and soil roughness parameters (ω, HR and NRp, p = H,V) were tested in this study, treating SMOS SM retrievals as homogeneous over each pixel instead of retrieving SM over a representative fraction of the pixel, as implemented in the operational SMOS L2 and L3 algorithms. Globally-constant values of ω = 0.10, HR = 0.4 and NRp = -1 (p = H,V) were found to yield SM retrievals that compared best with in situ SM data measured at many sites worldwide from the International Soil Moisture Network (ISMN). The calibration was repeated for collections of in situ sites classified in different land cover categories based on the International Geosphere-Biosphere Programme (IGBP) scheme. Depending on the IGBP land cover class, values of ω and HR varied, respectively, in the range 0.08-0.12 and 0.1-0.5. A validation exercise based on in situ measurements confirmed that using either a global or an IGBP-based calibration, there was an improvement in the accuracy of the SM retrievals compared to the SMOS L3 SM product considering all statistical metrics (R = 0.61, bias = -0.019 m3 m-3, ubRMSE = 0.062 m3 m-3 for the IGBP-based calibration; against R = 0.54, bias = -0.034 m3 m-3 and ubRMSE = 0.070 m3 m-3 for the SMOS L3 SM product). This result is a key step in the calibration of the roughness and vegetation parameters in the operational SMOS retrieval algorithm. The approach presented here is the

Mitigation of biases in SMOS Level 2 soil moisture retrieval algorithm

NASA Astrophysics Data System (ADS)

Mahmoodi, Ali; Richaume, Philippe; Kerr, Yann

2017-04-01

The Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA) relies on the L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer models to retrieve soil moisture (SM). These models require, as input, parameters which characterize the target like soil water content and temperature. The Soil Water Volume at Level 1 (SWVL1) from the European Centre for Medium-Range Weather Forecast (ECMWF) is used in the SMOS Level 2 SM algorithms as both an initial guess for SM in the iterative retrieval process and to compute fixed contributions from the so called "default" fractions. In case of mixed fractions of nominal (low vegetation land) and forest, retrieval is performed over one fraction while the contribution of the other is assumed to be fixed and known based on ECMWF data. Studies have shown that ECMWF SWVL1 is biased when compared to SMOS SM and represents values at a deeper layer of soil ( 7 cm) than that represented by SMOS ( 2 to 5 cm). This study uses a well know bias reduction technique based on matching of the Cumulative Distribution Functions (CDF) of the two distributions to help reduce the biases. Early results using a linear matching method provide very encouraging results. A complication with respect to performing CDF matching is that SMOS SM values are not available where they are needed, i.e. over the default fractions. In order to remedy this, we treat mixed fractions as homogeneous targets to retrieve SM over the whole target. The obtained values are then used to derive the CDF matching coefficients. A set of CDF coefficients derived using average and standard deviation of soil moisture values for 2014 has been used in reprocessing SMOS data for 2014 and 2015, as well as over selected sites (with in-situ data) over a longer period. The 2014 was selected due to its lower Radio Frequency Interference (RFI) contamination in comparison with other years. The application of CDF coefficients has lead to a wetter SM for

Inferring Land Surface Model Parameters for the Assimilation of Satellite-Based L-Band Brightness Temperature Observations into a Soil Moisture Analysis System

NASA Technical Reports Server (NTRS)

Reichle, Rolf H.; De Lannoy, Gabrielle J. M.

2012-01-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission provides global measurements of L-band brightness temperatures at horizontal and vertical polarization and a variety of incidence angles that are sensitive to moisture and temperature conditions in the top few centimeters of the soil. These L-band observations can therefore be assimilated into a land surface model to obtain surface and root zone soil moisture estimates. As part of the observation operator, such an assimilation system requires a radiative transfer model (RTM) that converts geophysical fields (including soil moisture and soil temperature) into modeled L-band brightness temperatures. At the global scale, the RTM parameters and the climatological soil moisture conditions are still poorly known. Using look-up tables from the literature to estimate the RTM parameters usually results in modeled L-band brightness temperatures that are strongly biased against the SMOS observations, with biases varying regionally and seasonally. Such biases must be addressed within the land data assimilation system. In this presentation, the estimation of the RTM parameters is discussed for the NASA GEOS-5 land data assimilation system, which is based on the ensemble Kalman filter (EnKF) and the Catchment land surface model. In the GEOS-5 land data assimilation system, soil moisture and brightness temperature biases are addressed in three stages. First, the global soil properties and soil hydraulic parameters that are used in the Catchment model were revised to minimize the bias in the modeled soil moisture, as verified against available in situ soil moisture measurements. Second, key parameters of the "tau-omega" RTM were calibrated prior to data assimilation using an objective function that minimizes the climatological differences between the modeled L-band brightness temperatures and the corresponding SMOS observations. Calibrated parameters include soil roughness parameters, vegetation structure parameters

Sea Surface Salinity signatures of tropical instability waves: New evidences from SMOS

NASA Astrophysics Data System (ADS)

Yin, Xiaobin; Boutin, Jacqueline; Reverdin, Gilles; Lee, Tong; Martin, Nicolas

2014-05-01

The European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, has been providing global maps of sea surface salinity (SSS) since 2010. SSS measurements from the SMOS satellite during June 2010 and December 2012 provide an unprecedented space-borne observation of the salinity structure of tropical instability waves (TIWs) including strong La Niña conditions during recent years. We use SMOS level 3 SSS maps averaged over 100 x 100 km2 with a 10-day running window and sampled daily over a 0.25 x 0.25° grid generated at Laboratoire d'Océanographie et du Climat: Expérimentation et Approches Numériques (http://catds.ifremer.fr/Products/Available-products-from-CEC-OS/Locean-v2013) [Boutin et al., 2013; Yin et al., 2012]. We also analyze daily SST from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) produced on an operational basis at the UK Met Office using optimal interpolation [Donlon et al., 2011]. From a time-longitude section in the eastern Pacific ocean, westward propagations of SSS and SST anomalies along 2° N became apparent west of 90° W during June 2010 - March 2011 and June 2011 - March 2012, coincident with negative indexes in the NINO3 and NINO3.4 regions. The 33-day SSS anomaly and SST anomaly appeared together approximately in the same time and regions. The 17-day SSS anomaly is less clear than the 17-day SST anomaly. The SSS anomaly has approximate amplitude of 0.5 practical salinity scale (pss) and the SST anomaly has approximate amplitude of 2 ° C. Then, we focus on analysis of SSS and SST anomalies during June to December 2010. During this period the tropical Pacific was characterized by a strong La Niña, providing favorable conditions for the occurrence of TIWs. The high anomalies and meridional gradients of both SSS and SST appear north of the equator west of 100° W. Near 100W, they straddle the equator where South Pacific water and eastern edge upwelling water with high

An overview of new insights from 6 years of salinity data from SMOS mission

NASA Astrophysics Data System (ADS)

Nicolas, R.

2015-12-01

Measurements of salt held in surface seawater are becoming ever-more important for oceanographers and climatologists to gain a deeper understanding of ocean circulation and Earth's water cycle. ESA's SMOS mission is proving essential for this aim. Launched in 2009, SMOS has provided the longest continuous record (now ~6 years) of sea-surface salinity measurements from space. The salinity of surface seawater is controlled largely by the balance between evaporation and precipitation, but freshwater from rivers and the freezing and melting of ice also cause changes in concentrations. Along with temperature, salinity drives ocean circulation - the thermohaline circulation - which, in turn, plays a key role in the global climate. With a wealth of salinity data from SMOS now in hand complemented by measurements from the NASA-CONAE Aquarius satellite, which uses a different measuring technique. In this talk we shall provide an overview of how the SMOS mission - now celebrating 6 years in orbit - is providing detailed global measurements of SSS. An ensemble of key ocean processes for climate and biochemistry can now be determined and monitored for the first time from space : the detailed salinity structure of tropical instability waves along the equator and the salt exchanged across major oceanic current fronts, the occurrences of large-scale salinity anomalies in the Pacific and Indian oceans related to important climate indexes are also well-evidenced in the six year-long data. In addition, the dispersal of freshwater into the ocean from the major large tropical rivers (Amazon, Orinoco and Congo), their impact on tropical cyclone (TC) intensification and the oceanic imprints of the intense rainfall in the ITCZ and under TC can now be regularly monitored to better understand the variability of the oceanic part of the global water cycle. We will present how SMOS data, along with concurrent in situ Argo ocean-profile data, other satellite observations of sea

SMOS and SMAP: from Lessons Learned to Future Mission Requirements

NASA Astrophysics Data System (ADS)

Kerr, Y. H.; Wigneron, J. P.; Cabot, F.; Escorihuela, M. J.; Anterrieu, E.; Rouge, B.; Rodriguez Fernandez, N.; Bindlish, R.; Khazaal, A.; Al-Bitar, A.; Mialon, A.; Lesthievent, G.

2017-12-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface, vegetation water content over land, and ocean salinity. The Soil Moisture and Ocean Salinity mission has now been collecting data for over 7 years. TheSoil Moisture Active and Passive for over 2 years.The two data set have been reprocessed (Version 620 for levels 1 and 2 and version 3 for level 3 CATDS) to be merged into one product, while operational near real time soil moisture data is now available and assimilation of SMOS data in NWP has proved successful. After 7 years of L-Band data acquisition, it seems important to start using data for having a look at anomalies and see how they can relate to large scale events. We have also produced a 15 year soil moisture data set by merging SMOS and AMSR using a neural network approach. The purpose of this communication is to present the two mission results after more than seven years in orbit in a climatic trend perspective, as through such a period anomalies can be detected. Thereby we benefit from consistent datasets provided through the latest reprocessing using most recent algorithm enhancements. Using the above mentioned products it is possible to follow large events such as the evolution of the droughts in North America, or water fraction evolution over the Amazonian basin. In this occasion we will focus on the analysis of SMOS and ancillary products anomalies to reveal two climatic trends, the temporal evolution of water storage over the Indian continent in relation to rainfall anomalies, and the global impact of El Nino types of events on the general water storage distribution. This presentation shows in detail the use of long term data sets of L-band microwave radiometry in two specific cases, namely droughts and water budget over a large basin. Several other analyses are under way currently. Obviously

Use of Physio-Hydrological Units for SMOS Validation at the Valencia Anchor Station Study Area

NASA Astrophysics Data System (ADS)

Millán-Scheiding, C.; Antolín, C.; Marco, J.; Soriano, M. P.; Torre, E.; Requena, F.; Carbó, E.; Cano, A.; Lopez-Baeza, E.

2009-04-01

Probe measurements (with 3 repetitions each), covering the whole area. This experimental campaign permits the characterization of the soil moisture distribution within each physio-hydrological unit and results in a soil moisture map of the VAS site. All of it used for the validation of the aircraft observations done throughout the campaign. The ground measurement results obtained indicate that soil properties and vegetation cover are the parameters of the physio-hydrological units that most influence the moisture of the soil. This relationship will permit a more simple delimitation of the physio-hydrological Units and a reduction of the number of sample points for the calibration/validation of SMOS products. References: Lopez-Baeza, E., R. Acosta, M.C. Antolin, F. Belda, A. Cano, E. Carbo, M. Crapeau, A. Fidalgo S. Juglea, Y. Kerr, B. Martinez, C. Millan-Scheiding, D. Rodriguez, K. Saleh, J. Sanchis, J.-P. Wigneron(10), Other Contributors: J.E. Balling, C. Domenech, EOLAB, A.G. Ferreira J. Ferrer, J. Grant, J. Marco C. Narbon, B. Navascues, OCEANSNELL, E. Rodriguez-Camino, N. Skou, S. Søbjærg, P. Soriano, J. Tamayo, S. Tauriainen, E. Torre G. Torregrosa, A. Velazquez Blazquez, S. Vidal (2008): Validation of SMOS Products over Mediterranean Ecosystem Vegetation at the Valencia Anchor Station Reference Area. SMOS Cal/Val AO I.D. no. 3252. Experimental Plan SMOS Validation Rehearsal Campaign. University of Valencia, April 2008 Millan-Scheiding, C. (2006): Aproximación a la Humedad del Suelo en el Altiplano de Requena-Utiel. Preparación para la Campaña de Cal/Val de la Misión Espacial SMOS. Trabajo de Investigación de III Ciclo. Universidad de Valencia. Millán-Scheiding, C., C. Antolín, A. Cano, E. López-Baeza (2007): Uso de Unidades Fisio-Hidrológicas en la Monitorización de la Humedad del Suelo con SMOS. III Simposio Nacional sobre el Control de la Degradación de Suelos y la Desertificación. Costa Calma (Pájara), Fuerteventura, 16 al 20 de Septiembre 2007

SMOS brightness temperature assimilation into the Community Land Model

NASA Astrophysics Data System (ADS)

Rains, Dominik; Han, Xujun; Lievens, Hans; Montzka, Carsten; Verhoest, Niko E. C.

2017-11-01

SMOS (Soil Moisture and Ocean Salinity mission) brightness temperatures at a single incident angle are assimilated into the Community Land Model (CLM) across Australia to improve soil moisture simulations. Therefore, the data assimilation system DasPy is coupled to the local ensemble transform Kalman filter (LETKF) as well as to the Community Microwave Emission Model (CMEM). Brightness temperature climatologies are precomputed to enable the assimilation of brightness temperature anomalies, making use of 6 years of SMOS data (2010-2015). Mean correlation R with in situ measurements increases moderately from 0.61 to 0.68 (11 %) for upper soil layers if the root zone is included in the updates. A reduced improvement of 5 % is achieved if the assimilation is restricted to the upper soil layers. Root-zone simulations improve by 7 % when updating both the top layers and root zone, and by 4 % when only updating the top layers. Mean increments and increment standard deviations are compared for the experiments. The long-term assimilation impact is analysed by looking at a set of quantiles computed for soil moisture at each grid cell. Within hydrological monitoring systems, extreme dry or wet conditions are often defined via their relative occurrence, adding great importance to assimilation-induced quantile changes. Although still being limited now, longer L-band radiometer time series will become available and make model output improved by assimilating such data that are more usable for extreme event statistics.

Combining SMOS with visible and near/shortwave/thermal infrared satellite data for high resolution soil moisture estimates

NASA Astrophysics Data System (ADS)

Sánchez-Ruiz, Sergio; Piles, María; Sánchez, Nilda; Martínez-Fernández, José; Vall-llossera, Mercè; Camps, Adriano

2014-08-01

Sensors in the range of visible and near-shortwave-thermal infrared regions can be used in combination with passive microwave observations to provide soil moisture maps at much higher spatial resolution than the original resolution of current radiometers. To do so, a new downscaling algorithm ultimately based on the land surface temperature (LST) - Normalized Difference Vegetation Index (NDVI) - Brightness Temperature (TB) relationship is used, in which shortwave infrared indices are used as vegetation descriptors, instead of the more common near infrared ones. The theoretical basis of those indices, calculated as the normalized ratio of the 1240, 1640 and 2130 nm shortwave infrared (SWIR) bands and the 858 nm near infrared (NIR) band indicate that they are able to provide estimates of the vegetation water content. These so-called water indices extracted from MODIS products, have been used together with MODIS LST, and SMOS TB to improve the spatial resolution of ∼40 km SMOS soil moisture estimates. The aim was to retrieve soil moisture maps with the same accuracy as SMOS, but at the same resolution of the MODIS dataset, i.e., 500 m, which were then compared against in situ measurements from the REMEDHUS network in Spain. Results using two years of SMOS and MODIS data showed a similar performance for the four indices, with slightly better results when using the index derived from the first SWIR band. For the areal-average, a coefficient of correlation (R) of ∼0.61 and ∼0.72 for the morning and afternoon orbits, respectively, and a centered root mean square difference (cRMSD) of ∼0.04 m3 m-3 for both orbits was obtained. A twofold improvement of the current versions of this downscaling approach has been achieved by using more frequent and higher spatial resolution water indexes as vegetation descriptors: (1) the spatial resolution of the resulting soil moisture maps can be enhanced from ∼40 km up to 500 m, and (2) more accurate soil moisture maps (in terms

Aquarius and SMOS detect effects of an extreme Mississippi River flooding event in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Gierach, Michelle M.; Vazquez-Cuervo, Jorge; Lee, Tong; Tsontos, Vardis M.

2013-10-01

surface salinity (SSS) measurements from the Aquarius/Satélite de Aplicaciones Científicas (SAC)-D satellite and Soil Moisture and Ocean Salinity (SMOS) mission were used to document the freshening associated with the record 2011 Mississippi River flooding event in the Gulf of Mexico (GoM). Assessment of the salinity response was aided by additional satellite observations, including chlorophyll-a (chl-a) and ocean surface currents, and a passive tracer simulation. Low SSS values associated with the spreading of the river plume were observed 1-3 months after peak river discharge which then receded and became unidentifiable from satellite observations 5 months after maximum discharge. The seasonal wind pattern and general circulation of the GoM dramatically impacted the observed salinity response, transporting freshwater eastward along the Gulf coast and entraining low salinity waters into the open GoM. The observed salinity response from Aquarius was consistent with SMOS SSS, chl-a concentrations, and the passive tracer simulation in terms of the pathway and transit time of the river plume spreading. This study is the first successful application of satellite SSS to study salinity variation in marginal seas.

Validation/Calibration of SMOS L2 Soil Moisture in Crop Area, Eastern China

NASA Astrophysics Data System (ADS)

Cui, Huizhen; Jiang, Lingmei; Yang, Na; Lu, Zheng

2016-08-01

The Soil Moisture and Ocean Salinity (SMOS) is the worldwide satellite dedicated to retrieve soil moisture information at the global scale, with a high temporal resolution, and from space borne L-band 2-D interferometry radiometer. Product validation for the accuracy of data and utilization is a crucial step. At present, the validation work carried out in China was mainly concentrated in the Tibetan Plateau. The study of this paper mainly focused on the validation of SMOS L2 soil moisture data products in the north of Henan province plain region. This region is in front of Taihang Mountains. Results from the average-average and node- site comparison show that the correlation coefficients (R) between 0.20 and 0.40, also the existence of dry bias mainly concentrated in the 0.07 0.11m3m-3. Finally, this paper analysed the influence factors on the quality of SMOS soil moisture products.

Inter-Comparison of SMOS and Aquarius Sea Surface Salinity: Effects of the Dielectric Constant and Vicarious Calibration

NASA Technical Reports Server (NTRS)

Dinnat, Emmanuel P.; Boutin, Jacqueline; Yin, Xiaobin; Le Vine, David M.

2014-01-01

Two spaceborne instruments share the scientific objective of mapping the global Sea Surface Salinity (SSS). ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometry to retrieve SSS. We find that SSS retrieved by SMOS is generally lower than SSS retrieved by Aquarius, except for very cold waters where SMOS SSS is higher overall. The spatial distribution of the differences in SSS is similar to the distribution of sea surface temperature. There are several differences in the retrieval algorithm that could explain the observed SSS differences. We assess the impact of the dielectric constant model and the ancillary sea surface salinity used by both missions for calibrating the radiometers and retrieving SSS. The differences in dielectric constant model produce differences in SSS of the order of 0.3 psu and exhibit a dependence on latitude and temperature. We use comparisons with the Argo in situ data to assess the performances of the model in various regions of the globe. Finally, the differences in the ancillary sea surface salinity products used to perform the vicarious calibration of both instruments are relatively small (0.1 psu), but not negligible considering the requirements for spaceborne remote sensing of SSS.

Mesoscale Turbulence in the Ocean and Synergy of Variables: Merging of Smos and Aquarius SSS Maps Using New, Non-Parametric Methods

NASA Astrophysics Data System (ADS)

Turiel, A.; Umbert, M.; Hoareau, N.; Ballabrera-Poy, J.; Font, J.

2012-12-01

Remote sensing platforms onboard satellites provide synoptic maps of ocean surface and thus an accurate picture of many processes taking place in the ocean at mesoscale and sub-mesoscale levels mainly can be gained. Since the first ocean observation satellites these images has been exploited to assess ocean processes; however, extracting further dynamic information from remote sensing maps generally implies a higher degree of processing complexity, involving the use of numerical models and assimilation schemes. A critical variable for the understanding the climate system is Sea Surface Salinity (SSS). The arrival of SMOS and Aquarius missions has given us access to SSS in a regular basis. However, those images still suffer of many acquisition and processing issues, what precludes gaining a complete picture of ocean surface dynamics. In order to favor the oceanographic exploitation of SMOS and Aquarius maps new filtering schemes need to be devised. During the last years a new branch of image processing techniques applied to ocean observation has arisen with force, namely multiscale/multifractal analysis. Different scalars submitted to the action of the ocean flow develop an identical inner structure (multifractal structure) that can be revealed by means of the appropriate analysis tools (singularity analysis). These tools allow for instance to characterize surface currents from snapshots of different scalars (Turiel et al, Ocean Sciences, 2009). In this work we go further away, with the introduction of a new method to blend different types of scalar in a single map of improved quality. The method does not imply the introduction of any parameter, nor relies in any numerical model, but in the assumption that the action of the oceanic flow leads to the same multifractal structure in any ocean variable. The method allows, for instance, to use the multifractal structure coming from SST images to improve the quality of SSS maps (as illustrated in the figure). It can also

Towards SMOS: The 2006 National Airborne Field Experiment Plan

NASA Astrophysics Data System (ADS)

Walker, J. P.; Merlin, O.; Panciera, R.; Kalma, J. D.

2006-05-01

The 2006 National Airborne Field Experiment (NAFE) is the second in a series of two intensive experiments to be conducted in different parts of Australia. The NAFE'05 experiment was undertaken in the Goulburn River catchment during November 2005, with the objective to provide high resolution data for process level understanding of soil moisture retrieval, scaling and data assimilation. The NAFE'06 experiment will be undertaken in the Murrumbidgee catchment during November 2006, with the objective to provide data for SMOS (Soil Moisture and Ocean Salinity) level soil moisture retrieval, downscaling and data assimilation. To meet this objective, PLMR (Polarimetric L-band Multibeam Radiometer) and supporting instruments (TIR and NDVI) will be flown at an altitude of 10,000 ft AGL to provide 1km resolution passive microwave data (and 20m TIR) across a 50km x 50km area every 2-3 days. This will both simulate a SMOS pixel and provide the 1km soil moisture data required for downscale verification, allowing downscaling and near-surface soil moisture assimilation techniques to be tested with remote sensing data which is consistent with that from current (MODIS) and planned (SMOS) satellite sensors.. Additionally, two transects will be flown across the area to provide both 1km multi-angular passive microwave data for SMOS algorithm development, and on the same day, 50m resolution passive microwave data for algorithm verification. The study area contains a total of 13 soil moisture profile and rainfall monitoring sites for assimilation verification, and the transect fight lines are planned to go through 5 of these. Ground monitoring of surface soil moisture and vegetation for algorithm verification will be targeted at these 5 focus farms, with soil moisture measurements made at 250m spacing for 1km resolution flights and 50m spacing for 50m resolution flights. While this experiment has a particular emphasis on the remote sensing of soil moisture, it is open for collaboration

Validation of Salinity Data from the Soil Moisture and Ocean Salinity (SMOS) and Aquarius Satellites in the Agulhas Current System

NASA Astrophysics Data System (ADS)

Button, N.

2016-02-01

The Agulhas Current System is an important western boundary current, particularly due to its vital role in the transport of heat and salt from the Indian Ocean to the Atlantic Ocean, such as through Agulhas rings. Accurate measurements of salinity are necessary for assessing the role of the Agulhas Current System and these rings in the global climate system are necessary. With ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius/SAC-D satellites, we now have complete spatial and temporal (since 2009 and 2011, respectively) coverage of salinity data. To use this data to understand the role of the Agulhas Current System in the context of salinity within the global climate system, we must first understand validate the satellite data using in situ and model comparisons. In situ comparisons are important because of the accuracy, but they lack in the spatial and temporal coverage to validate the satellite data. For example, there are approximately 100 floats in the Agulhas Return Current. Therefore, model comparisons, such as the Hybrid Coordinate Ocean Model (HYCOM), are used along with the in situ data for the validation. For the validation, the satellite data, Argo float data, and HYCOM simulations were compared within box regions both inside and outside of the Agulhas Current. These boxed regions include the main Agulhas Current, Agulhas Return Current, Agulhas Retroflection, and Agulhas rings, as well as a low salinity and high salinity region outside of the current system. This analysis reveals the accuracy of the salinity measurements from the Aquarius/SAC-D and SMOS satellites within the Agulhas Current, which then provides accurate salinity data that can then be used to understand the role of the Agulhas Current System in the global climate system.

Evaluating Soil Moisture Retrievals from ESA's SMOS and NASA's SMAP Brightness Temperature Datasets

NASA Technical Reports Server (NTRS)

Al-Yaari, A.; Wigernon, J.-P.; Kerr, Y.; Rodriguez-Fernandez, N.; O'Neill, P. E.; Jackson, T. J.; De Lannoy, G. J. M.; Al Bitar, A.; Mialon, A.; Richaume, P.;

Evaluating soil moisture retrievals from ESA's SMOS and NASA's SMAP brightness temperature datasets.

PubMed

Al-Yaari, A; Wigneron, J-P; Kerr, Y; Rodriguez-Fernandez, N; O'Neill, P E; Jackson, T J; De Lannoy, G J M; Al Bitar, A; Mialon, A; Richaume, P; Walker, J P; Mahmoodi, A; Yueh, S

2017-05-01

Two satellites are currently monitoring surface soil moisture (SM) using L-band observations: SMOS (Soil Moisture and Ocean Salinity), a joint ESA (European Space Agency), CNES (Centre national d'études spatiales), and CDTI (the Spanish government agency with responsibility for space) satellite launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration (NASA) satellite successfully launched in January 2015. In this study, we used a multilinear regression approach to retrieve SM from SMAP data to create a global dataset of SM, which is consistent with SM data retrieved from SMOS. This was achieved by calibrating coefficients of the regression model using the CATDS (Centre Aval de Traitement des Données) SMOS Level 3 SM and the horizontally and vertically polarized brightness temperatures (TB) at 40° incidence angle, over the 2013 - 2014 period. Next, this model was applied to SMAP L3 TB data from Apr 2015 to Jul 2016. The retrieved SM from SMAP (referred to here as SMAP_Reg) was compared to: (i) the operational SMAP L3 SM (SMAP_SCA), retrieved using the baseline Single Channel retrieval Algorithm (SCA); and (ii) the operational SMOSL3 SM, derived from the multiangular inversion of the L-MEB model (L-MEB algorithm) (SMOSL3). This inter-comparison was made against in situ soil moisture measurements from more than 400 sites spread over the globe, which are used here as a reference soil moisture dataset. The in situ observations were obtained from the International Soil Moisture Network (ISMN; https://ismn.geo.tuwien.ac.at/) in North of America (PBO_H2O, SCAN, SNOTEL, iRON, and USCRN), in Australia (Oznet), Africa (DAHRA), and in Europe (REMEDHUS, SMOSMANIA, FMI, and RSMN). The agreement was analyzed in terms of four classical statistical criteria: Root Mean Squared Error (RMSE), Bias, Unbiased RMSE (UnbRMSE), and correlation coefficient (R). Results of the comparison of these various products with in situ

Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

NASA Astrophysics Data System (ADS)

Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

2016-10-01

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches

Different rates of soil drying after rainfall are observed by the SMOS satellite and the South Fork In Situ Soil Moisture Network

USDA-ARS?s Scientific Manuscript database

Soil moisture affects the spatial variation of land–atmosphere interactions through its in'uence on the balance of latent and sensible heat 'ux. Wetter soils are more prone to 'ooding because a smaller fraction of rainfall can in'ltrate into the soil. The Soil Moisture and Oceanic Salinity (SMOS) sa...

Validation of the SMOS-MIRAS Soil Moisture Product (SML2UDP) in the Pampean Region of Argentina

NASA Astrophysics Data System (ADS)

Niclòs, Raquel; Rivas, Raúl; Sánchez, Juan Manuel; García-Santos, Vicente; Doña, Carolina; Valor, Enric; Holzman, Mauro; Bayala, Martín Ignacio; Carmona, Facundo; Ocampo, Dora; Soldano, Alvaro; Thibeault, Marc

2014-05-01

A validation campaign was carried out to evaluate the SMOS-MIRAS Soil Moisture (SM) SML2UDP product (v5.51) in the Pampean Region of Argentina on February 2013. The study area was selected because it is a vast area of flatlands containing quite homogeneous rainfed croplands, with prevalence of soybean crops, considered SMOS nominal land uses (i.e., crops with vegetation heights not exceeding 1 to 2 m by opposition to trees). Transects of ground SM measurements were collected by Delta-T ThetaProbe ML2x SM probes within four ISEA-4H9 DGG SMOS nodes. The SM data obtained by each probe transect in each parcel were checked by collecting soil samples in the same parcels at the same time and measuring their masses. The gravimetric method was used to obtain reference values. An uncertainty of ± 0.03 m3m-3 was obtained for the ML2x probes. Additionally, they were calibrated in the laboratory for different SMs by saturating and drying a specific and representative variety of soil samples collected from the experimental parcels (loam, clay loam and silt loam samples). This calibration showed again accurate operations for the ML2x probes, which even attain uncertainties of ±0.01 m3m-3, in agreement with the manufacturer. The comparison of the SM transect data collected during the campaign with the SMOS-MIRAS SML2UDP product values showed a negative bias between concurrent SMOS data and ground SM measurements, which means a slight SMOS-MIRAS underestimation, and a standard deviation of ± 0.06 m3m-3. The validation sites were selected taking as reference the locations of permanent SM stations property of the Argentinean Comisión Nacional de Actividades Espaciales (CONAE, National Commission of Space Activities), Instituto Nacional de Tecnología Agropecuaria (INTA, National Institute of Farming Technology) and Instituto de Hidrología de Llanuras (IHLLA, Plain Hydrology Institute). During the campaign several transects were carried out in the parcels where permanent SM

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System.

PubMed

Zhao, Kaihui; Li, Peng; Zhang, Changfan; Li, Xiangfei; He, Jing; Lin, Yuliang

2017-12-06

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.

Usage of satellite data SMOS in order to characterize Sea Surface Salinity in the western Mediterranean

NASA Astrophysics Data System (ADS)

Brook, Anna; Robins, Lotem; Olmedo Casal, Estrella

2017-04-01

data source of SSS, on a global scale, has an important role for understanding oceanic process and climate change patterns. While the global goal is contributing for research and development, on a more local scale it is possible to observe that analyzation of the Mediterranean, that mainly being held in high spatial resolution is not represented well using SMOS products. The main reason is the low spatial resolution, of the satellite, but owing to its unique technology, different methods could be applied, to better represent smaller scaled research.

Modelling the Passive Microwave Signature from Land Surfaces: A Review of Recent Results and Application to the L-Band SMOS SMAP Soil Moisture Retrieval Algorithms

NASA Technical Reports Server (NTRS)

Wigneron, J.-P.; Jackson, T. J.; O'Neill, P.; De Lannoy, G.; De Rosnay, P.; Walker, J. P.; Ferrazzoli, P.; Mironov, V.; Bircher, S.; Grant, J. P.;

SMOS first results over land

NASA Astrophysics Data System (ADS)

Kerr, Yann; Waldteufel, Philippe; Cabot, François; Richaume, Philippe; Jacquette, Elsa; Bitar, Ahmad Al; Mamhoodi, Ali; Delwart, Steven; Wigneron, Jean-Pierre

2010-05-01

The Soil Moisture and Ocean Salinity (SMOS) mission is ESA's (European Space Agency ) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint programme between ESA CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-band 2D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere and hence the instrument probes the Earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. In order to prepare the data use and dissemination, the ground segment will produce level 1 and 2 data. Level 1 consists mainly of angular brightness temperatures while level 2 consists of geophysical products. In this context, a group of institutes prepared the soil moisture and ocean salinity Algorithm Theoretical Basis documents (ATBD) to be used to produce the operational algorithm. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. This is achieved by finding the best suited set of the parameters which drive the direct TB model, e.g. soil moisture (SM) and vegetation characteristics. Despite the simplicity of this principle, the main reason for the complexity of the algorithm is that SMOS "pixels" can correspond to rather large, inhomogeneous surface areas whose contribution to the radiometric signal is difficult to model. Moreover, the exact description of pixels, given by a weighting function which expresses the directional pattern of the SMOS interferometric radiometer, depends on the incidence angle. The goal is to

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System

PubMed Central

Li, Xiangfei; Lin, Yuliang

2017-01-01

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system. PMID:29211017

A new Downscaling Approach for SMAP, SMOS and ASCAT by predicting sub-grid Soil Moisture Variability based on Soil Texture

NASA Astrophysics Data System (ADS)

Montzka, C.; Rötzer, K.; Bogena, H. R.; Vereecken, H.

2017-12-01

Improving the coarse spatial resolution of global soil moisture products from SMOS, SMAP and ASCAT is currently an up-to-date topic. Soil texture heterogeneity is known to be one of the main sources of soil moisture spatial variability. A method has been developed that predicts the soil moisture standard deviation as a function of the mean soil moisture based on soil texture information. It is a closed-form expression using stochastic analysis of 1D unsaturated gravitational flow in an infinitely long vertical profile based on the Mualem-van Genuchten model and first-order Taylor expansions. With the recent development of high resolution maps of basic soil properties such as soil texture and bulk density, relevant information to estimate soil moisture variability within a satellite product grid cell is available. Here, we predict for each SMOS, SMAP and ASCAT grid cell the sub-grid soil moisture variability based on the SoilGrids1km data set. We provide a look-up table that indicates the soil moisture standard deviation for any given soil moisture mean. The resulting data set provides important information for downscaling coarse soil moisture observations of the SMOS, SMAP and ASCAT missions. Downscaling SMAP data by a field capacity proxy indicates adequate accuracy of the sub-grid soil moisture patterns.

Analyzing the 2010-2011 La Niña signature in the tropical Pacific sea surface salinity using in situ data, SMOS observations, and a numerical simulation

NASA Astrophysics Data System (ADS)

Hasson, Audrey; Delcroix, Thierry; Boutin, Jacqueline; Dussin, Raphael; Ballabrera-Poy, Joaquim

2014-06-01

The tropical Pacific Ocean remained in a La Niña phase from mid-2010 to mid-2012. In this study, the 2010-2011 near-surface salinity signature of ENSO (El Niño-Southern Oscillation) is described and analyzed using a combination of numerical model output, in situ data, and SMOS satellite salinity products. Comparisons of all salinity products show a good agreement between them, with a RMS error of 0.2-0.3 between the thermosalinograph (TSG) and SMOS data and between the TSG and model data. The last 6 months of 2010 are characterized by an unusually strong tripolar anomaly captured by the three salinity products in the western half of the tropical Pacific. A positive SSS anomaly sits north of 10°S (>0.5), a negative tilted anomaly lies between 10°S and 20°S and a positive one south of 20°S. In 2011, anomalies shift south and amplify up to 0.8, except for the one south of 20°S. Equatorial SSS changes are mainly the result of anomalous zonal advection, resulting in negative anomalies during El Niño (early 2010), and positive ones thereafter during La Niña. The mean seasonal and interannual poleward drift exports those anomalies toward the south in the southern hemisphere, resulting in the aforementioned tripolar anomaly. The vertical salinity flux at the bottom of the mixed layer tends to resist the surface salinity changes. The observed basin-scale La Niña SSS signal is then compared with the historical 1998-1999 La Niña event using both observations and modeling.

Evaluating soil moisture retrievals from ESA’s SMOS and NASA’s SMAP brightness temperature datasets

PubMed Central

Al-Yaari, A.; Wigneron, J.-P.; Kerr, Y.; Rodriguez-Fernandez, N.; O’Neill, P. E.; Jackson, T. J.; De Lannoy, G.J.M.; Al Bitar, A; Mialon, A.; Richaume, P.; Walker, JP; Mahmoodi, A.; Yueh, S.

2018-01-01

Two satellites are currently monitoring surface soil moisture (SM) using L-band observations: SMOS (Soil Moisture and Ocean Salinity), a joint ESA (European Space Agency), CNES (Centre national d’études spatiales), and CDTI (the Spanish government agency with responsibility for space) satellite launched on November 2, 2009 and SMAP (Soil Moisture Active Passive), a National Aeronautics and Space Administration (NASA) satellite successfully launched in January 2015. In this study, we used a multilinear regression approach to retrieve SM from SMAP data to create a global dataset of SM, which is consistent with SM data retrieved from SMOS. This was achieved by calibrating coefficients of the regression model using the CATDS (Centre Aval de Traitement des Données) SMOS Level 3 SM and the horizontally and vertically polarized brightness temperatures (TB) at 40° incidence angle, over the 2013 – 2014 period. Next, this model was applied to SMAP L3 TB data from Apr 2015 to Jul 2016. The retrieved SM from SMAP (referred to here as SMAP_Reg) was compared to: (i) the operational SMAP L3 SM (SMAP_SCA), retrieved using the baseline Single Channel retrieval Algorithm (SCA); and (ii) the operational SMOSL3 SM, derived from the multiangular inversion of the L-MEB model (L-MEB algorithm) (SMOSL3). This inter-comparison was made against in situ soil moisture measurements from more than 400 sites spread over the globe, which are used here as a reference soil moisture dataset. The in situ observations were obtained from the International Soil Moisture Network (ISMN; https://ismn.geo.tuwien.ac.at/) in North of America (PBO_H2O, SCAN, SNOTEL, iRON, and USCRN), in Australia (Oznet), Africa (DAHRA), and in Europe (REMEDHUS, SMOSMANIA, FMI, and RSMN). The agreement was analyzed in terms of four classical statistical criteria: Root Mean Squared Error (RMSE), Bias, Unbiased RMSE (UnbRMSE), and correlation coefficient (R). Results of the comparison of these various products with in

SMOS soil moisture validation with U.S. in situ newworks

USDA-ARS?s Scientific Manuscript database

Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors using a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. Since it is a new sensor u...

Comparison of remote sensing and in-situ soil moisture measurements: 6 years survey of SMOS data and agrometeorological stations in Eastern Poland

NASA Astrophysics Data System (ADS)

Szlazak, Radoslaw; Rojek, Edyta; Lukowski, Mateusz; Marczewski, Wojciech; Slominski, Jan; Sagan, Joanna; Gluba, Lukasz; Usowicz, Jerzy; Usowicz, Boguslaw

2017-04-01

Long term measurements of soil moisture on a large scale provide important information about not only periodical changes in water content, but also its contribute to better understanding of water cycle in environment. In addition, if in the studied area occurred extreme weather conditions or even anomalies, it is scientifically challenging to compare and validate data from two such different techniques like remote sensing and in-situ measurements. The aim of our research was to compare data of independent soil moisture measurements from SMOS (Soil Moisture and Ocean Salinity) satellite and 9 agrometeorological stations installed on Eastern Poland (Polesie and Podlasie regions). Those regions have similar climatic and topographic conditions, however, different vegetation covers and soil properties. Radiometric SMOS data contain surface water content values (approx. 45 km) for the area corresponding to the positions of chosen agrometeorological stations. For the purpose of those studies only morning satellite overpasses (ascending) were used. In-situ sensors in stations measure precisely soil moisture at 5-10 cm depth, but each only in one point. Both datasets were 7-days averaged in order to standardize. Analysis of a long term data is very interesting, especially because of occurrence of flood and drought events during the analyzed period of time. For example, the analyses revealed clear rainfall trend between ground and satellite data. Some shifts between SMOS and ground measurements were also observed, what may be explained by impact of different depths of SMOS measurements (<5 cm) and layer measured by sensors in the stations (0-10 cm). The influence of different sensing depths for both techniques is also reflected in bigger variability of SMOS data as they came from shallower layer of soil that have smaller "inertia" (in terms of soil moisture variability) than deeper in situ measurements. The results from SMOS and those obtained with the soil moisture sensor

DisPATCh as a tool to evaluate coarse-scale remotely sensed soil moisture using localized in situ measurements: Application to SMOS and AMSR-E data in Southeastern Australia

NASA Astrophysics Data System (ADS)

Malbéteau, Yoann; Merlin, Olivier; Molero, Beatriz; Rüdiger, Christoph; Bacon, Stephan

2016-03-01

Validating coarse-scale satellite soil moisture data still represents a big challenge, notably due to the large mismatch existing between the spatial resolution (> 10 km) of microwave radiometers and the representativeness scale (several m) of localized in situ measurements. This study aims to examine the potential of DisPATCh (Disaggregation based on Physical and Theoretical scale Change) for validating SMOS (Soil Moisture and Ocean Salinity) and AMSR-E (Advanced Microwave Scanning Radiometer-Earth observation system) level-3 soil moisture products. The ∽40-50 km resolution SMOS and AMSR-E data are disaggregated at 1 km resolution over the Murrumbidgee catchment in Southeastern Australia during a one year period in 2010-2011, and the satellite products are compared with the in situ measurements of 38 stations distributed within the study area. It is found that disaggregation improves the mean difference, correlation coefficient and slope of the linear regression between satellite and in situ data in 77%, 92% and 94% of cases, respectively. Nevertheless, the downscaling efficiency is lower in winter than during the hotter months when DisPATCh performance is optimal. Consistently, better results are obtained in the semi-arid than in a temperate zone of the catchment. In the semi-arid Yanco region, disaggregation in summer increases the correlation coefficient from 0.63 to 0.78 and from 0.42 to 0.71 for SMOS and AMSR-E in morning overpasses and from 0.37 to 0.63 and from 0.47 to 0.73 for SMOS and AMSR-E in afternoon overpasses, respectively. DisPATCh has strong potential in low vegetated semi-arid areas where it can be used as a tool to evaluate coarse-scale remotely sensed soil moisture by explicitly representing the sub-pixel variability.

Global assessment of Level 3 SMOS and Aquarius salinity measurements using Argo and an operational ocean model

NASA Astrophysics Data System (ADS)

Banks, Chris; Gommenginger, Christine; Srokosz, Meric; Snaith, Helen

2013-04-01

The launch of the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite in November 2009 marked a new era in satellite oceanography. SMOS was joined in orbit, in June 2011, by the NASA/Argentine Aquarius/SAC-D mission, specifically designed to measure sea surface salinity (SSS). These two satellites have significantly improved our ability to measure SSS synoptically. Despite significant differences in how the two satellites estimate SSS, both utilise passive systems to measure the response of the brightness temperature (Tb) at L-band (1.4 GHz) to SSS and initial results are encouraging. The UK National Oceanography Centre has produced 'Level 3' SSS data products for SMOS and Aquarius using monthly data on a 1° by 1° global grid, between 60°S and 60°N, from 1 September 2011 to 31 August 2012. Previous and on-going work shows for both satellites significant temporally varying differences between SSS from ascending passes (satellite moving south to north) and SSS from descending passes (satellite moving north to south). Therefore, for both SMOS and Aquarius, separate Level 3 products are produced from data for ascending and descending passes. For this study, two separate monthly validation datasets are used based on the same grid as the satellite data. The first is averaged near-surface salinity (depth less than 10 m) as derived from the drifting Argo float programme. The second validation data source is output from the UK Met Office Forecasting Ocean Assimilation Model (FOAM), which is based on NEMO (Nucleus for European Modelling of the Ocean). We calculate maps of the difference between all possible pairs of SSS data for each month, and consider their relationships using regression on the 1˚ values. The analysis is carried out for the global ocean, as well as for smaller, more homogeneous, study regions (e.g. SPURS in the subtropical North Atlantic).

Long-term ELBARA-II Assistance to SMOS Land Product and Algorithm Validation at the Valencia Anchor Station (MELBEX Experiment 2010-2013)

NASA Astrophysics Data System (ADS)

Lopez-Baeza, Ernesto; Wigneron, Jean-Pierre; Schwank, Mike; Miernecki, Maciej; Kerr, Yann; Casal, Tania; Delwart, Steven; Fernandez-Moran, Roberto; Mecklenburg, Susanne; Coll Pajaron, M. Amparo; Salgado Hernanz, Paula

The main activity of the Valencia Anchor Station (VAS) is currently now to support the validation of SMOS (Soil Moisture and Ocean Salinity) Level 2 and 3 land products (soil moisture, SM, and vegetation optical depth, TAU). With this aim, the European Space Agency (ESA) has provided the Climatology from Satellites Group of the University of Valencia with an ELBARA-II microwave radiometer under a loan agreement since September 2009. During this time, brightness temperatures (TB) have continuously been acquired, except during normal maintenance or minor repair interruptions. ELBARA-II is an L-band dual-polarization radiometer with two channels (1400-1418 MHz, 1409-1427 MHz). It is continuously measuring over a vineyard field (El Renegado, Caudete de las Fuentes, Valencia) from a 15 m platform with a constant protocol for calibration and angular scanning measurements with the aim to assisting the validation of SMOS land products and the calibration of the L-MEB (L-Band Emission of the Biosphere) -basis for the SMOS Level 2 Land Processor- over the VAS validation site. One of the advantages of using the VAS site is the possibility of studying two different environmental conditions along the year. While the vine cycle extends mainly between April and October, during the rest of the year the area remains under bare soil conditions, adequate for the calibration of the soil model. The measurement protocol currently running has shown to be robust during the whole operation time and will be extended in time as much as possible to continue providing a long-term data set of ELBARA-II TB measurements and retrieved SM and TAU. This data set is also showing to be useful in support of SMOS scientific activities: the VAS area and, specifically the ELBARA-II site, offer good conditions to control the long-term evolution of SMOS Level 2 and Level 3 land products and interpret eventual anomalies that may obscure sensor hidden biases. In addition, SM and TAU that are currently

Clarifications on the "Comparison Between SMOS, VUA, ASCAT, and ECMWF Soil Moisture Products Over Four Watersheds in U.S."

NASA Technical Reports Server (NTRS)

Wagner, Wolfgang; Luca, Brocca; Naeimi, Vahid; Reichle, Rolf; Draper, Clara; de Jeu, Richard; Ryu, Dongryeol; Su, Chun-Hsu; Western, Andrew; Calvet, Jean-Christophe;

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over Valencia Anchor Station by Using Downscaling Technique

NASA Astrophysics Data System (ADS)

Ansari Amoli, Abdolreza; Lopez-Baeza, Ernesto; Mahmoudi, Ali; Mahmoodi, Ali

2016-07-01

Synergistic Use of SMOS Measurements with SMAP Derived and In-situ Data over the Valencia Anchor Station by Using a Downscaling Technique Ansari Amoli, A.(1),Mahmoodi, A.(2) and Lopez-Baeza, E.(3) (1) Department of Earth Physics and Thermodynamics, University of Valencia, Spain (2) Centre d'Etudes Spatiales de la BIOsphère (CESBIO), France (3) Department of Earth Physics and Thermodynamics, University of Valencia, Spain Soil moisture products from active sensors are not operationally available. Passive remote sensors return more accurate estimates, but their resolution is much coarser. One solution to overcome this problem is the synergy between radar and radiometric data by using disaggregation (downscaling) techniques. Few studies have been conducted to merge high resolution radar and coarse resolution radiometer measurements in order to obtain an intermediate resolution product. In this paper we present an algorithm using combined available SMAP (Soil Moisture Active and Passive) radar and SMOS (Soil Moisture and Ocean Salinity) radiometer measurements to estimate surface soil moisture over the Valencia Anchor Station (VAS), Valencia, Spain. The goal is to combine the respective attributes of the radar and radiometer observations to estimate soil moisture at a resolution of 3 km. The algorithm disaggregates the coarse resolution SMOS (15 km) radiometer brightness temperature product based on the spatial variation of the high resolution SMAP (3 km) radar backscatter. The disaggregation of the radiometer brightness temperature uses the radar backscatter spatial patterns within the radiometer footprint that are inferred from the radar measurements. For this reason the radar measurements within the radiometer footprint are scaled by parameters that are derived from the temporal fluctuations in the radar and radiometer measurements.

SMOS disaggregated soil moisture product at 1 km resolution: processor overview and first validation results

USDA-ARS?s Scientific Manuscript database

The SMOS (Soil Moisture and Ocean Salinity) mission provides surface soil moisture (SM) maps at a mean resolution of ~50 km. However, agricultural applications (irrigation, crop monitoring) and some hydrological applications (floods and modeling of small basins) require higher resolution SM...

SMOS Instrument Performance and Calibration after 3 Years in Orbit

NASA Astrophysics Data System (ADS)

Martin-Neira, Manuel; Corbella, Ignasi; Torres, Francesc; Kainulainen, Juha; Oliva, Roger; Closa, Josep; Cabot, François; Castro, Rita; Barbosa, Jose; Gutierrez, Antonio; Anterrieu, Eric; Tenerelli, Joe; Martin-Porqueras, Fernando; Buenadicha, Guillermo; Delwart, Steven; Crapolicchio, Raffaele; Suess, Martin

2013-04-01

ESA's Soil Moisture and Ocean Salinity (SMOS) mission has been in orbit for already over 3 years which has allowed the calibration and data processing team consolidating both the calibration strategy and the Level-1 processor which transforms the raw visibility samples into polarimetric brightness temperature images. The payload on board SMOS, MIRAS, is quite unique in that it is the first microwave radiometer in space ever capable to generate wide field of view images at every snapshot measurement. This means that most of the calibration as well as image processing techniques are being developed for the first time with little heritage from any previous space mission. Issues intrinsically attached to its wide field of view such as spatial ripples across the snapshot images are particular to MIRAS and to no other earlier radiometer. Even the fundamental theory behind the instrument was put at test, first on ground inside an electromagnetic compatibility chamber, and now in orbit when imaging the Cosmic Microwave Background Radiation of the cold sky. A groundbreaking effort is being carried out by the SMOS project team to understand and master all calibration and image reconstruction issues of this novel microwave interferometer payload. MIRAS in-orbit performance is driven by the amplitude of spatial ripples across the image and orbital and seasonal radiometer stability. Spatial ripples are unique to interferometric radiometers and are produced by (a) a limited knowledge of the antenna patterns and, in general, of the model of the instrument, (b) some fundamental limitations related to the inverse problem of image reconstruction in undetermined conditions and (c) subtle data processing inconsistencies which are discovered and corrected. To reduce the spatial ripples sea surface salinity retrievals are performed by first removing the brightness temperature spatial errors using a uniform region of the Pacific Ocean. However soil moisture retrievals cannot benefit of

Global Soil Moisture Estimation from L-Band Satellite Data: The Impact of Radiative Transfer Modeling in Assimilation and Retrieval Systems

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle; Reichle, Rolf; Gruber, Alexander; Bechtold, Michel; Quets, Jan; Vrugt, Jasper; Wigneron, Jean-Pierre

2018-01-01

The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model.

Rainfall estimation by inverting SMOS soil moisture estimates: a comparison of different methods over Australia

USDA-ARS?s Scientific Manuscript database

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) is used...

Evaluation and qualification of commercial opto-electronic components for the MOHA subsystem in ESA's SMOS mission

NASA Astrophysics Data System (ADS)

Gutierrez, Francisco; Cordero, Enrique; Sánchez, Carolina; Barbero, Juan; Mosberger, Martin; Boehle, Peter; Tornell, Manuel; Lundmark, Karin

2017-11-01

A dedicated evaluation and qualification campaign has been performed on several optical COTS components in order to use them on ESA's SMOS mission. The evaluation phase consisted of a set of critical tests and analyses and led to the selection of the flight lot component. After selection of the components, one lot of each component has been qualified for the SMOS mission. The overall approach is presented together with a summary of all activities performed. The whole task has been handled in a joint effort between ESA, EADS CASA Espacio (prime contractor), Contraves Space AG (MOHA subsystem), TECNOLOGICA SA (component qualification experts) and the respective manufacturers, each party providing their specific know-how. Test results are presented and the issues discovered and lessons learned are addressed. Special emphasis is given to particular tests for which dedicated setups had to be designed due to the unavailability of standard equipment.

Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation

USDA-ARS?s Scientific Manuscript database

The Soil Moisture and Ocean Salinity satellite (SMOS) was launched in November 2009 and started delivering data in January 2010. The commissioning phase ended in May 2010. Subsequently, the satellite has been in operation for over 5 years while the retrieval algorithms from Level 1 to Level 2 underw...

Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

NASA Technical Reports Server (NTRS)

Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

2014-01-01

Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

Advances in Assimilation of Satellite-Based Passive Microwave Observations for Soil-Moisture Estimation

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Pauwels, Valentijn; Reichle, Rolf H.; Draper, Clara; Koster, Randy; Liu, Qing

2012-01-01

Satellite-based microwave measurements have long shown potential to provide global information about soil moisture. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS, [1]) mission as well as the future National Aeronautics and Space Administration (NASA) Soil Moisture Active and Passive (SMAP, [2]) mission measure passive microwave emission at L-band frequencies, at a relatively coarse (40 km) spatial resolution. In addition, SMAP will measure active microwave signals at a higher spatial resolution (3 km). These new L-band missions have a greater sensing depth (of -5cm) compared with past and present C- and X-band microwave sensors. ESA currently also disseminates retrievals of SMOS surface soil moisture that are derived from SMOS brightness temperature observations and ancillary data. In this research, we address two major challenges with the assimilation of recent/future satellite-based microwave measurements: (i) assimilation of soil moisture retrievals versus brightness temperatures for surface and root-zone soil moisture estimation and (ii) scale-mismatches between satellite observations, models and in situ validation data.

Validation of SURFEX Simulated Soil Moisture over the Valencia Anchor Station using SMOS products and in situ measurements.

NASA Astrophysics Data System (ADS)

Coll, M. Amparo; Khodayar, Samiro; Lopez-Baeza, Ernesto

2014-05-01

Soil moisture is an important variable in agriculture, hydrology, meteorology and related disciplines. Despite its importance, it is complicated to obtain an appropriate representation of this variable, mainly because of its high temporal and spatial variability. SVAT (Soil-Vegetation-Atmosphere-Transfer) models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area. In this work, we use the SURFEX (Surface Externalisée) model developed at the Centre National de Recherches Météorologiques (CNRM) at Météo-France (http://www.cnrm.meteo.fr/surfex/) to simulate soil moisture at the Valencia Anchor Station. SURFEX integrates the ISBA (Interaction Sol-Biosphère-Atmosphère; surfaces with vegetation) module to describe the land surfaces (http://www.cnrm.meteo.fr/isbadoc/model.html) and we introduced the ECOCLIMAP for the description of land covers. The Valencia Anchor Station was chosen as a validation site for the SMOS (Soil Moisture and Ocean Salinity) mission and as one of the hydrometeorological sites for the HyMeX (HYdrological cycle in Mediterranean EXperiment) programme. This site represents a reasonably homogeneous and mostly flat area of about 50x50 km2. The main cover type is vineyards (65%), followed by fruit trees, shrubs, and pine forests, and a few number of small industrial and urban areas. Except for the vineyard growing season, the area remains mostly under bare soil conditions. In spite of its relatively flat topography, the small altitude variations of the region clearly influence climate. This oscillates between semiarid and dry-sub-humid. Annual mean temperatures are between 12 ºC and 14.5 ºC, and annual precipitation is about 400-450 mm. The duration of frost free periods is from May to November, with maximum precipitation in spring and autumn. The first part of this investigation consists in simulating soil moisture fields to be compared with level-2 and level-3 soil moisture maps generated

MIRAS characterization and monitoring during the SMOS In-Orbit Commissioning Phase

NASA Astrophysics Data System (ADS)

Corbella, I.; Torres, F.; Martin-Neira, M.; Duffo, N.; González-Gambau, V.; Camps, A.; Vall-Llossera, M.

2009-04-01

for the in-orbit commissioning phase. The tool can ingest raw data from the electronic ground support equipment (EGSE) developed by the instrument manufacturer and also from the nominal level 0 data provided by the SMOS ground segment data acquisition system. The software classifies the input data and applies the calibration procedures to produce calibrated visibility and brightness temperature. Most of the intermediate results, including raw data and calibration parameters, are saved in files for further analysis and processing. The processing has been optimized for speed so that the results are produced in near real time and it is designed to process large amount of data in a continuous way. Finally, the tool includes a user-friendly graphics interface that allows selecting specific data according to different parameters (baselines or receivers, modes of operation or others). 4 Conclusions During the SMOS In-Orbit Commissioning Phase, a number of tests will be carried out in order to check the payload MIRAS operation and fully characterize it in terms of data consistency and calibration parameters. The UPC team is in charge of analyzing the data and develop the procedures to verify that the final data meets the required specifications. The procedures for this have been summarized and will be presented at the conference in more detail. References [1] Michael Brown, "SMOS in-orbit commissioning phase plan," Tech. Rep. SO-PL-ESA-SYS-5505, issue 1.1, ESA-ESTEC, The Netherlands, 8 August 2008. [2] Ignasi Corbella, Francesc Torres, Nuria Duffo, Manuel Martín-Neira, Verónica González, Adriano Camps, and Mercè Vall-llossera, "MIRAS ground characterization," in 10th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment - Rad 2008, Florence, Italy, 11-14 March 2008, Istituto di Fisica Applicata "N.Carrara" (IFAC-CNR), pp. 1-4. [3] Manuel Martín-Neira, Martin Suess, and Juha Kainulainen, "The flat target transformation," IEEE Transactions on

The global SMOS Level 3 daily soil moisture and brightness temperature maps

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Mialon, Arnaud; Kerr, Yann H.; Cabot, François; Richaume, Philippe; Jacquette, Elsa; Quesney, Arnaud; Mahmoodi, Ali; Tarot, Stéphane; Parrens, Marie; Al-Yaari, Amen; Pellarin, Thierry; Rodriguez-Fernandez, Nemesio; Wigneron, Jean-Pierre

2017-06-01

The objective of this paper is to present the multi-orbit (MO) surface soil moisture (SM) and angle-binned brightness temperature (TB) products for the SMOS (Soil Moisture and Ocean Salinity) mission based on a new multi-orbit algorithm. The Level 3 algorithm at CATDS (Centre Aval de Traitement des Données SMOS) makes use of MO retrieval to enhance the robustness and quality of SM retrievals. The motivation of the approach is to make use of the longer temporal autocorrelation length of the vegetation optical depth (VOD) compared to the corresponding SM autocorrelation in order to enhance the retrievals when an acquisition occurs at the border of the swath. The retrieval algorithm is implemented in a unique operational processor delivering multiple parameters (e.g. SM and VOD) using multi-angular dual-polarisation TB from MO. A subsidiary angle-binned TB product is provided. In this study the Level 3 TB V310 product is showcased and compared to SMAP (Soil Moisture Active Passive) TB. The Level 3 SM V300 product is compared to the single-orbit (SO) retrievals from the Level 2 SM processor from ESA with aligned configuration. The advantages and drawbacks of the Level 3 SM product (L3SM) are discussed. The comparison is done on a global scale between the two datasets and on the local scale with respect to in situ data from AMMA-CATCH and USDA ARS Watershed networks. The results obtained from the global analysis show that the MO implementation enhances the number of retrievals: up to 9 % over certain areas. The comparison with the in situ data shows that the increase in the number of retrievals does not come with a decrease in quality, but rather at the expense of an increased time lag in product availability from 6 h to 3.5 days, which can be a limiting factor for applications like flood forecast but reasonable for drought monitoring and climate change studies. The SMOS L3 soil moisture and L3 brightness temperature products are delivered using an open licence and

Evolution of the 2011 Mississippi River Peak Flood Plume from Coincident Satellite and Airborne L-band Radiometer Surface Salinity Observations.

NASA Astrophysics Data System (ADS)

Burrage, D. M.; Wesson, J. C.; Hwang, P. A.; Wang, D. W.; Wijesekera, H. W.

2016-02-01

Airborne mapping of Sea Surface Salinity (SSS) with L-band radiometers has been practiced for 20 yrs., while global satellite observations began with the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) Satellite launch in 2009. Airborne data with high ( 1km) resolution, but limited coverage, complement the lower resolution ( 35 km at nadir) but global coverage and 3-5 day revisit of SMOS. The record June, 2011 Mississippi R. peak flood, with flows exceeding 42,500 m^3/s, required diversions into Lake Pontchartrain and the Atchafalaya R. to avoid flooding New Orleans and Baton Rouge. The resulting merged outflows formed a single freshwater plume that spanned the Mississippi, Louisiana and Texas `Gulf Coast', and reached up to 300 km across the shelf. SSS was mapped by the NRL airborne Salinity Temperature and Roughness Remote Scanner (STARRS) and SMOS radiometers during a two week (2-13 June 2011) campaign immediately following the flood crest. STARRS obtained oblique across-shelf transects spanning the Northern Gulf of Mexico, under-flying SMOS, and shorter zig-zag coastal transects. SSS samples from a ship near the shelf edge agreed well with STARRS and SMOS after applying standard geophysical correction models and roughness corrections from an SSA/SPM E-M model and an advanced wave spectrum. The minimum SMOS footprint size (35 km at nadir), produced a coastal data gap filled by STARRS transects that reached the coast. The 200 km overlap between the two sensors along coincident ground tracks agreed closely near the frontal boundary, with salinity contrasts of 7-15 psu over a 10 km span at the plume edge evident in both data sets. Successive SMOS Level 2 (L2) SSS data swaths obtained at 2-5 day intervals showed the evolution of the plume in three well-separated seaward extensions located near the Mississippi Delta, and well east and west of the Delta. The dispersal of the plume was also detected by SMOS following the airborne campaign.

The NASA Soil Moisture Active Passive (SMAP) Mission - Algorithm and Cal/Val Activities and Synergies with SMOS and Other L-Band Missions

NASA Technical Reports Server (NTRS)

Njoku, Eni; Entekhabi, Dara; O'Neill, Peggy; Jackson, Tom; Kellogg, Kent; Entin, Jared

2011-01-01

applicable to soil moisture measurement, such as Aquarius, SAO COM, and ALOS-2. The algorithms and data products for SMAP are being developed in the SMAP Science Data System (SDS) Testbed. The algorithms are developed and evaluated in the SDS Testbed using simulated SMAP observations as well as observational data from current airborne and spaceborne L-band sensors including SMOS. The SMAP project is developing a Calibration and Validation (Cal/Val) Plan that is designed to support algorithm development (pre-launch) and data product validation (post-launch). A key component of the Cal/Val Plan is the identification, characterization, and instrumentation of sites that can be used to calibrate and validate the sensor data (Level I) and derived geophysical products (Level 2 and higher). In this presentation we report on the development status of the SMAP data product algorithms, and the planning and implementation of the SMAP Cal/Val program. Several components of the SMAP algorithm development and Cal/Val plans have commonality with those of SMOS, and for this reason there are shared activities and resources that can be utilized between the missions, including in situ networks, ancillary data sets, and long-term monitoring sites.

Comparison of SMOS and SMAP Soil Moisture Retrieval Approaches Using Tower-based Radiometer Data over a Vineyard Field

NASA Technical Reports Server (NTRS)

Miernecki, Maciej; Wigneron, Jean-Pierre; Lopez-Baeza, Ernesto; Kerr, Yann; DeJeu, Richard; DeLannoy, Gabielle J. M.; Jackson, Tom J.; O'Neill, Peggy E.; Shwank, Mike; Moran, Roberto Fernandez;

ESA's Soil Moisture dnd Ocean Salinity Mission - Contributing to Water Resource Management

NASA Astrophysics Data System (ADS)

Mecklenburg, S.; Kerr, Y. H.

2015-12-01

The Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables used in predictive hydrological, oceanographic and atmospheric models. SMOS observations also provide information on the characterisation of ice and snow covered surfaces and the sea ice effect on ocean-atmosphere heat fluxes and dynamics, which affects large-scale processes of the Earth's climate system. The focus of this paper will be on SMOS's contribution to support water resource management: SMOS surface soil moisture provides the input to derive root-zone soil moisture, which in turn provides the input for the drought index, an important monitoring prediction tool for plant available water. In addition to surface soil moisture, SMOS also provides observations on vegetation optical depth. Both parameters aid agricultural applications such as crop growth, yield forecasting and drought monitoring, and provide input for carbon and land surface modelling. SMOS data products are used in data assimilation and forecasting systems. Over land, assimilating SMOS derived information has shown to have a positive impact on applications such as NWP, stream flow forecasting and the analysis of net ecosystem exchange. Over ocean, both sea surface salinity and severe wind speed have the potential to increase the predictive skill on the seasonal and short- to medium-range forecast range. Operational users in particular in Numerical Weather Prediction and operational hydrology have put forward a requirement for soil moisture data to be available in near-real time (NRT). This has been addressed by developing a fast retrieval for a NRT level 2 soil moisture product based on Neural Networks, which will be available by autumn 2015. This paper will focus on presenting the

Analysis of L-band radiometric data over the Mediterranean Sea from the SMOS Validation Rehearsal campaign

NASA Astrophysics Data System (ADS)

Gabarro, C.; Talone, M.; Font, J.

2009-04-01

L-band radiometric data obtained with a real aperture airborne radiometer during SMOS validation Rehearsal campaign (April-May 2008) over the NW Mediterranean Sea have been analysed. EMIRAD, a fully polarimetric radiometer developed by the Technical University of Denmark operating in the 1400 - 1427 MHz band, was mounted on board a Skyvan aircraft from the Helsinki University of Technology. Two antennas were used: one facing nadir with 37.6° full aperture at half-power; and one placed towards the rear of the aircraft at 40° zenith angle with 30.6° full aperture at half-power. Two transit flights over the sea from Marseille to Valencia (19 April 2008) and from Valencia to Marseille (3 May 2008) have been studied. Two meteorological and oceanographic buoys were moored 40 Km offshore in front of Tarragona and were overflown during these transits. Additionally, information on sea surface temperature (SST) and sea surface salinity (SSS) was obtained from operational model outputs (Mediterranean Forecasting System - Mediterranean Operational Oceanography Network) and wind speed from QuikSCAT. Measured brightness temperatures (Tb) have been compared with modelled Tb, using a semi-empirical emissivity model: Klein and Swift model is used to define the dielectric constant and Hollinger model for the rough sea emissivity contribution. Comparisons show that in general measured Tb variability fits with modelled variability, although a bias is observed in the aft V channel.

Modelling the passive microwave signature from land surfaces: a review of recent results and application to the SMOS & SMAP soil moisture retrieval algorithms

USDA-ARS?s Scientific Manuscript database

Two passive microwave missions are currently operating at L-band to monitor surface soil moisture (SM) over continental surfaces. The SMOS sensor, based on an innovative interferometric technology enabling multi-angular signatures of surfaces to be measured, was launched in November 2009....

SURFEX modeling of soil moisture fields over the Valencia Anchor Station and their comparison to different SMOS products and in situ measurements

NASA Astrophysics Data System (ADS)

Coll Pajaron, M. Amparo; Lopez-Baeza, Ernesto; Fernandez-Moran, Roberto; Samiro Khodayar-Pardo, D.

2016-07-01

Soil moisture is a difficult variable to obtain proper representation because of its high temporal and spatial variability. It is a significant parameter in agriculture, hydrology, meteorology and related disciplines. {it SVAT (Soil-Vegetation-Atmosphere-Transfer)} models can be used to simulate the temporal behaviour and spatial distribution of soil moisture in a given area. In this work, we use the {bf SURFEX (Surface Externalisée)} model developed at the {it Centre National de Recherches Météorologiques (CNRM)} at Météo-France (http://www.cnrm.meteo.fr/surfex/) to simulate soil moisture at the {bf Valencia Anchor Station}. SURFEX integrates the {bf ISBA (Interaction Sol-Biosphère-Atmosphère}; surfaces with vegetation) module to describe the land surfaces (http://www.cnrm.meteo.fr/isbadoc/model.html) that have been adapted to describe the land covers of our study area. The Valencia Anchor Station was chosen as a core validation site for the {it SMOS (Soil Moisture and Ocean Salinity)} mission and as one of the hydrometeorological sites for the {it HyMeX (HYdrological cycle in Mediterranean EXperiment)} programme. This site represents a reasonably homogeneous and mostly flat area of about 50x50 km2. The main cover type is vineyards (65%), followed by fruit trees, shrubs, and pine forests, and a few small scattered industrial and urban areas. Except for the vineyard growing season, the area remains mostly under bare soil conditions. In spite of its relatively flat topography, the small altitude variations of the region clearly influence climate. This oscillates between semiarid and dry sub-humid. Annual mean temperatures are between 12 ºC and 14.5 ºC, and annual precipitation is about 400-450 mm. The duration of frost free periods is from May to November, with maximum precipitation in spring and autumn. The first part of this investigation consists in simulating soil moisture fields over the Valencia Anchor Station to be compared with SMOS level-2

Summary of Meteorological Observations, Surface (SMOS), Kingsville, Texas.

DTIC Science & Technology

1984-09-01

of surface C weather observation. The six parts are: Part A - Wather Conditions/ Atmospheric Phenn. Part S1 - Preci pitatien/Spofal 1/Snow, Depth... WATHER SERVICE SU2VACl WINDS AMMOIC MMD86AW MPW OFU ~AHOY hUam~W _______________ 41±low kI&K GO!PtO I2 Ci I~. I~JT2. C,. 2.& . W 1. -S . S 64~ E - S

Summary of Meteorological Observations, Surface (SMOS), Barbers Point, Hawaii.

DTIC Science & Technology

1984-09-01

available. Also provided are the means and standard deviations for each month and annual (all months). The extremes for a month are not printed nor...January 1964. When 90 or more of the daily observations of peak gust wind data are available for a month, the extreme is selected and printed . These...ASHEVILLE, NC PERCENTAGE FREQUENCY OF WIND DIRECTION AND SPEED (FROM HOURLY OBSERVATIONS) STATUSI STATIM usA. V U0*t5 CLA mi6 (O t ST PE ND MEAN (KNTS) 1

Assimilation of neural network soil moisture in land surface models

NASA Astrophysics Data System (ADS)

Rodriguez-Fernandez, Nemesio; de Rosnay, Patricia; Albergel, Clement; Aires, Filipe; Prigent, Catherine; Kerr, Yann; Richaume, Philippe; Muñoz-Sabater, Joaquin; Drusch, Matthias

2017-04-01

In this study a set of land surface data assimilation (DA) experiments making use of satellite derived soil moisture (SM) are presented. These experiments have two objectives: (1) to test the information content of satellite remote sensing of soil moisture for numerical weather prediction (NWP) models, and (2) to test a simplified assimilation of these data through the use of a Neural Network (NN) retrieval. Advanced Scatterometer (ASCAT) and Soil Moisture and Ocean Salinity (SMOS) data were used. The SMOS soil moisture dataset was obtained specifically for this project training a NN using SMOS brightness temperatures as input and using as reference for the training European Centre for Medium-Range Weather Forecasts (ECMWF) H-TESSEL SM fields. In this way, the SMOS NN SM dataset has a similar climatology to that of the model and it does not present a global bias with respect to the model. The DA experiments are computed using a surface-only Land Data Assimilation System (so-LDAS) based on the HTESSEL land surface model. This system is very computationally efficient and allows to perform long surface assimilation experiments (one whole year, 2012). SMOS NN SM DA experiments are compared to ASCAT SM DA experiments. In both cases, experiments with and without 2 m air temperature and relative humidity DA are discussed using different observation errors for the ASCAT and SMOS datasets. Seasonal, geographical and soil-depth-related differences between the results of those experiments are presented and discussed. The different SM analysed fields are evaluated against a large number of in situ measurements of SM. On average, the SM analysis gives in general similar results to the model open loop with no assimilation even if significant differences can be seen for specific sites with in situ measurements. The sensitivity to observation errors to the SM dataset slightly differs depending on the networks of in situ measurements, however it is relatively low for the tests

SMOS: a satellite mission to measure ocean surface salinity

NASA Astrophysics Data System (ADS)

Font, Jordi; Kerr, Yann H.; Srokosz, Meric A.; Etcheto, Jacqueline; Lagerloef, Gary S.; Camps, Adriano; Waldteufel, Philippe

2001-01-01

The ESA's SMOS (Soil Moisture and Ocean Salinity) Earth Explorer Opportunity Mission will be launched by 2005. Its baseline payload is a microwave L-band (21 cm, 1.4 GHz) 2D interferometric radiometer, Y shaped, with three arms 4.5 m long. This frequency allows the measurement of brightness temperature (Tb) under the best conditions to retrieve soil moisture and sea surface salinity (SSS). Unlike other oceanographic variables, until now it has not been possible to measure salinity from space. However, large ocean areas lack significant salinity measurements. The 2D interferometer will measure Tb at large and different incidence angles, for two polarizations. It is possible to obtain SSS from L-band passive microwave measurements if the other factors influencing Tb (SST, surface roughness, foam, sun glint, rain, ionospheric effects and galactic/cosmic background radiation) can be accounted for. Since the radiometric sensitivity is low, SSS cannot be recovered to the required accuracy from a single measurement as the error is about 1-2 psu. If the errors contributing to the uncertainty in Tb are random, averaging the independent data and views along the track, and considering a 200 km square, allow the error to be reduced to 0.1-0.2 pus, assuming all ancillary errors are budgeted.

Towards an estimation of water masses formation areas from SMOS-based TS diagrams

NASA Astrophysics Data System (ADS)

Klockmann, Marlene; Sabia, Roberto; Fernandez-Prieto, Diego; Donlon, Craig; Font, Jordi

2014-05-01

Temperature-Salinity (TS) diagrams emphasize the mutual variability of ocean temperature and salinity values, relating them to the corresponding density. Canonically used in oceanography, they provide a means to characterize and trace ocean water masses. In [1], a first attempt to estimate surface-layer TS diagrams based on satellite measurements has been performed, profiting from the recent availability of spaceborne salinity data. In fact, the Soil Moisture and Ocean Salinity (SMOS, [2]) and the Aquarius/SAC-D [3] satellite missions allow to study the dynamical patterns of Sea Surface Salinity (SSS) for the first time on a global scale. In [4], given SMOS and Aquarius salinity estimates, and by also using Sea Surface Temperature (SST) from the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA, [5]) effort, experimental satellite-based TS diagrams have been routinely derived for the year 2011. They have been compared with those computed from ARGO-buoys interpolated fields, referring to a customised partition of the global ocean into seven regions, according to the water masses classification of [6]. In [7], moreover, besides using TS diagrams as a diagnostic tool to evaluate the temporal variation of SST and SSS (and their corresponding density) as estimated by satellite measurements, the emphasis was on the interpretation of the geographical deviations with respect to the ARGO baseline (aiming at distinguishing between the SSS retrieval errors and the additional information contained in the satellite data with respect to ARGO). In order to relate these mismatches to identifiable oceanographic structures and processes, additional satellite datasets of ocean currents, evaporation/precipitation fluxes, and wind speed have been super-imposed. Currently, the main focus of the study deals with the exploitation of these TS diagrams as a prognostic tool to derive water masses formation areas. Firstly, following the approach described in [8], the surface

Summary of Meteorological Observations, Surface (SMOS) Memphis, Tennessee.

DTIC Science & Technology

1984-08-01

and annual (all months). The extremes for a month are not printed nor used in computations if one or more observations are missing. NOTE: Snow depth...16 ,, r . 20 ." l., _ 20 :.20 ID PE _ __ 21 .4 11’ 3____- 21 .5 . ___ 22 𔄁~ us 1-,’____ 22 3.t o 1 7p 191 ?___ 23 Z’ 42’ 9lQ 23 2 1 P _ __ 24 . 12...is selected and printed . These values are then used to compute means and standard deviations for the entire period. Every month of a year must have

Summary of Meteorological Observations, Surface (SMOS), El Toro, California

DTIC Science & Technology

1983-10-01

SURFACE WINDS DETACHMENT ASHEVILLE. NC PERCENTAGE FREQUENCY OF WIND DIRECTION AND SPEED (FROM HOURLY OBSERVATIONS) EL TIPO , CALIrQO𔃾IA 73-’.? A ir, U~~tiAL...OF WiND DIRECTION AND SPEED (FROM HOURLY OBSERVATIONS) ... 112L. E L TIPO , ALIODkI1A 71-q2 r ALL wEANCP _______ MEAN 11-11 6.S 7.A 1.U 11.W6 17.21 n...nTa IO STyVIO. *..M YUOnb0U T-mp. WIT BULl TEMPERATUIE DEPRESSION fF) TOTAL TOTAL 0 1- 2 3 -4 - j 8 9 10 11-12113 14,11516117. 18119 270:i21 . 2 23

Global retrieval of soil moisture and vegetation properties using data-driven methods

NASA Astrophysics Data System (ADS)

Rodriguez-Fernandez, Nemesio; Richaume, Philippe; Kerr, Yann

2017-04-01

Data-driven methods such as neural networks (NNs) are a powerful tool to retrieve soil moisture from multi-wavelength remote sensing observations at global scale. In this presentation we will review a number of recent results regarding the retrieval of soil moisture with the Soil Moisture and Ocean Salinity (SMOS) satellite, either using SMOS brightness temperatures as input data for the retrieval or using SMOS soil moisture retrievals as reference dataset for the training. The presentation will discuss several possibilities for both the input datasets and the datasets to be used as reference for the supervised learning phase. Regarding the input datasets, it will be shown that NNs take advantage of the synergy of SMOS data and data from other sensors such as the Advanced Scatterometer (ASCAT, active microwaves) and MODIS (visible and infra red). NNs have also been successfully used to construct long time series of soil moisture from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and SMOS. A NN with input data from ASMR-E observations and SMOS soil moisture as reference for the training was used to construct a dataset sharing a similar climatology and without a significant bias with respect to SMOS soil moisture. Regarding the reference data to train the data-driven retrievals, we will show different possibilities depending on the application. Using actual in situ measurements is challenging at global scale due to the scarce distribution of sensors. In contrast, in situ measurements have been successfully used to retrieve SM at continental scale in North America, where the density of in situ measurement stations is high. Using global land surface models to train the NN constitute an interesting alternative to implement new remote sensing surface datasets. In addition, these datasets can be used to perform data assimilation into the model used as reference for the training. This approach has recently been tested at the European Centre

Summary of Meteorological Observations, Surface (SMOS), Quantico, Virginia.

DTIC Science & Technology

1984-08-01

DETACHMENT ASHEVILLE, NC PERCENTAGE FREQUENCY OF WIND DIRECTION AND SPEED (FROM HOURLY OBSERVATIONS) STATION STAIN S OE5583O" LL ~’"ALLL CLAN OWN8 I L.S...8217v ’j 6 7 !~o .1 P1. "? 7* 2 P3 72 &.I t, 71 a ?!t .V . 70 71.3 ?%3 . 3 . : I > 3300 Z. 7 *’..1 OJS. ;- OF A191 *9 8*1 6*.3 14 p. 1~. 92. 92. 1’. 09...QUNIn VA ~9-77 NOV WarmU STAiNS uSE PRO" mom C PERCENTAGE FREQUENCY OF OCCURRENCE (FROM HOURLY OUSERVATIONS) "T(L.) 0 a 2 3 4 s 6 y 1s uccv to SK s. 9

An overview of new insights from satellite salinity missions on oceanography

NASA Astrophysics Data System (ADS)

Reul, Nicolas

2015-04-01

The Soil Moisture and Ocean Salinity (SMOS) mission, launched on 2 November 2009, is the European Space Agency's (ESA) second Earth Explorer Opportunity mission. The scientific objectives of the SMOS mission directly respond to the need for global observations of soil moisture and ocean salinity, two key variables describing the Earth's water cycle and having been identified as Essential Climate Variables (ECVs) by the Global Climate Observing System (GCOS). After five years of satellite Sea Surface Salinity (SSS) monitoring from SMOS data, we will present an overview of the scientific highlights these data have brougtht to the oceanographic communities. In particular, we shall review the impact of SMOS SSS and brightness tempeaerture data for the monitoring of: -Mesoscale variability of SSS (and density) in frontal structures, eddies, -Ocean propagative SSS signals (e.g. TIW, planetary waves), -Freshwater flux Monitoring (Evaportaion minus precipitation, river run off), -Large scale SSS anomalies related to climate fluctuations (e.g. ENSO, IOD), -Air-Sea interactions (equatorial upwellings, Tropical cyclone wakes) -Temperature-Salinity dependencies, -Sea Ice thickness, -Tropical Storm and high wind monitoring, -Ocean surface bio-geo chemistry.

Summary of Meteorological Observations, Surface (SMOS), Midway Island.

DTIC Science & Technology

1984-08-01

8 1.7 415 !I _? .,8 1.3.. 35 1962 9 ’.2 32 l󈧽 9 t.o 27 1965 10 1.2 2 1062 10 1 z1 1*6?2 11 1 - 641 ’ .E 24 1971 12 ’.11 1 !97 12 100 77 19 __9 13 1... 1971 22 1. 4 72 19ev 22 2 0 < 53 1’$6 7_______ 23 *1 . 961 23 1.13 2 ; 1981 24 ". 1’ 5 46P 24 1.-4 42’ 1952 25 ’. 0 36 1i)79 26 l.’b %s 蚝 1 26 𔃻. 6...OBSERVATIONS) j2 7ŕ 74!:WAY !SLA.𔃼 73-R2 MAY SiUUlm iS&AYWI MUl Y IOUAI kALL WEATHEP IP MMW=N ( L.8.1 . SIf, UL S aiim MEAN INTS I13 4.6 7-10 1114 17.21

Long-term SMOS soil moisture products: A comprehensive evaluation across scales and methods in the Duero Basin (Spain)

NASA Astrophysics Data System (ADS)

González-Zamora, Ángel; Sánchez, Nilda; Martínez-Fernández, José; Gumuzzio, Ángela; Piles, María; Olmedo, Estrella

The European Space Agency's Soil Moisture and Ocean Salinity (SMOS) Level 2 soil moisture and the new L3 product from the Barcelona Expert Center (BEC) were validated from January 2010 to June 2014 using two in situ networks in Spain. The first network is the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS), which has been extensively used for validating remotely sensed observations of soil moisture. REMEDHUS can be considered a small-scale network that covers a 1300 km2 region. The second network is a large-scale network that covers the main part of the Duero Basin (65,000 km2). At an existing meteorological network in the Castilla y Leon region (Inforiego), soil moisture probes were installed in 2012 to provide data until 2014. Comparisons of the temporal series using different strategies (total average, land use, and soil type) as well as using the collocated data at each location were performed. Additionally, spatial correlations on each date were computed for specific days. Finally, an improved version of the Triple Collocation (TC) method, i.e., the Extended Triple Collocation (ETC), was used to compare satellite and in situ soil moisture estimates with outputs of the Soil Water Balance Model Green-Ampt (SWBM-GA). The results of this work showed that SMOS estimates were consistent with in situ measurements in the time series comparisons, with Pearson correlation coefficients (R) and an Agreement Index (AI) higher than 0.8 for the total average and the land-use averages and higher than 0.85 for the soil-texture averages. The results obtained at the Inforiego network showed slightly better results than REMEDHUS, which may be related to the larger scale of the former network. Moreover, the best results were obtained when all networks were jointly considered. In contrast, the spatial matching produced worse results for all the cases studied. These results showed that the recent reprocessing of the L2 products (v5.51) improved

Continental hydrology from satellite multi-sensor data and in situ observations

NASA Astrophysics Data System (ADS)

Kouraev, A. V.

2009-04-01

Continental waters represent a tiny part of the total water amount on Earth, but play a major role in climate variability and have paramount importance for terrestrial ecosystems and human needs. They are an integral part of the global climate system with important links and feedbacks generated through its influence on surface energy and moisture fluxes between continental water, atmosphere and oceans. It is important to well understand what are temporal and spatial scales of variability of continental waters, what are teleconnections, feedbacks and mechanisms responsible for the changes, what are natural and anthropogenic causes of recent and historical changes in the hydrometeorological parameters. In this respect, continental hydrology is one of the research fields where acquired knowledge and understanding of natural processes will benefit from combination of conventional observations with data from SMOS and other Earth Observation satellites. We present studies of two key regions where SMOS data have the potential to significantly expand the potential of scientific and applied studies: a) Western Siberia and b) Euphrates-Tigris river system. Main part of the Western Siberia is covered by Ob' river system; which will be the main object of study for this region. This river basin is characterised by large flooded areas, frequently described as the biggest world swamp. Wetlands are also an important source of methane and source/sink for the CO2. Although wetlands played a key role in the natural variations of carbon cycle during the last climatic cycles, their temporal and spatial variations are still poorly modelled. As a consequence, it is very difficult to predict the effect of their variations with climate change and the resulting effect on the carbon cycle for the next decades. Water resources of the extensive Euphrates-Tigris (ET) river basin have vital importance for people living on its watershed, and for its ecosystems. This river basin also provides

Definition of SMOS Level 3 Land Products for the Villafranca del Castillo Data Processing Centre (CP34)

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.; Monsoriu Torres, A.; Font, J.; Alonso, O.

2009-04-01

The ESA SMOS (Soil Moisture and Ocean Salinity) Mission is planned to be launched in July 2009. The satellite will measure soil moisture over the continents and surface salinity of the oceans at resolutions that are sufficient for climatological-type studies. This paper describes the procedure to be used at the Spanish SMOS Level 3 and 4 Data Processing Centre (CP34) to generate Soil Moisture and other Land Surface Product maps from SMOS Level 2 data. This procedure can be used to map Soil Moisture, Vegetation Water Content and Soil Dielectric Constant data into different pre-defined spatial grids with fixed temporal frequency. The L3 standard Land Surface Products to be generated at CP34 are: Soil Moisture products: maximum spatial resolution with no spatial averaging, temporal averaging of 3 days, daily generation maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. b': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month), generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation Seasonal average, temporal averaging from L3 monthly averages, seasonally generation yearly average, temporal averaging from L3 monthly averages, yearly generation Vegetation Water Content products: maximum spatial resolution with no spatial averaging, temporal averaging of 10 days, generation frequency of once every 10 days. a': maximum spatial resolution with no spatial averaging, temporal averaging of monthly decades (1st to 10th of the month, 11th to 20th of the month, 21st to last day of the month) using simple averaging method over the L2 products in ISEA grid, generation frequency of once every decade monthly average, temporal averaging from L3 decade averages, monthly generation seasonal average, temporal averaging from

Summary of Meteorological Observations, Surface (SMOS), Lakehurst, New Jersey.

DTIC Science & Technology

1984-08-01

8aq 1,qo 1,37 1.82 2o 𔄃 2o2S 1,52 1.2 ° 071 -7 c ,s ISt 60o1 i( e73 954 195 1.0 P2 1o, 7 0-. o .73- 7.- .9z .A .63 09e .25 1. ,4 3.97 .36 1.51 1.57...NC PERCENTAGE FREQUENCY OF WIND DIRECTION AND SPEED (FROM HOURLY OBSERVATIONS) ’,-7 . L ’Li u R %T. 1:J ’ JAI, STATOR STATOR MASS TIANS *MTN LL inE

Snow depth retrieval from L-band satellite measurements on Arctic and Antarctic sea ice

NASA Astrophysics Data System (ADS)

Maaß, N.; Kaleschke, L.; Wever, N.; Lehning, M.; Nicolaus, M.; Rossmann, H. L.

2017-12-01

The passive microwave mission SMOS provides daily coverage of the polar regions and measures at a low frequency of 1.4 GHz (L-band). SMOS observations have been used to operationally retrieve sea ice thickness up to 1 m and to estimate snow depth in the Arctic for thicker ice. Here, we present how SMOS-retrieved snow depths compare with airborne measurements from NASA's Operation IceBridge mission (OIB) and with AMSR-2 satellite retrievals at higher frequencies, and we show first applications to Antarctic sea ice. In previous studies, SMOS and OIB snow depths showed good agreement on spatial scales from 50 to 1000 km for some days and disagreement for other days. Here, we present a more comprehensive comparison of OIB and SMOS snow depths in the Arctic for 2011 to 2015. We find that the SMOS retrieval works best for cold conditions and depends on auxiliary information on ice surface temperature, here provided by MODIS thermal imagery satellite data. However, comparing SMOS and OIB snow depths is difficult because of the different spatial resolutions (SMOS: 40 km, OIB: 40 m). Spatial variability within the SMOS footprint can lead to different snow conditions as seen from SMOS and OIB. Ideally the comparison is made for uniform conditions: Low lead and open water fraction, low spatial and temporal variability of ice surface temperature, no mixture of multi- and first-year ice. Under these conditions and cold temperatures (surface temperatures below -25°C), correlation coefficients between SMOS and OIB snow depths increase from 0.3 to 0.6. A finding from the comparison with AMSR-2 snow depths is that the SMOS-based maps depend less on the age of the sea ice than the maps derived from higher frequencies. Additionally, we show first results of SMOS snow depths for Antarctic sea ice. SMOS observations are compared to measurements of autonomous snow buoys drifting in the Weddell Sea since 2014. For a better comparability of these point measurements with SMOS data, we use

Summary of Meteorological Observations, Surface (SMOS), Patuxent River, Maryland.

DTIC Science & Technology

1983-11-01

annual (all months). The extremes for a month are not printed nor used in computations if one or more observations are missing. NOTE: Snow depth was...297 1979 20 1 jn7 77 -1279 3.7 *a 1l7 20 .1.12.U 21 lol 2 71 1969 21 1 1 4 1949 111.31 I -J&2 21 2.9 91 1*!l& n.1 . 19&LL 22 -I2 JJD 2p’ 1971 22- 3D ’A...month, the extreme is selected and printed . These values are then used to compute means and standard deviations for the entire period. Every month of a

Soil moisture extremes drive tree canopy death in 2011 Texas drought: multispectral (Landsat, NAIP) and L-band passive microwave remote sensing (SMOS-IC)

NASA Astrophysics Data System (ADS)

Swenson, J. J.; Schwantes, A. M.; Johnson, D. M.; Domec, J. C.; Wigneron, J. P.

2017-12-01

Climate change is bringing more frequent and intense droughts that are causing broad scale tree mortality events. Detecting regional drought stress is now more frequently monitored with passive microwave satellite sensing of soil moisture (SM) and vegetation water status (through the vegetation optical depth (VOD) index), that can be validated with in-situ measurements of soil moisture or corroborated with satellite multispectral indices of greenness. The detection of canopy death however marks the passing of a definitive physiological threshold. We compare soil moisture from the L-band SMOS-IC passive microwave product (2010-20176) to an accurate and detailed (30-m spatial resolution) map of canopy loss across the US state of Texas during the record breaking 2011 drought. The SMOS-IC product (25 km) is a new and simpler product of soil moisture and VOD that has been shown to be more accurate than past SMOS products and it is independent of ancillary data. Canopy loss was mapped from Landsat imagery trained with 186, 41 km2 subplots of classified National Agriculture Inventory Program color infrared aerial imagery recorded before and after the drought. Bringing these two datasets of disparate spatial resolution together and averaging them across the state, we find that areas with at least 25% tree cover that experienced the most canopy loss (highest quartile) had lower soil moisture compared to areas with less canopy loss in 2011. These areas with the most loss, experienced up to 9 weeks of the growing season at < 0.05 SM (m3/m3), while the rest of Texas forests, experienced just 1 week at that SM. The following years, 2012 - 2016, dropped below 0.05 SM very rarely (two weeks each in 2012 and 2015, and never for 2013, 2014, 2016). Forests during the drought of 2011 experienced the absolute lowest SM (0.031) and had the earliest onset of low SM across the 6 years analyzed. Analyzing areas of drought induced canopy loss with SM preceding and during drought across a

L-band Dielectric Constant Measurements of Seawater (Oral presentation and SMOS Poster)

NASA Technical Reports Server (NTRS)

Lang, Roger H.; Utku, Cuneyt; LeVine, David M.

2003-01-01

This paper describes a resonant cavity technique for the measurement of the dielectric constant of seawater as a function of its salinity. Accurate relationships between salinity and dielectric constant (which determines emissivity) are needed for sensor systems such as SMOS and Aquarius that will monitor salinity from space in the near future. The purpose of the new measurements is to establish the dependence of the dielectric constant of seawater on salinity in contemporary units (e.g. psu) and to take advantage of modern instrumentation to increase the accuracy of these measurements. The measurement device is a brass cylindrical cavity 16cm in diameter and 7cm in height. The seawater is introduced into the cavity through a slender glass tube having an inner diameter of 0.1 mm. By assuming that this small amount of seawater slightly perturbs the internal fields in the cavity, perturbation theory can be employed. A simple formula results relating the real part of the dielectric constant to the change in resonant frequency of the cavity. In a similar manner, the imaginary part of the dielectric constant is related to the change in the cavity s Q. The expected accuracy of the cavity technique is better than 1% for the real part and 1 to 2% for the imaginary part. Presently, measurements of methanol have been made and agree with precision measurements in the literature to within 1% in both real and imaginary parts. Measurements have been made of the dielectric constant of seawater samples from Ocean Scientific in the United Kingdom with salinities of 10, 30, 35 and 38 psu. All measurements were made at room temperature. Plans to make measurements at a range of temperatures and salinities will be discussed.

Satellite surface salinity maps to determine fresh water fluxes in the Arctic Ocean

NASA Astrophysics Data System (ADS)

Gabarro, Carolina; Estrella, Olmedo; Emelianov, Mikhail; Ballabrera, Joaquim; Turiel, Antonio

2017-04-01

Salinity and temperature gradients drive the thermohaline circulation of the oceans, and play a key role in the ocean-atmosphere coupling. The strong and direct interactions between the ocean and the cryosphere (primarily through sea ice and ice shelves) are also a key ingredient of the thermohaline circulation. Recent observational studies have documented changes in upper Arctic Ocean hydrography [1, 2]. The ESA's Soil Moisture and Ocean Salinity (SMOS) mission, launched in 2009, have the objective to measure soil moisture over the continents and sea surface salinity over the oceans [3]. However, SMOS is also making inroads in Cryospheric science, as the measurements of thin ice thickness and sea ice concentration. SMOS carries an innovative L-band (1.4 GHz, or 21-cm wavelength), passive interferometric radiometer (the so-called MIRAS) that measures the electromagnetic radiation emitted by the Earth's surface, at about 50 km spatial resolution wide swath (1200-km), and with a 3-day revisit time at the equator, but more frequently at the poles. Although the SMOS radiometer operating frequency offers almost the maximum sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) variations, such sensitivity is rather low, even lower at cold waters [4]: 90% of ocean SSS values span a range of brightness temperatures of just 5K. This implies that the SMOS SSS retrieval requires a high performance of the MIRAS interferometric radiometer [5]. New algorithms, recently developed at the Barcelona Expert Center (BEC) to improve the quality of SMOS measurements [6], allow for the first time to derive cold-water SSS maps from SMOS data, and to observe the variability of the SSS in the higher north Atlantic and the Arctic Ocean. In this work, we will provide an assessment of the quality of these new SSS Arctic maps, and we will illustrate their potential to monitor the impact on ocean state of the discharges from the main rivers to the Arctic Ocean. Moreover

Transitioning to Integrated Modular Avionics with a Mission Management System

DTIC Science & Technology

2000-10-01

software structure, which is based on the use of a of interchangeable processing modules of a limited COTS Real - Time Operating System . number of...open standardised interfaces system hardware or the Real - Time Operating System directly supports the use of COTS components, which implementation, to...System RTOS Real - Time Operating System SMBP System Management Blueprint Interface SMOS System Management to Operating System Interface Figure 2: The ASAAC

Soil Moisture Data Assimilation in the NASA Land Information System for Local Modeling Applications and Improved Situational Awareness

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Blakenship, Clay B.; Zavodsky, Bradley T.

2014-01-01

As part of the NASA Soil Moisture Active Passive (SMAP) Early Adopter (EA) program, the NASA Shortterm Prediction Research and Transition (SPoRT) Center has implemented a data assimilation (DA) routine into the NASA Land Information System (LIS) for soil moisture retrievals from the European Space Agency's Soil Moisture Ocean Salinity (SMOS) satellite. The SMAP EA program promotes application-driven research to provide a fundamental understanding of how SMAP data products will be used to improve decision-making at operational agencies. SPoRT has partnered with select NOAA/NWS Weather Forecast Offices (WFOs) that use output from a real-time regional configuration of LIS, without soil moisture DA, to initialize local numerical weather prediction (NWP) models and enhance situational awareness. Improvements to local NWP with the current LIS have been demonstrated; however, a better representation of the land surface through assimilation of SMOS (and eventually SMAP) retrievals is expected to lead to further model improvement, particularly during warm-season months. SPoRT will collaborate with select WFOs to assess the impact of soil moisture DA on operational forecast situations. Assimilation of the legacy SMOS instrument data provides an opportunity to develop expertise in preparation for using SMAP data products shortly after the scheduled launch on 5 November 2014. SMOS contains a passive L-band radiometer that is used to retrieve surface soil moisture at 35-km resolution with an accuracy of 0.04 cu cm cm (exp -3). SMAP will feature a comparable passive L-band instrument in conjunction with a 3-km resolution active radar component of slightly degraded accuracy. A combined radar-radiometer product will offer unprecedented global coverage of soil moisture at high spatial resolution (9 km) for hydrometeorological applications, balancing the resolution and accuracy of the active and passive instruments, respectively. The LIS software framework manages land surface model

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

NASA Technical Reports Server (NTRS)

Bolten, John D.; Mladenova, Iliana E.; Crow, Wade; De Jeu, Richard

2016-01-01

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

Data Assimilation of SMAP Observations and the Impact on Weather Forecasts and Heat Stress

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; Case, Jonathan; Blankenship, Clay; Crosson, William; White, Khristopher

2014-01-01

SPoRT produces real-time LIS soil moisture products for situational awareness and local numerical weather prediction over CONUS, Mesoamerica, and East Africa ?Currently interact/collaborate with operational partners on evaluation of soil moisture products ?Drought/fire ?Extreme heat ?Convective initiation ?Flood and water borne diseases ?Initial efforts to assimilate L2 soil moisture observations from SMOS (as a precursor for SMAP) have been successful ?Active/passive blended product from SMAP will be assimilated similarly and higher spatial resolution should improve on local-scale processes

Canadian Experiment for Soil Moisture in 2010 (CanEX-SM10): Overview and Preliminary Results

NASA Technical Reports Server (NTRS)

Magagi, Ramata; Berg, Aaron; Goita, Kalifa; Belair, Stephane; Jackson, Tom; Toth, B.; Walker, A.; McNairn, H.; O'Neill, P.; Moghdam. M;

Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

NASA Technical Reports Server (NTRS)

Kim, Edward; Walker, Jeff; Rudiger, Christopher; Panciera, Rocco

2010-01-01

L-band imaging radar is being added to the complement to provide simultaneous active-passive L-band observations, for algorithm development activities in support of NASA's upcoming Soil Moisture Active Passive (.S"M) mission. This paper will describe the campaigns, their objectives, their datasets, and some of the unique advantages of working with small/light sensors and aircraft. We will also review the main scientific findings, including improvements to the SMOS retrieval algorithm enabled by NAFE observations and the evaluation of the Simpson Desert as a calibration target for L-band satellite missions. Plans for upcoming campaigns will also be discussed.

Satellite observed salinity distributions at high latitudes in the Northern Hemisphere: A comparison of four products

NASA Astrophysics Data System (ADS)

Garcia-Eidell, Cynthia; Comiso, Josefino C.; Dinnat, Emmanuel; Brucker, Ludovic

2017-09-01

Global surface ocean salinity measurements have been available since the launch of SMOS in 2009 and coverage was further enhanced with the launch of Aquarius in 2011. In the polar regions where spatial and temporal changes in sea surface salinity (SSS) are deemed important, the data have not been as robustly validated because of the paucity of in situ measurements. This study presents a comparison of four SSS products in the ice-free Arctic region, three using Aquarius data and one using SMOS data. The accuracy of each product is assessed through comparative analysis with ship and other in situ measurements. Results indicate RMS errors ranging between 0.33 and 0.89 psu. Overall, the four products show generally good consistency in spatial distribution with the Atlantic side being more saline than the Pacific side. A good agreement between the ship and satellite measurements was also observed in the low salinity regions in the Arctic Ocean, where SSS in situ measurements are usually sparse, at the end of summer melt seasons. Some discrepancies including biases of about 1 psu between the products in spatial and temporal distribution are observed. These are due in part to differences in retrieval techniques, geophysical filtering, and sea ice and land masks. The monthly SSS retrievals in the Arctic from 2011 to 2015 showed variations (within ˜1 psu) consistent with effects of sea ice seasonal cycles. This study indicates that spaceborne observations capture the seasonality and interannual variability of SSS in the Arctic with reasonably good accuracy.

Inter-comparison of SMAP, Aquarius and SMOS L-band brightness temperature observations

USDA-ARS?s Scientific Manuscript database

Soil Moisture Active Passive (SMAP) mission is scheduled for launch on January 29, 2015. SMAP will make observations with an L-band radar and radiometer using a shared 6 m rotating reflector antenna. SMAP is a fully polarimetric radiometer with the center frequency of 1.41 GHz. The target accuracy o...

Integrating SMOS brightness temperatures with a new conceptual spatially distributed hydrological model for improving flood and drought predictions at large scale.

NASA Astrophysics Data System (ADS)

Hostache, Renaud; Rains, Dominik; Chini, Marco; Lievens, Hans; Verhoest, Niko E. C.; Matgen, Patrick

2017-04-01

, SUPERFLEX is capable of predicting runoff, soil moisture, and SMOS-like brightness temperature time series. Such a model is traditionally calibrated using only discharge measurements. In this study we designed a multi-objective calibration procedure based on both discharge measurements and SMOS-derived brightness temperature observations in order to evaluate the added value of remotely sensed soil moisture data in the calibration process. As a test case we set up the SUPERFLEX model for the large scale Murray-Darling catchment in Australia ( 1 Million km2). When compared to in situ soil moisture time series, model predictions show good agreement resulting in correlation coefficients exceeding 70 % and Root Mean Squared Errors below 1 %. When benchmarked with the physically based land surface model CLM, SUPERFLEX exhibits similar performance levels. By adapting the runoff routing function within the SUPERFLEX model, the predicted discharge results in a Nash Sutcliff Efficiency exceeding 0.7 over both the calibration and the validation periods.

ELBARA II, an L-band radiometer system for soil moisture research.

PubMed

Schwank, Mike; Wiesmann, Andreas; Werner, Charles; Mätzler, Christian; Weber, Daniel; Murk, Axel; Völksch, Ingo; Wegmüller, Urs

2010-01-01

L-band (1-2 GHz) microwave radiometry is a remote sensing technique that can be used to monitor soil moisture, and is deployed in the Soil Moisture and Ocean Salinity (SMOS) Mission of the European Space Agency (ESA). Performing ground-based radiometer campaigns before launch, during the commissioning phase and during the operative SMOS mission is important for validating the satellite data and for the further improvement of the radiative transfer models used in the soil-moisture retrieval algorithms. To address these needs, three identical L-band radiometer systems were ordered by ESA. They rely on the proven architecture of the ETH L-Band radiometer for soil moisture research (ELBARA) with major improvements in the microwave electronics, the internal calibration sources, the data acquisition, the user interface, and the mechanics. The purpose of this paper is to describe the design of the instruments and the main characteristics that are relevant for the user.

ELBARA II, an L-Band Radiometer System for Soil Moisture Research

PubMed Central

Schwank, Mike; Wiesmann, Andreas; Werner, Charles; Mätzler, Christian; Weber, Daniel; Murk, Axel; Völksch, Ingo; Wegmüller, Urs

2010-01-01

L-band (1–2 GHz) microwave radiometry is a remote sensing technique that can be used to monitor soil moisture, and is deployed in the Soil Moisture and Ocean Salinity (SMOS) Mission of the European Space Agency (ESA). Performing ground-based radiometer campaigns before launch, during the commissioning phase and during the operative SMOS mission is important for validating the satellite data and for the further improvement of the radiative transfer models used in the soil-moisture retrieval algorithms. To address these needs, three identical L-band radiometer systems were ordered by ESA. They rely on the proven architecture of the ETH L-Band radiometer for soil moisture research (ELBARA) with major improvements in the microwave electronics, the internal calibration sources, the data acquisition, the user interface, and the mechanics. The purpose of this paper is to describe the design of the instruments and the main characteristics that are relevant for the user. PMID:22315556

A Proposed Extension to the Soil Moisture and Ocean Salinity Level 2 Algorithm for Mixed Forest and Moderate Vegetation Pixels

NASA Technical Reports Server (NTRS)

Panciera, Rocco; Walker, Jeffrey P.; Kalma, Jetse; Kim, Edward

2011-01-01

optical depth of the forested area (better than 35% uncertainty). This study makes use of an unprecedented data set of airborne L-band observations and ground supporting data from the National Airborne Field Experiment 2005 (NAFE'05), which allowed accurate characterisation of the land surface heterogeneity over an area equivalent in size to a SMOS pixel.

Summary of Meteorological Observations, Surface (SMOS), Pensacola, Florida.

DTIC Science & Technology

1984-02-01

1 o ot TD 3__- 7o 0lU4 .9 iop -- I f 61 goo * 94 1.6 b 22 Ne o_ TT 9,! oU .4’ 2.2 3.6 2.1 .2 SOS SOS S * ___, 301_____ o__ 15,3* 9.2 SW .0 1 __ 3 1...2 1 93 C 1Q3 - 2t 1000 9 9 o ,.j -7 𔃻 94 ’ 4* . 5 Soft t 4. 94I 9f , ’ o. • no SW * ~ ~ ~ ’)~ 𔄁 .9 9". 46 9’.. -41195 ’,’., .2 07 > 700 * . 7 A...34. ’Iloa 29 *U 6S*2 3 .0I I, I".1 -a. 0 .1 g. 01 IS,.0 1 I 0" 93o3 I or! 2So.3 . 7%.’ oft 11 II tD ’:ca t’r. 0 6 e .; 92oe4 4 45 C.7 -? o ’, TOTALS 9 5 2

Summary of Meteorological Observations, Surface (SMOS) Pensacola, Florida.

DTIC Science & Technology

1978-07-01

flSV~MAYN IC’~4~ ~~~ ) ‘) .) ‘ - J IISPS -LS0I 151,1 I — — — _ — ________— — — -~~ -~~ ~~~~~~~~~~~~~~~~~~~~ -, I F~~~ ’ ~~~~~~~~~~~ —~~ . ~~ J-~4S

Summary of Meteorological Observations, Surface (SMOS), Glenview, Illinois.

DTIC Science & Technology

1984-08-01

READ INSTRUCTIONS REPORT DOCUMENTATION PAGE BEFORE COMPLETING FORM 1 . REPORT NUMBER 2. GOVT ACCESSION NO. 3. RECIPIENT’S CATALOG NUMBER 4. TITLE (end...CEOCNAPHICAL LOCATION I NANE OF LATITUDE LMCITUSE PEI L OCATIO STATION irkN To STATION IFT) TM NAROITEM SAT 1 . 4eather service office located in Navy 1948...LOCATION CHANCE LOCATION TANSOFT T YPE or5K NU ABOVE______________________ 1 . 1948 Roof of control tower atop Selsyn Triple 77.8’ 1 .Barograph (ML-3

Summary of Meteorological Observations, Surface (SMOS), Brunswick, Maine

DTIC Science & Technology

1988-12-01

8217 0 -~ ~ ~ C 00 𔃺 ’-P-~ r-InN0 r In0 o- U"N.-𔃺 ’’~ :1-0 0 OI In (11 Z m 0 0’m 󈧅 o ,- NcaO .- 0 In U)in In 10 𔃺’c 𔃺r- 000I0I-- o o 0’,00’ 0 0, C),0

Soil moisture on Polish territory - comparison of satellite and ground-based measurements

NASA Astrophysics Data System (ADS)

Rojek, Edyta; Łukowski, Mateusz; Marczewski, Wojciech; Usowicz, Bogusław

2014-05-01

Assessment of water resources due to changing climatic conditions in time and space is still very uncertain. The territory of Poland has a limited resource of waters, occasionally resulting in small agricultural droughts. From the other side intense rainfalls, floods or run-offs, causing soil erosion are observed. Therefore, it is important to predict and prevent of this adverse phenomena. Huge spatial variability of soil moisture does not allow for accurate estimation of its distribution using ground-based measurements. SMOS soil moisture data are quite much inherently consistent in time and space, but their validation is still a challenge for further use in the climate and hydrology studies. This is the motivation for the research: to examine soil moisture from SMOS and ground based stations of the SWEX network held over eastern Poland. The presented results are related to changes of the soil moisture on regional scales for Poland in the period 2010-2013. Some results with SMOS L2 data are extended on continental scales for Europe. Time series from ground and satellite SMOS data sources were compared by regression methods. The region of Poland indicates clearly some genetic spatial distributions in weekly averaged values. In continental scales, the country territory contrasts evidently to Lithuania and in Polesie, and indicates seasonal cycling observed in archives and well known traditional records. The central part of Poland is repeatedly susceptible on droughts with soil moisture values ranging from about 0.02 to 0.20 m3 m-3. SMOS data allows on creating systematic drought data for Poland and watching annual changes, and differences to other drought services kept on national scales for agricultural purposes. We bound that drought susceptibility to the content of sand clay components and the land use there. Lack of rainfall in the late 2011 summer, caused a significant deficit of water in soil moisture content (below 0.05 m3 m-3) throughout the entire country

Four Decades of Microwave Satellite Soil Moisture Observations: Product validation and inter-satellite comparisons

NASA Astrophysics Data System (ADS)

Lanka, K.; Pan, M.; Wanders, N.; Kumar, D. N.; Wood, E. F.

2017-12-01

The satellite based passive and active microwave sensors enhanced our ability to retrieve soil moisture at global scales. It has been almost four decades since the first passive microwave satellite sensor was launched in 1978. Since then soil moisture has gained considerable attention in hydro-meteorological, climate, and agricultural research resulting in the deployment of two dedicated missions in the last decade, SMOS and SMAP. Signifying the four decades of microwave remote sensing of soil moisture, this work aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy of retrieving soil moisture. We considered daily coverage, temporal performance, and spatial performance to assess the accuracy of products corresponding to eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product), using 1058 ISMN in-situ stations and the VIC LSM soil moisture simulations (VICSM) over the CONUS. Our analysis indicated that the daily coverage has increased from 30 % during 1980s to 85 % (during non-winter months) with the launch of dedicated soil moisture missions SMOS and SMAP. The temporal validation of passive and active soil moisture products with the ISMN data place the range of median RMSE as 0.06-0.10 m3/m3 and median correlation as 0.20-0.68. When TMI, AMSR-E and WindSAT are evaluated, the AMSR-E sensor is found to have produced the brightness temperatures with better quality, given that these sensors are paired with same retrieval algorithm (LPRM). The ASCAT product shows a significant improvement during the temporal validation of retrievals compared to its predecessor ERS, thanks to enhanced sensor configuration. The SMAP mission, through its improved sensor design and RFI handling, shows a high retrieval accuracy under all-topography conditions

SMOS L1PP Performance Analysis from Commissioning Phase - Improved Algorithms and Major Results

NASA Astrophysics Data System (ADS)

Castro, Rita; Oliva, Roger; Gutiérrez, Antonio; Barbosa, José; Catarino, Nuno; Martin-Neira, Manuel; Zundo, Michele; Cabot, François

2010-05-01

Following the Soil Moisture and Ocean Salinity (SMOS) launch in November 2009, a Commissioning Phase has taken place for six months, having Deimos closely cooperated with the European Space Agency's (ESA) Level 1 team. During these six months several studies have been conducted on calibration optimization, image reconstruction improvement, geolocation assessment and the impact on scientific results, in particular to insure optimal input to Level 2 Soil Moisture and Ocean Salinity retrieval. In parallel with the scientific studies, some new algorithms/mitigation techniques had to be developed, tested and implemented during the Commissioning Phase. Prior to launch, the Level 1 Prototype Processor (L1PP) included already several experimental algorithms different from the ones existent in the operational chain. These algorithms were tested during Commissioning and some were included in the final processing baseline as a result of the planned studies. Some unforeseen algorithms had to be defined, implemented and tested during the Commissioning Phase itself and these will also be described below. In L1a, for example, the calibration of the Power Measuring Systems (PMS) can be done using a cold target as reference, i.e., the Sky at ~3 K. This has been extensively analyzed and the results will be presented here. At least two linearity corrections to the PMS response function have been tested and compared. The deflection method was selected for inclusion on the operational chain and the results leading to this decision will be also presented. In Level 1B, all the foreign sources algorithms have been tested and validated using real data. The System Response Function (G-matrix) computed for different events has been analyzed and criteria for validation of its pseudo inverse, the J+ matrix, have been defined during the Commissioning Phase. The impact of errors in the J+ matrix has been studied and well characterized. The effects of the Flat Target Response (FTR) have also been

Satellite Sea-surface Salinity Retrieval Dependencies

NASA Astrophysics Data System (ADS)

Bayler, E. J.; Ren, L.

2016-02-01

Comparing satellite sea-surface salinity (SSS) measurements and in situ observations reveals large-scale differences. What causes these differences? In this study, five boxes, sampling various oceanic regimes of the global ocean, provide insights on the relative performance of satellite SSS retrievals with respect to the influences of SST, precipitation and wind speed. The regions sampled are: the Inter-tropical Convergence Zone (ITCZ), the South Pacific Convergence Zone (SPCZ), NASA's Salinity Processes of the Upper-ocean Regional Study (SPURS) area, the North Pacific subarctic region, and the southern Indian Ocean. This study examines satellite SSS data from NASA's Aquarius Mission and ESA's Soil Moisture - Ocean Salinity (SMOS) mission, specifically: Aquarius official Aquarius Data Processing System (ADPS) Level-2 data, experimental Aquarius Combined Active-Passive (CAP) Level-2 SSS data developed by NASA's Jet Propulsion Laboratory (JPL), and SMOS Level-2 data.

System/observer/controller identification toolbox

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Horta, Lucas G.; Phan, Minh

1992-01-01

System Identification is the process of constructing a mathematical model from input and output data for a system under testing, and characterizing the system uncertainties and measurement noises. The mathematical model structure can take various forms depending upon the intended use. The SYSTEM/OBSERVER/CONTROLLER IDENTIFICATION TOOLBOX (SOCIT) is a collection of functions, written in MATLAB language and expressed in M-files, that implements a variety of modern system identification techniques. For an open loop system, the central features of the SOCIT are functions for identification of a system model and its corresponding forward and backward observers directly from input and output data. The system and observers are represented by a discrete model. The identified model and observers may be used for controller design of linear systems as well as identification of modal parameters such as dampings, frequencies, and mode shapes. For a closed-loop system, an observer and its corresponding controller gain directly from input and output data.

Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre

2017-01-01

The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.

Contribution of proline to the pre-structuring tendency of transient helical secondary structure elements in intrinsically disordered proteins.

PubMed

Lee, Chewook; Kalmar, Lajos; Xue, Bin; Tompa, Peter; Daughdrill, Gary W; Uversky, Vladimir N; Han, Kyou-Hoon

2014-03-01

IDPs function without relying on three-dimensional structures. No clear rationale for such a behavior is available yet. PreSMos are transient secondary structures observed in the target-free IDPs and serve as the target-binding "active" motifs in IDPs. Prolines are frequently found in the flanking regions of PreSMos. Contribution of prolines to the conformational stability of the helical PreSMos in IDPs is investigated. MD simulations are performed for several IDP segments containing a helical PreSMo and the flanking prolines. To measure the influence of flanking-prolines on the structural content of a helical PreSMo calculations were done for wild type as well as for mutant segments with Pro→Asp, His, Lys, or Ala. The change in the helicity due to removal of a proline was measured both for the PreSMo region and for the flanking regions. The α-helical content in ~70% of the helical PreSMos at the early stage of simulation decreases due to replacement of an N-terminal flanking proline by other residues whereas the helix content in nearly all PreSMos increases when the same replacements occur at the C-terminal flanking region. The helix destabilizing/terminating role of the C-terminal flanking prolines is more pronounced than the helix promoting effect of the N-terminal flanking prolines. This work represents a novel example demonstrating that a proline is encoded in an IDP with a defined purpose. The helical PreSMos presage their target-bound conformations. As they most likely mediate IDP-target binding via conformational selection their helical content can be an important feature for IDP function. Copyright © 2013 Elsevier B.V. All rights reserved.

The Group on Earth Observations and the Global Earth Observation System of Systems

NASA Astrophysics Data System (ADS)

Achache, J.

2006-05-01

The Group on Earth Observations (GEO) is leading a worldwide effort to build a Global Earth Observation System of Systems (GEOSS) over the next 10 years. The GEOSS vision, articulated in its 10-Year Implementation Plan, represents the consolidation of a global scientific and political consensus: the assessment of the state of the Earth requires continuous and coordinated observation of our planet at all scales. GEOSS aims to achieve comprehensive, coordinated and sustained observations of the Earth system in order to improve monitoring of the state of the Earth; increase understanding of Earth processes; and enhance prediction of the behaviour of the Earth system. After the World Summit on Sustainable Development in 2002 highlighted the urgent need for coordinated observations relating to the state of the Earth, GEO was established at the Third Earth Observation Summit in February 2005 and the GEOSS 10-Year Implementation Plan was endorsed. GEO currently involves 60 countries; the European Commission; and 43 international organizations and has begun implementation of the GEOSS 10-Year Implementation Plan. GEO programme activities cover nine societal benefit areas (Disasters; Health; Energy; Climate; Water; Weather; Ecosystems; Agriculture; Biodiversity) and five transverse or crosscutting elements (User Engagement; Architecture; Data Management; Capacity Building; Outreach). All these activities have as their final goal the establishment of the "system of systems" which will yield a broad range of basic societal benefits, including the reduction of loss of life and property from tsunamis, hurricanes, and other natural disasters; improved water resource and energy management; and improved understanding of environmental factors significant to public health. As a "system of systems", GEOSS will work with and build upon existing national, regional, and international systems to provide comprehensive, coordinated Earth observations from thousands of instruments worldwide

Application of the Auto-Tuned Land Assimilation System (ATLAS) to ASCAT and SMOS soil moisture retrieval products

USDA-ARS?s Scientific Manuscript database

Land data assimilations are typically based on highly uncertain assumptions regarding the statistical structure of observation and modeling errors. Left uncorrected, poor assumptions can degrade the quality of analysis products generated by land data assimilation systems. Recently, Crow and van de...

Combined evaluation of optical and microwave satellite dataset for soil moisture deficit estimation

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Han, Dawei; Islam, Tanvir; Singh, Sudhir Kumar; Gupta, Manika; Gupta, Dileep Kumar; Kumar, Pradeep

2016-04-01

Soil moisture is a key variable responsible for water and energy exchanges from land surface to the atmosphere (Srivastava et al., 2014). On the other hand, Soil Moisture Deficit (or SMD) can help regulating the proper use of water at specified time to avoid any agricultural losses (Srivastava et al., 2013b) and could help in preventing natural disasters, e.g. flood and drought (Srivastava et al., 2013a). In this study, evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and soil moisture from Soil Moisture and Ocean Salinity (SMOS) satellites are attempted for prediction of Soil Moisture Deficit (SMD). Sophisticated algorithm like Adaptive Neuro Fuzzy Inference System (ANFIS) is used for prediction of SMD using the MODIS and SMOS dataset. The benchmark SMD estimated from Probability Distributed Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the validation. The performances are assessed in terms of Nash Sutcliffe Efficiency, Root Mean Square Error and the percentage of bias between ANFIS simulated SMD and the benchmark. The performance statistics revealed a good agreement between benchmark and the ANFIS estimated SMD using the MODIS dataset. The assessment of the products with respect to this peculiar evidence is an important step for successful development of hydro-meteorological model and forecasting system. The analysis of the satellite products (viz. SMOS soil moisture and MODIS LST) towards SMD prediction is a crucial step for successful hydrological modelling, agriculture and water resource management, and can provide important assistance in policy and decision making. Keywords: Land Surface Temperature, MODIS, SMOS, Soil Moisture Deficit, Fuzzy Logic System References: Srivastava, P.K., Han, D., Ramirez, M.A., Islam, T., 2013a. Appraisal of SMOS soil moisture at a catchment scale in a temperate maritime climate. Journal of Hydrology 498, 292-304. Srivastava, P.K., Han, D., Rico

Version 3 of the SMAP Level 4 Soil Moisture Product

NASA Technical Reports Server (NTRS)

Reichle, Rolf; Liu, Qing; Ardizzone, Joe; Crow, Wade; De Lannoy, Gabrielle; Kolassa, Jana; Kimball, John; Koster, Randy

2017-01-01

The NASA Soil Moisture Active Passive (SMAP) Level 4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root zone (0-100 cm) soil moisture as well as related land surface states and fluxes from 31 March 2015 to present with a latency of 2.5 days. The ensemble-based L4_SM algorithm is a variant of the Goddard Earth Observing System version 5 (GEOS-5) land data assimilation system and ingests SMAP L-band (1.4 GHz) Level 1 brightness temperature observations into the Catchment land surface model. The soil moisture analysis is non-local (spatially distributed), performs downscaling from the 36-km resolution of the observations to that of the model, and respects the relative uncertainties of the modeled and observed brightness temperatures. Prior to assimilation, a climatological rescaling is applied to the assimilated brightness temperatures using a 6 year record of SMOS observations. A new feature in Version 3 of the L4_SM data product is the use of 2 years of SMAP observations for rescaling where SMOS observations are not available because of radio frequency interference, which expands the impact of SMAP observations on the L4_SM estimates into large regions of northern Africa and Asia. This presentation investigates the performance and data assimilation diagnostics of the Version 3 L4_SM data product. The L4_SM soil moisture estimates meet the 0.04 m3m3 (unbiased) RMSE requirement. We further demonstrate that there is little bias in the soil moisture analysis. Finally, we illustrate where the assimilation system overestimates or underestimates the actual errors in the system.

Rainfall Imprint on Sea Surface Salinity in the ITCZ: new satellite perspectives

NASA Astrophysics Data System (ADS)

Boutin, J.; Viltard, N.; Supply, A.; Martin, N.; Vergely, J. L.; Hénocq, C.; Reverdin, G. P.

2016-02-01

The European Soil Moisture and Ocean Salinity (SMOS) satellite mission monitors sea surface salinity (SSS) over the global ocean for more than 5 years since 2010. The MADRAS microwave radiometer carried by the French (CNES) Indian (ISRO) satellite mission Megha-Tropiques sampled the 30° N-30° S region end of 2011 and in 2012, very complementary to other Global Precipitation Measurement(GPM) missions. In tropical regions, SMOS SSS contains a large imprint of atmospheric rainfall, but is also likely affected by oceanographic processes (advection and diffusion). At local and short time scales, Boutin et al. (2013, 2014) have shown that the spatio-temporal variability of SSS is dominated by rainfall as detected by satellite microwave radiometers and have demonstrated a close to linear relationship between SMOS SSS freshening under rain cells and satellite rain rate. The order of magnitude is in remarkable agreement with the theoretical renewal model of Schlussel et al. (1997) and compatible with AQUARIUS SSS observations, as well as with in situ drifters observations although the latter are local and taken at 45cm depth while satellite L-band SSS roughly correspond to the top 1cm depth and are spatially integrated over 43-150km. It is thus expected that the combined information of satellite rain rates and satellite SSS brings new constraints on the precipitation budget. We first look at the consistency between the spatial structures of SMOS SSS decrease and of rain rates derived either from the MADRAS microwave radiometer or from the CMORPH combined products that do not use MADRAS rain rates. This provides an indirect validation of the rain rates estimates. We then investigate the impact of rain history and of wind speed on the observed SMOS freshening. Based on these results, we discuss the precision on various precipitation estimates over 2012 in the ITCZ region and the major sources of uncertainties that the SPURS2 campaign could help to resolve.

Prediction of Root Zone Soil Moisture using Remote Sensing Products and In-Situ Observation under Climate Change Scenario

NASA Astrophysics Data System (ADS)

Singh, G.; Panda, R. K.; Mohanty, B.

2015-12-01

Prediction of root zone soil moisture status at field level is vital for developing efficient agricultural water management schemes. In this study, root zone soil moisture was estimated across the Rana watershed in Eastern India, by assimilation of near-surface soil moisture estimate from SMOS satellite into a physically-based Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble Kalman filter (EnKF) technique coupled with SWAP model was used for assimilating the satellite soil moisture observation at different spatial scales. The universal triangle concept and artificial intelligence techniques were applied to disaggregate the SMOS satellite monitored near-surface soil moisture at a 40 km resolution to finer scale (1 km resolution), using higher spatial resolution of MODIS derived vegetation indices (NDVI) and land surface temperature (Ts). The disaggregated surface soil moisture were compared to ground-based measurements in diverse landscape using portable impedance probe and gravimetric samples. Simulated root zone soil moisture were compared with continuous soil moisture profile measurements at three monitoring stations. In addition, the impact of projected climate change on root zone soil moisture were also evaluated. The climate change projections of rainfall were analyzed for the Rana watershed from statistically downscaled Global Circulation Models (GCMs). The long-term root zone soil moisture dynamics were estimated by including a rainfall generator of likely scenarios. The predicted long term root zone soil moisture status at finer scale can help in developing efficient agricultural water management schemes to increase crop production, which lead to enhance the water use efficiency.

L-MEB Model Calibration Over the Valencia Anchor Station Area

NASA Astrophysics Data System (ADS)

Lopez-Baeza, E.

2009-04-01

period of both experiments, there was a large range of vegetation and soil moisture conditions related to significant rainfall events, different temperature and vegetation biomass conditions, etc. The experiments consisted on the continuous acquisition of L-band polarimetric and multi angular measurements (from 20 to 60 degrees of elevation) over both types of vegetation using the EMIRAD L-band radiometer from the Electromagnetic System Group (EMI) of the Technical University of Denmark. In addition, measurements of infrared temperature, gravimetric and volumetric soil moisture, soil temperature profile, soil roughness and Leaf Area Index (LAI) were also monitored with an adequate frequency. This paper presents the main results from both experiments. In particular, the main L-MEB parameters that characterize these two significant Mediterranean Ecosystem species have been computed and evaluated for soil moisture retrieval purposes in the framework of the imminent SMOS over land measurements. References Lopez-Baeza, E. et al. (2207): Validation of SMOS Products over Mediterranean Ecosystem Vegetation at the Valencia Anchor Station Reference Area. ESA SMOS Cal/Val Announcement of Opportunities (ID 3252). P.I.: E. Lopez-Baeza Wigneron J-P, Y. Kerr, P. Waldteufel, K. Saleh, M.-J. Escorihuela, P. Richaume, P. Ferrazzoli, P. de Rosnay, R. Gurney, J.-C. Calvet, J.P. Grant, M. Guglielmetti, B. Hornbuckle, C. Mätzler, T. Pellarin, M. Schwank (2007): L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields, Remote Sens. Env., 107, p. 639-655, 2007

Summary of Meteorological Observations, Surface (SMOS), for Atsugi, Japan.

DTIC Science & Technology

1985-03-01

s. * .5- 4 -- - - ---- ------- .. . - - ~- . . .. -...-.------- --- -. ____ 1.---±.k4 .... _ _ __ . .- -± ----.---. ... ..-- - .. .. hh ...81.5’ 88.6’ 0.2.2? 9 4.7’ 96.’. 97? 97Q 97.9 979 9997.9 97.97 700 9𔄀a~-1- j 3 A. 95.7 .4*5 98. 9 8 9 , 9 9 . 9 a. 60 Jb 4 C 2 7R.3 r1.9! 89.7 󈧯...3 4 671. 2 ’ -0 1 - 2[6 1 , . ’, l7 :" 18 - 2012 . 22T23 24I 25 2627-2 , 29. 30 31 ’D B w e ’,, BJb W.,8.b D.D P..t ] ,3, el- l4-- - --.i .1

Summary of Meteorological Observations, Surface (SMOS), Imperial Beach, California.

DTIC Science & Technology

1983-10-01

67.5 67o5 67.5 67.5 67.o b7.6j 67.6 tIso0 46. bl6 64*6 65.8 66.9 67.1 67.o4 67.5 67.5 67.5 b7.5 b7!) 67.5 67.; b7.s 67,) 2t16M ’:I b±.b 6 1.6 65. 6ba, 67...be( 590 0.1o bo 50.6 i 6~ 1.4 51.4 51.6 61.61 51.6 51.$651. b16 51. ;- 2000 20.9 54.7 56.$619 51 051. 63.7 64.l 54.3 6*3 54.5 64.5 54.5 5407 5,4.:? bE

Summary of Meteorological Observations, Surface (SMOS) for Diego Garcia

DTIC Science & Technology

1989-04-01

01 ,L A L c acca , 0O𔃺 0O 0: 1- U 0I 0IDJ - cc C aj Go w Go )co 000) Goaaa a0 7 ,0, 0101 a,01 0 ’C a W I u ( 011 -.) U 0 mN 010 0 n00mmwonr -ma w...0 0 f𔃺 0 0’ al z I - -. 3 -:)~.~30 . f3 333 3 U.5 . a:-- - P t0 OP-fJU)L -C )0 I 7 ar r- OD’)’J. CID-0 C’~ 0~ OOO 00’I DC)C o c 4 0 O O O ’ Q- I tu...rnu0 - U. CZ. - 00 00 0 3 t0 tr- OD00 C3N rZ303 M A0 ’ O 0 0’ 0 C,0 ,0 ’A/ U.1 D I 3’ ’r10 0 0 0 O O ,n 0 1-U.iU DA 0- f G D0 0 r- GO010 rNl U f3 ~ .3

Summary of Meteorological Observations, Surface (SMOS) Beaufort, South Carolina.

DTIC Science & Technology

1984-08-01

WATHER N 0? 33 SOO -___ 22$ 75 2ses _1590 NNE 303 *.q lt 17.6 9.9 *7.3 3.1 NE 5*P J.__ 1.? 13.8 $.4 39.7 1 3.9 ENE 1*$ ..s _____7_ 129S S9 55.4 25.0... WATHER SERVC[ OETACHMENT DAILY AVERAGE/EXTREME TEMPERATURES ASHEVILLE. N’ORTH CAROLINA AIP ft 1A o £VrIB*OI ~ mAWSMO £WiIlS O.I OA9 ’C 0 066 0*__ _ 0

Summary of Meteorological Observations, Surface (SMOS) for Keflavik, Iceland

DTIC Science & Technology

1989-04-01

is not considered obstruction to vision for purposes of this summary; therefore, the percentage total of obstructions to vis need not reflect the total...1 .J . I0 . . 1 0 .0 .c IC 10 .5 CLP .’ .C .0 . : . .0 C0 1.2 .0 AL 3I.4 331. 3 2%. 1 ’* A$. p~t r~ r Iro C0 I03’. 2 T VI AL N. (3 0~A 10 t 42 p f W...55w ’LI. • b VI "w" Jut NOUN :0 n0 Lk 1 ):51 )il /4Il6 : J ): r , 7(2. 20.6 72.1 20.7 70.7 ,’ 7 1. 21.6 7.1 7 II-? 71.1 .S 22.( 22.6 72.7 27.7 72

Summary of Meteorological Observations, Surface (SMOS) for Misawa, Japan.

DTIC Science & Technology

1985-03-01

SPECLIAL DATE ACCESSIONED DISTRIBUTION STAMP _ _ _ _ _ _ _DATE RETURNED 85 3 25 098 DATE RBCEIE IN DK REGISTERED OR CERTIFIED NO. PIT OGRAPH THS IBMT AMD...SPIED .1MEAN tINTS) I .3 4 7 10 11 16 17 21I 22 27 20 33 34 40 41 47 48 55 ~ 56 % WINO pit SPEED TE ± ---- -. ---- -- - - --------- SIR 4_4. WSW Sw L.1...8217 IT. 4 ____ 2. nnnm ~ ___nn ___mlln u .unm m _ - 1. 4.1 WNW 1e__ 3 1 VASILi - CALMA >ɚ ____ _ 1____ 2 2 ,3 Z. 1 .3 b- TOTAL NUMIN OF OSSEt VATIO#46

Improving River Flow Predictions from the NOAA NCRFC Forecasting Model by Incorporating Satellite Observations

NASA Astrophysics Data System (ADS)

Tuttle, S. E.; Jacobs, J. M.; Restrepo, P. J.; Deweese, M. M.; Connelly, B.; Buan, S.

2016-12-01

The NOAA National Weather Service North Central River Forecast Center (NCRFC) is responsible for issuing river flow forecasts for parts of the Upper Mississippi, Great Lakes, and Hudson Bay drainages, including the Red River of the North basin (RRB). The NCRFC uses an operational hydrologic modeling infrastructure called the Community Hydrologic Prediction System (CHPS) for its operational forecasts, which currently links the SNOW-17 snow accumulation and ablation model, to the Sacramento-Soil Moisture Accounting (SAC-SMA) rainfall-runoff model, to a number of hydrologic and hydraulic flow routing models. The operational model is lumped and requires only area-averaged precipitation and air temperature as inputs. NCRFC forecasters use observational data of hydrological state variables as a source of supplemental information during forecasting, and can use professional judgment to modify the model states in real time. In a few recent years (e.g. 2009, 2013), the RRB exhibited unexpected anomalous hydrologic behavior, resulting in overestimation of peak flood discharge by up to 70% and highlighting the need for observations with high temporal and spatial coverage. Unfortunately, observations of hydrological states (e.g. soil moisture, snow water equivalent (SWE)) are relatively scarce in the RRB. Satellite remote sensing can fill this need. We use Minnesota's Buffalo River watershed within the RRB as a test case and update the operational CHPS model using modifications based on satellite observations, including AMSR-E SWE and SMOS soil moisture estimates. We evaluate the added forecasting skill of the satellite-enhanced model compared to measured streamflow using hindcasts from 2010-2013.

Arctic sea ice signatures: L-band brightness temperature sensitivity comparison using two radiation transfer models

NASA Astrophysics Data System (ADS)

Richter, Friedrich; Drusch, Matthias; Kaleschke, Lars; Maaß, Nina; Tian-Kunze, Xiangshan; Mecklenburg, Susanne

2018-03-01

Sea ice is a crucial component for short-, medium- and long-term numerical weather predictions. Most importantly, changes of sea ice coverage and areas covered by thin sea ice have a large impact on heat fluxes between the ocean and the atmosphere. L-band brightness temperatures from ESA's Earth Explorer SMOS (Soil Moisture and Ocean Salinity) have been proven to be a valuable tool to derive thin sea ice thickness. These retrieved estimates were already successfully assimilated in forecasting models to constrain the ice analysis, leading to more accurate initial conditions and subsequently more accurate forecasts. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems, reducing the data latency and providing a more consistent first guess. As a first step towards such a data assimilation system we studied the forward operator that translates geophysical parameters provided by a model into brightness temperatures. We use two different radiative transfer models to generate top of atmosphere brightness temperatures based on ORAP5 model output for the 2012/2013 winter season. The simulations are then compared against actual SMOS measurements. The results indicate that both models are able to capture the general variability of measured brightness temperatures over sea ice. The simulated brightness temperatures are dominated by sea ice coverage and thickness changes are most pronounced in the marginal ice zone where new sea ice is formed. There we observe the largest differences of more than 20 K over sea ice between simulated and observed brightness temperatures. We conclude that the assimilation of SMOS brightness temperatures yields high potential for forecasting models to correct for uncertainties in thin sea ice areas and suggest that information on sea ice fractional coverage from higher-frequency brightness temperatures should be used simultaneously.

Dense Gas-Star Systems: Evolution of Supermassive Stars

NASA Astrophysics Data System (ADS)

Amaro-Seoane, P.; Spurzem, R.

In the 60s and 70s super-massive central objects (from now onwards SMOs) were thought to be the main source of active galactic nuclei (AGNs) characteristics (luminosities of L ≅1012 Lodot). The release of gravitational binding energy by the accretion of material on to an SMO in the range of 107 - 109 Modot has been suggested to be the primary powerhouse (Lynden-Bell 1969). That rather exotic idea in early time has become common sense nowadays. Not only our own galaxy harbours a few million-solar mass black hole (Genzel 2001) but also many of other non-active galaxies show kinematic and gas-dynamic evidence of these objects (Magorrian et al. 1998) The concept of central super-massive stars (SMSs henceforth) (cal M ≥ 5 × 104 Modot, where cal M is the mass of the SMS) embedded in dense stellar systems was suggested as a possible explanation for high- energy emissions phenomena occurring in AGNs and quasars (Vilkoviski 1976, Hara 1978), such as X-ray emissions (Bahcall and Ostriker, 1975). SMSs and super-massive black holes (SMBHs) are two possibilities to explain the nature of SMOs, and SMSs may be an intermediate step towards the formation of SMBHs (Rees 1984). In this paper we give the equations that describe the dynamics of such a dense star-gas system which are the basis for the code that will be used in a prochain future to simulate this scenario. We also briefly draw the mathematical fundamentals of the code.

Sensitivity Observing System Experiment (SOSE)-a new effective NWP-based tool in designing the global observing system

NASA Astrophysics Data System (ADS)

Marseille, Gert-Jan; Stoffelen, Ad; Barkmeijer, Jan

2008-03-01

Lacking an established methodology to test the potential impact of prospective extensions to the global observing system (GOS) in real atmospheric cases we developed such a method, called Sensitivity Observing System Experiment (SOSE). For example, since the GOS is non uniform it is of interest to investigate the benefit of complementary observing systems filling its gaps. In a SOSE adjoint sensitivity structures are used to define a pseudo true atmospheric state for the simulation of the prospective observing system. Next, the synthetic observations are used together with real observations from the existing GOS in a state-of-the-art Numerical Weather Prediction (NWP) model to assess the potential added value of the new observing system. Unlike full observing system simulation experiments (OSSE), SOSE can be applied to real extreme events that were badly forecast operationally and only requires the simulation of the new instrument. As such SOSE is an effective tool, for example, to define observation requirements for extensions to the GOS. These observation requirements may serve as input for the design of an operational network of prospective observing systems. In a companion paper we use SOSE to simulate potential future space borne Doppler Wind Lidar (DWL) scenarios and assess their capability to sample meteorologically sensitive areas not well captured by the current GOS, in particular over the Northern Hemisphere oceans.

Jupiter System Observer

NASA Technical Reports Server (NTRS)

Senske, Dave; Kwok, Johnny

2008-01-01

This slide presentation reviews the proposed mission for the Jupiter System Observer. The presentation also includes overviews of the mission timeline, science goals, and spacecraftspecifications for the satellite.

Observing System Evaluations Using GODAE Systems

DTIC Science & Technology

2009-09-01

DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release, distribution is unlimite 13. SUPPLEMENTARY NOTES 20091228151 14. ABSTRACT Global ocean...forecast systems, developed under the Global Ocean Data Assimilation Experiment (GODAE), are a powerful means of assessing the impact of different...components of the Global Ocean Observing System (GOOS). Using a range of analysis tools and approaches, GODAE systems are useful for quantifying the

Synthetic observations of protostellar multiple systems

NASA Astrophysics Data System (ADS)

Lomax, O.; Whitworth, A. P.

2018-04-01

Observations of protostars are often compared with synthetic observations of models in order to infer the underlying physical properties of the protostars. The majority of these models have a single protostar, attended by a disc and an envelope. However, observational and numerical evidence suggests that a large fraction of protostars form as multiple systems. This means that fitting models of single protostars to observations may be inappropriate. We produce synthetic observations of protostellar multiple systems undergoing realistic, non-continuous accretion. These systems consist of multiple protostars with episodic luminosities, embedded self-consistently in discs and envelopes. We model the gas dynamics of these systems using smoothed particle hydrodynamics and we generate synthetic observations by post-processing the snapshots using the SPAMCART Monte Carlo radiative transfer code. We present simulation results of three model protostellar multiple systems. For each of these, we generate 4 × 104 synthetic spectra at different points in time and from different viewing angles. We propose a Bayesian method, using similar calculations to those presented here, but in greater numbers, to infer the physical properties of protostellar multiple systems from observations.

The Earth Observing System

NASA Technical Reports Server (NTRS)

Shaffer, Lisa Robock

1992-01-01

The restructuring of the NASA Earth Observing System (EOS), designed to provide comprehensive long term observations from space of changes occurring on the Earth from natural and human causes in order to have a sound scientific basis for policy decisions on protection of the future, is reported. In response to several factors, the original program approved in the fiscal year 1991 budget was restructured and somewhat reduced in scope. The resulting program uses three different sized launch vehicles to put six different spacecraft in orbit in the first phase, followed by two replacement launches for each of five of the six satellites to maintain a long term observing capability to meet the needs of global climate change research and other science objectives. The EOS system, including the space observatories, the data and information system, and the interdisciplinary global change research effort, are approved and proceeding. Elements of EOS are already in place, such as the research investigations and initial data system capabilities. The flights of precursor satellite and Shuttle missions, the ongoing data analysis, and the evolutionary enhancements to the integrated Earth science data management capabilities are all important building blocks to the full EOS program.

Modeling of the dielectric permittivity of porous soil media with water using statistical-physical models

NASA Astrophysics Data System (ADS)

Usowicz, Boguslaw; Marczewski, Wojciech; Usowicz, Jerzy B.; Łukowski, Mateusz; Lipiec, Jerzy; Stankiewicz, Krystyna

2013-04-01

Radiometric observations with SMOS rely on the Radiation Transfer Equations (RTE) determining the Brightness Temperature (BT) in two linear polarization components (H, V) satisfying Fresnel principle of propagation in horizontally layered target media on the ground. RTE involve variables which bound the equations expressed in Electro-Magnetic (EM) terms of the intensity BT to the physical reality expressed by non-EM variables (Soil Moisture (SM), vegetation indexes, fractional coverage with many different properties, and the boundary conditions like optical thickness, layer definitions, roughness, etc.) bridging the EM domain to other physical aspects by means of the so called tau-omega methods. This method enables joining variety of different valuable models, including specific empirical estimation of physical properties in relation to the volumetric water content. The equations of RTE are in fact expressed by propagation, reflection and losses or attenuation existing on a considered propagation path. The electromagnetic propagation is expressed in the propagation constant. For target media on the ground the dielectric constant is a decisive part for effects of propagation. Therefore, despite of many various physical parameters involved, one must effectively and dominantly rely on the dielectric constant meant as a complex variable. The real part of the dielectric constant represents effect of apparent shortening the propagation path and the refraction, while the imaginary part is responsible for the attenuation or losses. This work engages statistical-physical modeling of soil properties considering the media as a mixture of solid grains, and gas or liquid filling of pores and contact bridges between compounds treated statistically. The method of this modeling provides an opportunity of characterizing the porosity by general statistical means, and is applicable to various physical properties (thermal, electrical conductivity and dielectric properties) which

Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Barella-Ortiz, Anaïs; Polcher, Jan; de Rosnay, Patricia; Piles, Maria; Gelati, Emiliano

2017-01-01

L-band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture (SSM) by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm which yields SSM estimates. The work exposed compares brightness temperatures measured by the SMOS mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The two modelled sets were estimated using a radiative transfer model and state variables from two land-surface models: (i) ORCHIDEE and (ii) H-TESSEL. The radiative transfer model used is the CMEM. Measured and modelled brightness temperatures show a good agreement in their temporal evolution, but their spatial structures are not consistent. An empirical orthogonal function analysis of the brightness temperature's error identifies a dominant structure over the south-west of the Iberian Peninsula which evolves during the year and is maximum in autumn and winter. Hypotheses concerning forcing-induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for the weak spatial correlations at the moment. Further hypotheses are proposed and will be explored in a forthcoming paper. The analysis of spatial inconsistencies between modelled and measured TBs is important, as these can affect the estimation of geophysical variables and TB assimilation in operational models, as well as result in misleading validation studies.

Autonomous aerial observations to extend and complement the Earth Observing System: a science-driven systems-oriented approach

NASA Astrophysics Data System (ADS)

Sandford, Stephen P.; Harrison, F. W.; Langford, John; Johnson, James W.; Qualls, Garry; Emmitt, David; Jones, W. Linwood; Shugart, Herman H., Jr.

2004-12-01

The current Earth observing capability depends primarily on spacecraft missions and ground-based networks to provide the critical on-going observations necessary for improved understanding of the Earth system. Aircraft missions play an important role in process studies but are limited to relatively short-duration flights. Suborbital observations have contributed to global environmental knowledge by providing in-depth, high-resolution observations that space-based and in-situ systems are challenged to provide; however, the limitations of aerial platforms - e.g., limited observing envelope, restrictions associated with crew safety and high cost of operations have restricted the suborbital program to a supporting role. For over a decade, it has been recognized that autonomous aerial observations could potentially be important. Advances in several technologies now enable autonomous aerial observation systems (AAOS) that can provide fundamentally new observational capability for Earth science and applications and thus lead scientists and engineers to rethink how suborbital assets can best contribute to Earth system science. Properly developed and integrated, these technologies will enable new Earth science and operational mission scenarios with long term persistence, higher-spatial and higher-temporal resolution at lower cost than space or ground based approaches. This paper presents the results of a science driven, systems oriented study of broad Earth science measurement needs. These needs identify aerial mission scenarios that complement and extend the current Earth Observing System. These aerial missions are analogous to space missions in their complexity and potential for providing significant data sets for Earth scientists. Mission classes are identified and presented based on science driven measurement needs in atmospheric, ocean and land studies. Also presented is a nominal concept of operations for an AAOS: an innovative set of suborbital assets that

The Global Ocean Observing System

NASA Technical Reports Server (NTRS)

Kester, Dana

1992-01-01

A Global Ocean Observing System (GOOS) should be established now with international coordination (1) to address issues of global change, (2) to implement operational ENSO forecasts, (3) to provide the data required to apply global ocean circulation models, and (4) to extract the greatest value from the one billion dollar investment over the next ten years in ocean remote sensing by the world's space agencies. The objectives of GOOS will focus on climatic and oceanic predictions, on assessing coastal pollution, and in determining the sustainability of living marine resources and ecosystems. GOOS will be a complete system including satellite observations, in situ observations, numerical modeling of ocean processes, and data exchange and management. A series of practical and economic benefits will be derived from the information generated by GOOS. In addition to the marine science community, these benefits will be realized by the energy industries of the world, and by the world's fisheries. The basic oceanic variables that are required to meet the oceanic and predictability objectives of GOOS include wind velocity over the ocean, sea surface temperature and salinity, oceanic profiles of temperature and salinity, surface current, sea level, the extent and thickness of sea ice, the partial pressure of CO2 in surface waters, and the chlorophyll concentration of surface waters. Ocean circulation models and coupled ocean-atmosphere models can be used to evaluate observing system design, to assimilate diverse data sets from in situ and remotely sensed observations, and ultimately to predict future states of the system. The volume of ocean data will increase enormously over the next decade as new satellite systems are launched and as complementary in situ measuring systems are deployed. These data must be transmitted, quality controlled, exchanged, analyzed, and archived with the best state-of-the-art computational methods.

Evaluation of three different data fusion approaches that uses satellite soil moisture from different passive microwave sensors to construct one consistent climate record

NASA Astrophysics Data System (ADS)

van der Schalie, Robin; de Jeu, Richard; Kerr, Yann; Wigneron, Jean-Pierre; Rodríguez-Fernández, Nemesio; Al-Yaari, Amen; Drusch, Matthias; Mecklenburg, Susanne; Dolman, Han

2016-04-01

Datasets that are derived from satellite observations are becoming increasingly important for measuring key parameters of the Earth's climate and are therefore crucial in research on climate change, giving the opportunity to researchers to detect anomalies and long-term trends globally. One of these key parameters is soil moisture (SM), which has a large impact on water, energy and biogeochemical cycles worldwide. A long-term SM data record from active and passive microwave satellite observations was developed as part of ESA's Climate Change Initiative (ESA-CCI-SM, http://www.esa-soilmoisture-cci.org/). Currently the dataset covers a period from 1978 to 2014 and is updated regularly, observations from a several microwave satellites including: ERS-1, ERS-2, METOP-A, Nimbus 7 SMMR, DMSP SSM/I, TRMM TMI, Aqua AMSRE, Coriolis WindSat, and GCOM-W1 AMSR2. In 2009, ESA launched the Soil Moisture and Ocean Salinity (SMOS, Kerr et al., 2010) mission, carrying onboard a unique L-band radiometer, but its SM retrievals are not yet part of this dataset. Due to the different radiometric characteristics of SMOS, integrating SMOS into the ESA-CCI-SM dataset is not straight forward. Therefore several approaches have been tested to fuse soil moisture retrievals from SMOS and AMSRE, which currently forms the basis of the passive microwave part within ESA-CCI-SM project. These approaches are: 1. A Neural Network Fusion approach (Rodríguez-Fernández et al., 2015), 2. A regression approach (Wigneron et al., 2004; Al-Yaari et al., 2015) and 3. A radiative transfer based approach, using the Land Parameter Retrieval Model (Van der Schalie et al., 2016). This study evaluates the three different approaches and tests their skills against multiple datasets, including MERRA-Land, ERA-Interim/Land, the current ESA-CCI-SM v2.2 and in situ measurements from the International Soil Moisture Network and present a recommendation for the potential integration of SMOS soil moisture into the ESA

Operable Data Management for Ocean Observing Systems

NASA Astrophysics Data System (ADS)

Chavez, F. P.; Graybeal, J. B.; Godin, M. A.

2004-12-01

As oceanographic observing systems become more numerous and complex, data management solutions must follow. Most existing oceanographic data management systems fall into one of three categories: they have been developed as dedicated solutions, with limited application to other observing systems; they expect that data will be pre-processed into well-defined formats, such as netCDF; or they are conceived as robust, generic data management solutions, with complexity (high) and maturity and adoption rates (low) to match. Each approach has strengths and weaknesses; no approach yet fully addresses, nor takes advantage of, the sophistication of ocean observing systems as they are now conceived. In this presentation we describe critical data management requirements for advanced ocean observing systems, of the type envisioned by ORION and IOOS. By defining common requirements -- functional, qualitative, and programmatic -- for all such ocean observing systems, the performance and nature of the general data management solution can be characterized. Issues such as scalability, maintaining metadata relationships, data access security, visualization, and operational flexibility suggest baseline architectural characteristics, which may in turn lead to reusable components and approaches. Interoperability with other data management systems, with standards-based solutions in metadata specification and data transport protocols, and with the data management infrastructure envisioned by IOOS and ORION, can also be used to define necessary capabilities. Finally, some requirements for the software infrastructure of ocean observing systems can be inferred. Early operational results and lessons learned, from development and operations of MBARI ocean observing systems, are used to illustrate key requirements, choices, and challenges. Reference systems include the Monterey Ocean Observing System (MOOS), its component software systems (Software Infrastructure and Applications for MOOS, and

Observing system simulation experiments with multiple methods

NASA Astrophysics Data System (ADS)

Ishibashi, Toshiyuki

2014-11-01

An observing System Simulation Experiment (OSSE) is a method to evaluate impacts of hypothetical observing systems on analysis and forecast accuracy in numerical weather prediction (NWP) systems. Since OSSE requires simulations of hypothetical observations, uncertainty of OSSE results is generally larger than that of observing system experiments (OSEs). To reduce such uncertainty, OSSEs for existing observing systems are often carried out as calibration of the OSSE system. The purpose of this study is to achieve reliable OSSE results based on results of OSSEs with multiple methods. There are three types of OSSE methods. The first one is the sensitivity observing system experiment (SOSE) based OSSE (SOSEOSSE). The second one is the ensemble of data assimilation cycles (ENDA) based OSSE (ENDA-OSSE). The third one is the nature-run (NR) based OSSE (NR-OSSE). These three OSSE methods have very different properties. The NROSSE evaluates hypothetical observations in a virtual (hypothetical) world, NR. The ENDA-OSSE is very simple method but has a sampling error problem due to a small size ensemble. The SOSE-OSSE requires a very highly accurate analysis field as a pseudo truth of the real atmosphere. We construct these three types of OSSE methods in the Japan meteorological Agency (JMA) global 4D-Var experimental system. In the conference, we will present initial results of these OSSE systems and their comparisons.

Surface Soil Moisture Estimates Across China Based on Multi-satellite Observations and A Soil Moisture Model

NASA Astrophysics Data System (ADS)

Zhang, Ke; Yang, Tao; Ye, Jinyin; Li, Zhijia; Yu, Zhongbo

2017-04-01

Soil moisture is a key variable that regulates exchanges of water and energy between land surface and atmosphere. Soil moisture retrievals based on microwave satellite remote sensing have made it possible to estimate global surface (up to about 10 cm in depth) soil moisture routinely. Although there are many satellites operating, including NASA's Soil Moisture Acitive Passive mission (SMAP), ESA's Soil Moisture and Ocean Salinity mission (SMOS), JAXA's Advanced Microwave Scanning Radiometer 2 mission (AMSR2), and China's Fengyun (FY) missions, key differences exist between different satellite-based soil moisture products. In this study, we applied a single-channel soil moisture retrieval model forced by multiple sources of satellite brightness temperature observations to estimate consistent daily surface soil moisture across China at a spatial resolution of 25 km. By utilizing observations from multiple satellites, we are able to estimate daily soil moisture across the whole domain of China. We further developed a daily soil moisture accounting model and applied it to downscale the 25-km satellite-based soil moisture to 5 km. By comparing our estimated soil moisture with observations from a dense observation network implemented in Anhui Province, China, our estimated soil moisture results show a reasonably good agreement with the observations (RMSE < 0.1 and r > 0.8).

The Global Observing System in the Assimilation Context

NASA Technical Reports Server (NTRS)

Reinecker, Michele M.; Gelaro, R.; Pawson, S.; Reichle, R.; McCarty, W.

2011-01-01

Weather and climate analyses and predictions all rely on the global observing system. However, the observing system, whether atmosphere, ocean, or land surface, yields a diverse set of incomplete observations of the different components of Earth s environment. Data assimilation systems are essential to synthesize the wide diversity of in situ and remotely sensed observations into four-dimensional state estimates by combining the various observations with model-based estimates. Assimilation, or associated tools and products, are also useful in providing guidance for the evolution of the observing system of the future. This paper provides a brief overview of the global observing system and information gleaned through assimilation tools, and presents some evaluations of observing system gaps and issues.

Summary of Meteorological Observations, Surface (SMOS) for Moffett Field, California

DTIC Science & Technology

1988-12-01

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Summary of Meteorological Observations, Surface (SMOS), Santa Ana, California/Tustin

DTIC Science & Technology

1983-10-01

STATOR " All" SARK T1AM MONT. ALL -LATHE7 ir CLAS %l as (’.8+T. (KNIS) 1.3 4.4 7.10 11.16 17.21 22.27 23•331 34 -40 41.47 48 ,S >56 % WIND cmSL SPEED...me .I -o - -1L .I,. * 3- 0o 0o I07. 3mNM sl 2 -e -OS -o -. 0 S beC ?3+ 1.9+ * 11o2 6.r. VAN ’ iC1U M q ll 1., 1m, 1M 1EW M1,ol 03 3 3o 310, w mo8e1... 2006 79.5 26.4 lO 400C 1961 58.7 11,8 52 11.1 1963 4 ,9.0 2006 79.0 26.1 96 35.6 1981 59.1 15.1 51 10.6 194.7 5 6609 20.5 77.2 25.1 5Q 31,.7T 1961 60.06

Summary of Meteorological Observations, Surface (SMOS) for Providence, Rhode Island

DTIC Science & Technology

1988-12-01

4 0 0 1 -go 5 0 V IV4 0 %.. - 0 N 5.0 10-. c. N 0 0 -i 030 N p - S 0 r- > 0o o .. 5.. s . N ) 0. & 1. I 0 4,0 C ) " "i 025 - 4 C. .4, S.’ 100 *3 t...4 . 03- 6 p4 2-4 t4’ 0O46)4 >. 00 00~ 0 U $.- 100 -. ".1. 4 0 100 0.0 1 ol5~ 0 0 d d 0. 0 >o0 040 ~. 03- 1 46 - .OpA. I)01 F.p 0)’ > 4) Ol ti 4 0 r...82170 124)4) 9.0 t. 16id4 0 0 𔃺 IV 0 w241 -Pto to16 06 .4’ r16 0.4r 04’ 12a 0 X1c2 1 12.0 0 P. .0 -P 0 100 0 16 0 >’ V0 C’.0 4) 𔃺.0 0 C𔃾-4-0 0. 202r

Understanding the Dynamics of the South Indian Ocean Sea Surface Salinity Maximum Pool From Argo, Rama, Aquarius, SMOS & Other Satellites

NASA Astrophysics Data System (ADS)

Menezes, V. V.; Phillips, H. E.

2016-02-01

Subtropical salinity maximum regions are particularly important because the salty subtropical underwater (STW) is formed by subduction of surface waters in these areas. In all oceans, the STW is transported equatorward from the formation region and are tightly related to the Subtropical-Tropical Cell. In the South Indian Ocean (SIO), the salinity maximum pool is further poleward (25S-38S) and eastward (60E-120E). It significantly impacts the circulation of the eastern basin, because the STW forms a strong haline front with the fresh Indonesian Throughflow waters. This haline front overwhelms the temperature contribution establishing the eastward Eastern Gyral Current, an important upstream source for the Leeuwin Current. In the present work, we analyze the variability of the SSS maximum pool using Aquarius and SMOS satellites, an Argo gridded product and the RAMA mooring located at 25S-100E. OAFLUX, 3B42 TRMM, Ascat/Quikscat winds and OSCAR products complement this study. The salinity maximum pool has a strong seasonal cycle of contraction (min in Oct) and expansion (max in April), and most of this variation occurs in the pool poleward side. Advection and entrainment control the contraction, while expansion is due to atmospheric forcing (E-P). From 2004 to 2014, a clear reduction in the pool area is identified, which might be related to a decadal variability. In this case, the variation is in the equatorward side of the pool. Processes controlling this long-term variability are being investigated.

The Ups and Downs of Measuring Sea Surface Salinity from Space

NASA Astrophysics Data System (ADS)

Banks, C. J.; Gommenginger, C. P.; Srokosz, M. A.; Snaith, H. M.

2012-12-01

In November 2009, the European Space Agency (ESA) launched the Soil Moisture and Ocean Salinity (SMOS) satellite and a new era of satellite oceanography began vastly improving our ability to synoptically measure sea surface salinity (SSS). SMOS was joined in June 2011 by the NASA/Argentine Aquarius/SAC-D mission designed specifically to measure SSS. Although there are significant differences in how both satellites retrieve SSS, both utilise passive systems to measure the response of the brightness temperature (Tb) at L-band (1.4 GHz). We report on-going investigations into the validation of SMOS and Aquarius 'Level 3' measurements of SSS using monthly data on a 1° by 1° global grid between 60°S and 60°N. Previous studies have indicated significant temporally varying differences between SSS from SMOS ascending passes and from SMOS descending passes: therefore, for both SMOS and Aquarius, data from ascending and descending passes will be studied separately. Both satellites have sun-synchronous orbits but the direction of travel for the two satellites are twelve hours out of phase (i.e. at approximately 6 a.m. local time SMOS is travelling south-to-north (ascending) and Aquarius is travelling north-to-south (descending) whereas at 6 p.m. the directions of travel are switched). For validation purposes two separate monthly, 1° by 1° datasets are used over the same locations as the satellite data. The first is based on averaged near-surface salinity (depth less than 10 m) as derived from the drifting Argo float programme. The second validation data source is output from the UK Met Office Forecasting Ocean Assimilation Model (FOAM) based on NEMO (Nucleus for European Modelling of the Ocean). The SMOS Level 3 products are developed from ESA Level 2 products after quality control (QC) based on flags and SSS error provided in the ESA Level 2 products. Aquarius data (QC) is based only on data flags and a simple selection of in-range SSS values ([30, 40]). The study is

GEOS observation systems intercomparison investigation results

NASA Technical Reports Server (NTRS)

Berbert, J. H.

1974-01-01

The results of an investigation designed to determine the relative accuracy and precision of the different types of geodetic observation systems used by NASA is presented. A collocation technique was used to minimize the effects of uncertainties in the relative station locations and in the earth's gravity field model by installing accurate reference tracking systems close to the systems to be compared, and by precisely determining their relative survey. The Goddard laser and camera systems were shipped to selected sites, where they tracked the GEOS satellite simultaneously with other systems for an intercomparison observation.

Observing System Simulation Experiments

NASA Technical Reports Server (NTRS)

Prive, Nikki

2015-01-01

This presentation gives an overview of Observing System Simulation Experiments (OSSEs). The components of an OSSE are described, along with discussion of the process for validating, calibrating, and performing experiments. a.

L-band radiometry for sea ice applications

NASA Astrophysics Data System (ADS)

Heygster, G.; Hedricks, S.; Mills, P.; Kaleschke, L.; Stammer, D.; Tonboe, R.

2009-04-01

Although sea ice remote sensing has reached the level of operational exploitation with well established retrieval methods, several important tasks are still unsolved. In particular during freezing and melting periods with mixed ice and water surfaces, estimates of ice concentration with passive and active microwave sensors remain challenging. Newly formed thin ice is also hard to distinguish from open water with radiometers for frequencies above 8 GHz. The SMOS configuration (planned launch 2009) with a radiometer at 1.4 GHz is a promising technique to complement observations at higher microwave frequencies. ESA has initiated a project to investigate the possibilities for an additional Level-2 sea ice data product based on SMOS. In detail, the project objectives are (1) to model the L band emission of sea ice, and to assess the potential (2) to retrieve sea ice parameters, especially concentration and thickness, and (3) to use cold water regions for an external calibration of SMOS. Modelling of L band emission: Several models have are investigated. All of them work on the same basic principles and have a vertically-layered, plane-parallel geometry. They are comprised of three basic components: (1) effective permittivities are calculated for each layer based on ice bulk and micro-structural properties; (2) these are integrated across the total depth to derive emitted brightness temperature; (3) scattering terms can also be added because of the granular structure of ice and snow. MEMLS (Microwave Emission Model of Layered Snowpacks (Wiesmann and Matzler 1999)) is one such model that contains all three elements in a single Matlab program. In the absence of knowledge about the internal structure of the sea ice, three-layer (air, ice and water) dielectric slab models which take as input a single effective permittivity for the ice layer are appropriate. By ignoring scattering effects one can derive a simple analytic expression for a dielectric slab as shown by Apinis and

Solar System Observations with JWST

NASA Technical Reports Server (NTRS)

Norwood, James; Hammel, Heidi; Milam, Stefanie; Stansberry, John; Lunine, Jonathan; Chanover, Nancy; Hines, Dean; Sonneborn, George; Tiscareno, Matthew; Brown, Michael;

Multi-site assimilation of a terrestrial biosphere model (BETHY) using satellite derived soil moisture data

NASA Astrophysics Data System (ADS)

Wu, Mousong; Sholze, Marko

2017-04-01

We investigated the importance of soil moisture data on assimilation of a terrestrial biosphere model (BETHY) for a long time period from 2010 to 2015. Totally, 101 parameters related to carbon turnover, soil respiration, as well as soil texture were selected for optimization within a carbon cycle data assimilation system (CCDAS). Soil moisture data from Soil Moisture and Ocean Salinity (SMOS) product was derived for 10 sites representing different plant function types (PFTs) as well as different climate zones. Uncertainty of SMOS soil moisture data was also estimated using triple collocation analysis (TCA) method by comparing with ASCAT dataset and BETHY forward simulation results. Assimilation of soil moisture to the system improved soil moisture as well as net primary productivity(NPP) and net ecosystem productivity (NEP) when compared with soil moisture derived from in-situ measurements and fluxnet datasets. Parameter uncertainties were largely reduced relatively to prior values. Using SMOS soil moisture data for assimilation of a terrestrial biosphere model proved to be an efficient approach in reducing uncertainty in ecosystem fluxes simulation. It could be further used in regional an global assimilation work to constrain carbon dioxide concentration simulation by combining with other sources of measurements.

Using Combined Marine Spatial Planning Tools and Observing System Experiments to define Gaps in the Emerging European Ocean Observing System.

NASA Astrophysics Data System (ADS)

Nolan, G.; Pinardi, N.; Vukicevic, T.; Le Traon, P. Y.; Fernandez, V.

2016-02-01

Ocean observations are critical to providing accurate ocean forecasts that support operational decision making in European open and coastal seas. Observations are available in many forms from Fixed platforms e.g. Moored Buoys and tide gauges, underway measurements from Ferrybox systems, High Frequency radars and more recently from underwater Gliders and profiling floats. Observing System Simulation Experiments have been conducted to examine the relative contribution of each type of platform to an improvement in our ability to accurately forecast the future state of the ocean with HF radar and Gliders showing particular promise in improving model skill. There is considerable demand for ecosystem products and services from today's ocean observing system and biogeochemical observations are still relatively sparse particularly in coastal and shelf seas. There is a need to widen the techniques used to assess the fitness for purpose and gaps in the ocean observing system. As well as Observing System Simulation Experiments that quantify the effect of observations on the overall model skill we present a gap analysis based on (1) Examining where high model skill is required based on a marine spatial planning analysis of European seas i.e where does activity take place that requires more accurate forecasts? and (2) assessing gaps based on the capacity of the observing system to answer key societal challenges e.g. site suitability for aquaculture and ocean energy, oil spill response and contextual oceanographic products for fisheries and ecosystems. The broad based analysis will inform the development of the proposed European Ocean Observing System as a contribution to the Global Ocean Observing System (GOOS).

Synthesis and Assimilation Systems - Essential Adjuncts to the Global Ocean Observing System

NASA Technical Reports Server (NTRS)

Rienecker, Michele M.; Balmaseda, Magdalena; Awaji, Toshiyuki; Barnier, Bernard; Behringer, David; Bell, Mike; Bourassa, Mark; Brasseur, Pierre; Breivik, Lars-Anders; Carton, James;

Spatial distribution of soil moisture obtained from gravimetric and TDR methods for SMOS validation, at the Polesie test site SVRT 3275, in Poland

NASA Astrophysics Data System (ADS)

Usowicz, B.; Marczewski, W.; Lipiec, J.; Usowicz, J. B.; Sokolowska, Z.; Dabkowska-Naskret, H.; Hajnos, M.; Lukowski, M. I.

2009-04-01

The purpose is obtaining trustful ground based measurement data of SM (Soil Moisture) for validating SMOS, respectively to spatial and temporal distribution and variations. A use of Time Domain Reflectometric (TDR) method is fast, simple and less destructive, to the soil matter, than a usual standard gravimetric method. TDR tools operate efficiently, enable nearly instant measurements, and allow on collecting many measurements from numerous sites, even when operated manually in short time intervals. The method enables also very frequent sampling of SM at few selected fixed sites, when long terms of temporal variations are needed. In effect one obtains reasonably large data base for determining spatial and temporal distributions of SM. The study is devoted to determining a plan on collecting TDR data, in the scales of small and large field areas, and checking their relevance to those available from gravimetric methods. Finally, the ground based SM distributions are needed for validating other SM distributions, available remotely in larger scales, from the satellite data of ENVISAT-ASAR, and from SMOS (Soil Moisture and Ocean Salinity Mission) when it becomes operational. The ground based evaluations are served mainly by geo-statistical analysis. The space borne estimations are retrieved by image processing and physical models, proper to relevant Remote Sensing (RS) instruments on the orbit. Finally, validation must engage again the geo-statistical evaluations, to assess the agreement between direct and remote sensing means, and provide a measure of trust for extending the limited scales of the ground based data, on concluding the agreement in scales proper to the satellite data. The study is focused mainly on trustful evaluating data from the ground, provided independently on satellite data sources. SM ground based data are collected permanently at 2 selected tests sites, and temporary in areas around the tests sites, in one day sessions, repeated several times per

NOAA Observing System Integrated Analysis (NOSIA): development and support to the NOAA Satellite Observing System Architecture

NASA Astrophysics Data System (ADS)

Reining, R. C.; Cantrell, L. E., Jr.; Helms, D.; LaJoie, M.; Pratt, A. S.; Ries, V.; Taylor, J.; Yuen-Murphy, M. A.

2016-12-01

There is a deep relationship between NOSIA-II and the Federal Earth Observation Assessment (EOA) efforts (EOA 2012 and 2016) chartered under the National Science and Technology Council, Committee on Environment, Natural Resources, and Sustainability, co-chaired by the White House Office of Science and Technology Policy, NASA, NOAA, and USGS. NOSIA-1, which was conducted with a limited scope internal to NOAA in 2010, developed the methodology and toolset that was adopted for EOA 2012, and NOAA staffed the team that conducted the data collection, modeling, and analysis effort for EOA 2012. EOA 2012 was the first-ever integrated analysis of the relative impact of 379 observing systems and data sources contributing to the key objectives identified for 13 Societal Benefit Areas (SBA) including Weather, Climate, Disasters, Oceans and Coastal Resources, and Water Resources. This effort culminated in the first National Plan for Civil Earth Observations. NOAA conducted NOSIA-II starting in 2012 to extend the NOSIA methodology across all of NOAA's Mission Service Areas, covering a representative sample (over 1000) of NOAA's products and services. The detailed information from NOSIA-II is being integrated into EOA 2016 to underpin a broad array of Key Products, Services, and (science) Objectives (KPSO) identified by the inter-agency SBA teams. EOA 2016 is expected to provide substantially greater insight into the cross-agency impacts of observing systems contributing to a wide array of KPSOs, and by extension, to societal benefits flowing from these public-facing products. NOSIA-II is being adopted by NOAA as a corporate decision-analysis and support capability to inform leadership decisions on its integrated observing systems portfolio. Application examples include assessing the agency-wide impacts of planned decommissioning of ships and aircraft in NOAA's fleet, and the relative cost-effectiveness of alternative space-based architectures in the post-GOES-R and JPSS era

Assimilation of gridded terrestrial water storage observations from GRACE into a land surface model

NASA Astrophysics Data System (ADS)

Girotto, Manuela; De Lannoy, Gabriëlle J. M.; Reichle, Rolf H.; Rodell, Matthew

2016-05-01

Observations of terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) satellite mission have a coarse resolution in time (monthly) and space (roughly 150,000 km2 at midlatitudes) and vertically integrate all water storage components over land, including soil moisture and groundwater. Data assimilation can be used to horizontally downscale and vertically partition GRACE-TWS observations. This work proposes a variant of existing ensemble-based GRACE-TWS data assimilation schemes. The new algorithm differs in how the analysis increments are computed and applied. Existing schemes correlate the uncertainty in the modeled monthly TWS estimates with errors in the soil moisture profile state variables at a single instant in the month and then apply the increment either at the end of the month or gradually throughout the month. The proposed new scheme first computes increments for each day of the month and then applies the average of those increments at the beginning of the month. The new scheme therefore better reflects submonthly variations in TWS errors. The new and existing schemes are investigated here using gridded GRACE-TWS observations. The assimilation results are validated at the monthly time scale, using in situ measurements of groundwater depth and soil moisture across the U.S. The new assimilation scheme yields improved (although not in a statistically significant sense) skill metrics for groundwater compared to the open-loop (no assimilation) simulations and compared to the existing assimilation schemes. A smaller impact is seen for surface and root-zone soil moisture, which have a shorter memory and receive smaller increments from TWS assimilation than groundwater. These results motivate future efforts to combine GRACE-TWS observations with observations that are more sensitive to surface soil moisture, such as L-band brightness temperature observations from Soil Moisture Ocean Salinity (SMOS) or Soil Moisture Active Passive

Assimilation of Gridded Terrestrial Water Storage Observations from GRACE into a Land Surface Model

NASA Technical Reports Server (NTRS)

Girotto, Manuela; De Lannoy, Gabrielle J. M.; Reichle, Rolf H.; Rodell, Matthew

2016-01-01

Observations of terrestrial water storage (TWS) from the Gravity Recovery and Climate Experiment (GRACE) satellite mission have a coarse resolution in time (monthly) and space (roughly 150,000 km(sup 2) at midlatitudes) and vertically integrate all water storage components over land, including soil moisture and groundwater. Data assimilation can be used to horizontally downscale and vertically partition GRACE-TWS observations. This work proposes a variant of existing ensemble-based GRACE-TWS data assimilation schemes. The new algorithm differs in how the analysis increments are computed and applied. Existing schemes correlate the uncertainty in the modeled monthly TWS estimates with errors in the soil moisture profile state variables at a single instant in the month and then apply the increment either at the end of the month or gradually throughout the month. The proposed new scheme first computes increments for each day of the month and then applies the average of those increments at the beginning of the month. The new scheme therefore better reflects submonthly variations in TWS errors. The new and existing schemes are investigated here using gridded GRACE-TWS observations. The assimilation results are validated at the monthly time scale, using in situ measurements of groundwater depth and soil moisture across the U.S. The new assimilation scheme yields improved (although not in a statistically significant sense) skill metrics for groundwater compared to the open-loop (no assimilation) simulations and compared to the existing assimilation schemes. A smaller impact is seen for surface and root-zone soil moisture, which have a shorter memory and receive smaller increments from TWS assimilation than groundwater. These results motivate future efforts to combine GRACE-TWS observations with observations that are more sensitive to surface soil moisture, such as L-band brightness temperature observations from Soil Moisture Ocean Salinity (SMOS) or Soil Moisture Active

Integrated Arctic Observation System Development Under Horizon 2020

NASA Astrophysics Data System (ADS)

Sandven, S.

2016-12-01

The overall objective of INTAROS is to develop an integrated Arctic Observation System (iAOS) by extending, improving and unifying existing systems in the different regions of the Arctic. INTAROS will have a strong multidisciplinary focus, with tools for integration of data from atmosphere, ocean, cryosphere and terrestrial sciences, provided by institutions in Europe, North America and Asia. Satellite earth observation data plays an increasingly important role in such observing systems, because the amount of EO data for observing the global climate and environment grows year by year. In situ observing systems are much more limited due to logistical constraints and cost limitations. The sparseness of in situ data is therefore the largest gap in the overall observing system. INTAROS will assess strengths and weaknesses of existing observing systems and contribute with innovative solutions to fill some of the critical gaps in the in situ observing network. INTAROS will develop a platform, iAOS, to search for and access data from distributed databases. The evolution into a sustainable Arctic observing system requires coordination, mobilization and cooperation between the existing European and international infrastructures (in-situ and remote including space-based), the modeling communities and relevant stakeholder groups. INTAROS will include development of community-based observing systems, where local knowledge is merged with scientific data. An integrated Arctic Observation System will enable better-informed decisions and better-documented processes within key sectors (e.g. local communities, shipping, tourism, fishing), in order to strengthen the societal and economic role of the Arctic region and support the EU strategy for the Arctic and related maritime and environmental policies.

Earth observing system: 1989 reference handbook

NASA Technical Reports Server (NTRS)

1989-01-01

NASA is studying a coordinated effort called the Mission to Planet Earth to understand global change. The goals are to understand the Earth as a system, and to determine those processes that contribute to the environmental balance, as well as those that may result in changes. The Earth Observing System (Eos) is the centerpiece of the program. Eos will create an integrated scientific observing system that will enable multidisciplinary study of the Earth including the atmosphere, oceans, land surface, polar regions, and solid Earth. Science goals, the Eos data and information system, experiments, measuring instruments, and interdisciplinary investigations are described.

Observing System Simulation Experiments: An Overview

NASA Technical Reports Server (NTRS)

Prive, Nikki C.; Errico, Ronald M.

2016-01-01

An overview of Observing System Simulation Experiments (OSSEs) will be given, with focus on calibration and validation of OSSE frameworks. Pitfalls and practice will be discussed, including observation error characteristics, incestuousness, and experimental design. The potential use of OSSEs for investigation of the behaviour of data assimilation systems will be explored, including some results from experiments using the NASAGMAO OSSE.

Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons

NASA Astrophysics Data System (ADS)

Karthikeyan, L.; Pan, Ming; Wanders, Niko; Kumar, D. Nagesh; Wood, Eric F.

2017-11-01

Soil moisture is widely recognized as an important land surface variable that provides a deeper knowledge of land-atmosphere interactions and climate change. Space-borne passive and active microwave sensors have become valuable and essential sources of soil moisture observations at global scales. Over the past four decades, several active and passive microwave sensors have been deployed, along with the recent launch of two fully dedicated missions (SMOS and SMAP). Signifying the four decades of microwave remote sensing of soil moisture, this Part 2 of the two-part review series aims to present an overview of how our knowledge in this field has improved in terms of the design of sensors and their accuracy for retrieving soil moisture. The first part discusses the developments made in active and passive microwave soil moisture retrieval algorithms. We assess the evolution of the products of various sensors over the last four decades, in terms of daily coverage, temporal performance, and spatial performance, by comparing the products of eight passive sensors (SMMR, SSM/I, TMI, AMSR-E, WindSAT, AMSR2, SMOS and SMAP), two active sensors (ERS-Scatterometer, MetOp-ASCAT), and one active/passive merged soil moisture product (ESA-CCI combined product) with the International Soil Moisture Network (ISMN) in-situ stations and the Variable Infiltration Capacity (VIC) land surface model simulations over the Contiguous United States (CONUS). In the process, the regional impacts of vegetation conditions on the spatial and temporal performance of soil moisture products are investigated. We also carried out inter-satellite comparisons to study the roles of sensor design and algorithms on the retrieval accuracy. We find that substantial improvements have been made over recent years in this field in terms of daily coverage, retrieval accuracy, and temporal dynamics. We conclude that the microwave soil moisture products have significantly evolved in the last four decades and will

Seasonal Variability of Salt Transports in the Northern Indian Ocean

NASA Astrophysics Data System (ADS)

D'Addezio, J. M.; Bulusu, S.

2016-02-01

Due to limited observational data in the Indian Ocean compared to other regions of the global ocean, past work on the Northern Indian Ocean (NIO) has relied heavily upon model analysis to study the variability of regional salinity advection caused by the monsoon seasons. With the launch of the Soil Moisture and Ocean Salinity (SMOS) satellite in 2009 and the Aquarius SAC-D mission in 2011 (ended on June 7, 2011), remotely sensed, synoptic scale sea surface salinity (SSS) data is now readily available to study this dynamic region. The new observational data has allowed us to revisit the region to analyze seasonal variability of salinity advection in the NIO using several modeled products, the Aquarius and SMOS satellites, and Argo floats data. The model simulations include the Consortium for Estimating the Circulation and Climate of the Ocean (ECCO2), European Centre for Medium-Range Weather Forecasts - Ocean Reanalysis System 4 (ECMWF-ORSA4), Simple Ocean Data Assimilation (SODA) Reanalysis, and HYbrid Coordinate Ocean Model (HYCOM). Our analyses of salinity at the surface and at depths up to 200 m, surface salt transport in the top 5 m layer, and depth-integrated salt transports revealed different salinity processes in the NIO that are dominantly related to the semi-annual monsoons. Aquarius and SMOS prove useful tools for observing this dynamic region, and reveal some aspects of SSS that Argo cannot resolve. Meridional depth-integrated salt transports using the modeled products along 6°N revealed dominant advective processes from the surface towards near-bottom depths. Finally, a difference in subsurface salinity stratification causes many of the modeled products to incorrectly estimate the magnitude and seasonality of NIO barrier layer thickness (BLT) when compared to the Argo solution. This problem is also evident in model output from the Seychelles-Chagos Thermocline Ridge (SCTR), a region with strong air-sea teleconnections with the Arabian Sea.

Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey

2016-01-01

Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.

CATOS (Computer Aided Training/Observing System): Automating animal observation and training.

PubMed

Oh, Jinook; Fitch, W Tecumseh

2017-02-01

In animal behavioral biology, an automated observing/training system may be useful for several reasons: (a) continuous observation of animals for documentation of specific, irregular events, (b) long-term intensive training of animals in preparation for behavioral experiments, (c) elimination of potential cues and biases induced by humans during training and testing. Here, we describe an open-source-based system named CATOS (Computer Aided Training/Observing System) developed for such situations. There are several notable features in this system. CATOS is flexible and low cost because it is based on free open-source software libraries, common hardware parts, and open-system electronics based on Arduino. Automated video condensation is applied, leading to significantly reduced video data storage compared to the total active hours of the system. A data-viewing utility program helps a user browse recorded data quickly and more efficiently. With these features, CATOS has the potential to be applied to many different animal species in various environments such as laboratories, zoos, or even private homes. Also, an animal's free access to the device without constraint, and a gamified learning process, enhance the animal's welfare and enriches their environment. As a proof of concept, the system was built and tested with two different species. Initially, the system was tested for approximately 10 months with a domesticated cat. The cat was successfully and fully automatically trained to discriminate three different spoken words. Then, in order to test the system's adaptability to other species and hardware components, we used it to train a laboratory rat for 3 weeks.

An adaptive tracking observer for failure-detection systems

NASA Technical Reports Server (NTRS)

Sidar, M.

1982-01-01

The design problem of adaptive observers applied to linear, constant and variable parameters, multi-input, multi-output systems, is considered. It is shown that, in order to keep the observer's (or Kalman filter) false-alarm rate (FAR) under a certain specified value, it is necessary to have an acceptable proper matching between the observer (or KF) model and the system parameters. An adaptive observer algorithm is introduced in order to maintain desired system-observer model matching, despite initial mismatching and/or system parameter variations. Only a properly designed adaptive observer is able to detect abrupt changes in the system (actuator, sensor failures, etc.) with adequate reliability and FAR. Conditions for convergence for the adaptive process were obtained, leading to a simple adaptive law (algorithm) with the possibility of an a priori choice of fixed adaptive gains. Simulation results show good tracking performance with small observer output errors and accurate and fast parameter identification, in both deterministic and stochastic cases.

Assessing Preschool Children's Competitive Behaviour: An Observational System

ERIC Educational Resources Information Center

Tsiakara, Angeliki; Digelidis, Nikolaos M.

2014-01-01

The aim of this study was to develop a direct observational system in order to assess competitive behaviours in preschool children. Participants were 176 children (90 boys, 86 girls; M[subscript age]?=?5.2 years) from 10 kindergarten classes of one town of Central Greece. A new observational system (Observational System Assessing Competition in…

Predicting Near Real-Time Inundation Occurrence from Complimentary Satellite Microwave Brightness Temperature Observations

NASA Astrophysics Data System (ADS)

Fisher, C. K.; Pan, M.; Wood, E. F.

2017-12-01

Throughout the world, there is an increasing need for new methods and data that can aid decision makers, emergency responders and scientists in the monitoring of flood events as they happen. In many regions, it is possible to examine the extent of historical and real-time inundation occurrence from visible and infrared imagery provided by sensors such as MODIS or the Landsat TM; however, this is not possible in regions that are densely vegetated or are under persistent cloud cover. In addition, there is often a temporal mismatch between the sampling of a particular sensor and a given flood event, leading to limited observations in near real-time. As a result, there is a need for alternative methods that take full advantage of complimentary remotely sensed data sources, such as available microwave brightness temperature observations (e.g., SMAP, SMOS, AMSR2, AMSR-E, and GMI), to aid in the estimation of global flooding. The objective of this work was to develop a high-resolution mapping of inundated areas derived from multiple satellite microwave sensor observations with a daily temporal resolution. This system consists of first retrieving water fractions from complimentary microwave sensors (AMSR-2 and SMAP) which may spatially and temporally overlap in the region of interest. Using additional information in a Random Forest classifier, including high resolution topography and multiple datasets of inundated area (both historical and empirical), the resulting retrievals are spatially downscaled to derive estimates of the extent of inundation at a scale relevant to management and flood response activities ( 90m or better) instead of the relatively coarse resolution water fractions, which are limited by the microwave sensor footprints ( 5-50km). Here we present the training and validation of this method for the 2015 floods that occurred in Houston, Texas. Comparing the predicted inundation against historical occurrence maps derived from the Landsat TM record and MODIS

Land-cover observations as part of a Global Earth Observation System of Systems (GEOSS): Progress, activities, and prospects

USGS Publications Warehouse

Herold, M.; Woodcock, C.E.; Loveland, Thomas R.; Townshend, J.; Brady, M.; Steenmans, C.; Schmullius, C. C.

2008-01-01

The international land-cover community has been working with GEO since 2005 to build the foundations for land-cover observations as an integral part of a Global Earth Observation System of Systems (GEOSS). The Group on Earth Observation (GEO) has provided the platform to elevate the societal relevance of land cover monitoring and helped to link a diverse set of global, regional, and national activities. A dedicated 2007-2009 GEO work plan task has resulted in achievements on the strategic and implementation levels. Integrated Global Observations of the Land (IGOL), the land theme of the Integrated Global Observation Strategy (IGOS), has been approved and is now in the process of transition into GEO implementation. New global land-cover maps at moderate spatial resolutions (i.e., GLOBCOVER) are being produced using guidelines and standards of the international community. The Middecadal Global Landsat Survey for 2005-2006 is extending previous 1990 and 2000 efforts for global, high-quality Landsat data. Despite this progress, essential challenges for building a sustained global land-cover-observing system remain, including: international cooperation on the continuity of global observations; ensuring consistency in land monitoring approaches; community engagement and country participation in mapping activities; commitment to ongoing quality assurance and validation; and regional networking and capacity building.

1993 Earth Observing System reference handbook

NASA Technical Reports Server (NTRS)

Asrar, Ghassem (Editor); Dokken, David Jon (Editor)

1993-01-01

Mission to Planet Earth (MTPE) is a NASA-sponsored concept that uses space- and ground-based measurement systems to provide the scientific basis for understanding global change. The space-based components of MTPE will provide a constellation of satellites to monitor the Earth from space. Sustained observations will allow researchers to monitor climate variables overtime to determine trends; however, space-based monitoring alone is not sufficient. A comprehensive data and information system, a community of scientists performing research with the data acquired, and extensive ground campaigns are all important components. Brief descriptions of the various elements that comprise the overall mission are provided. The Earth Observing System (EOS) - a series of polar-orbiting and low-inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans - is the centerpiece of MTPE. The elements comprising the EOS mission are described in detail.

On the development of earth observation satellite systems

NASA Technical Reports Server (NTRS)

1977-01-01

Subsequent to the launching of the first LANDSAT by NASA, Japan has recognized the importance of data from earth observation satellites, has conducted studies, and is preparing to develop an independent system. The first ocean observation satellite will be launched in 1983, the second in 1985. The first land observation satellite is scheduled to be launched in 1987 and by 1990 Japan intends to have both land and ocean observation systems in regular operation. The association reception and data processing systems are being developed.

Interleaved Observation Execution and Rescheduling on Earth Observing Systems

NASA Technical Reports Server (NTRS)

Khatib, Lina; Frank, Jeremy; Smith, David; Morris, Robert; Dungan, Jennifer

2003-01-01

Observation scheduling for Earth orbiting satellites solves the following problem: given a set of requests for images of the Earth, a set of instruments for acquiring those images distributed on a collecting of orbiting satellites, and a set of temporal and resource constraints, generate a set of assignments of instruments and viewing times to those requests that satisfy those constraints. Observation scheduling is often construed as a constrained optimization problem with the objective of maximizing the overall utility of the science data acquired. The utility of an image is typically based on the intrinsic importance of acquiring it (for example, its importance in meeting a mission or science campaign objective) as well as the expected value of the data given current viewing conditions (for example, if the image is occluded by clouds, its value is usually diminished). Currently, science observation scheduling for Earth Observing Systems is done on the ground, for periods covering a day or more. Schedules are uplinked to the satellites and are executed rigorously. An alternative to this scenario is to do some of the decision-making about what images are to be acquired on-board. The principal argument for this capability is that the desirability of making an observation can change dynamically, because of changes in meteorological conditions (e.g. cloud cover), unforeseen events such as fires, floods, or volcanic eruptions, or un-expected changes in satellite or ground station capability. Furthermore, since satellites can only communicate with the ground between 5% to 10% of the time, it may be infeasible to make the desired changes to the schedule on the ground, and uplink the revisions in time for the on-board system to execute them. Examples of scenarios that motivate an on-board capability for revising schedules include the following. First, if a desired visual scene is completely obscured by clouds, then there is little point in taking it. In this case

Roles of Social Movement Organizations for Securing Workers' Safety in Korea: A Case Study of Abolition of the 30-Minute Delivery Guarantee Program in Pizza Delivery Service.

PubMed

Park, Ji-Eun; Kim, Myoung-Hee

2016-07-01

Many restaurants in Korea maintain quick-delivery service programs to satisfy customers. This service allows delivery workers limited time to deliver, which frequently put them in danger. Most of the workers are young, work part-time, and are rarely organized into trade unions. In this article, through a case study of the social movement to abolish the 30-minute delivery guarantee program of pizza companies in Korea, we argue that social movements involving social movement organizations (SMOs) and individual citizens could serve as a means to rectify this problem. We show how the SMOs developed and expanded the movement using a framing perspective and how the general public became involved through social media. Data was collected via online searching. Interview scripts from key players of SMOs and unofficial documents they provided were also reviewed. Three SMOs primarily led the movement, successfully forming a frame that emphasized social responsibility. SMOs also utilized social media to link their standing frame with unmobilized citizens and to expand the movement. We identified contributing factors and limitations of the movement and drew lessons that could be applied to other sectors where workers are in vulnerable positions. © The Author(s) 2016.

Developing a Carbon Observing System

NASA Astrophysics Data System (ADS)

Moore, B., III

2015-12-01

There is a clear need to better understand and predict future climate change, so that science can more confidently inform climate policy, including adaptation planning and future mitigation strategies. Understanding carbon cycle feedbacks, and the relationship between emissions (fossil and land use) and the resulting atmospheric carbon dioxide (CO2) and methane (CH4) concentrations in a changing climate has been recognized as an important goal by the IPCC. The existing surface greenhouse gas observing networks provide accurate and precise measurements of background values, but they are not configured to target the extended, complex and dynamic regions of the carbon budget. Space Agencies around the globe are committed to CO2 and CH4 observations: GOSAT-1/2, OCO-2/3, MERLin, TanSat, and CarbonSat. In addition to these Low Earth Orbit (LEO) missions, a new mission in Geostationary Orbit (GEO), geoCARB, which would provide mapping-like measurements of carbon dioxide, methane, and carbon monoxide concentrations over major land areas, has been recently proposed to the NASA Venture Program. These pioneering missions do not provide the spatial/temporal coverage to answer the key carbon-climate questions at process relevant scales nor do they address the distribution and quantification of anthropogenic sources at urban scales. They do demonstrate, however, that a well-planned future system of system integrating space-based LEO and GEO missions with extensive in situ observations could provide the accuracy, spatial resolution, and coverage needed to address critical open issues in the carbon-climate system. Dr. Diana Wickland devoted enormous energy in developing a comprehensive apprioach to understand the global carbon cycle; she understood well that an integrated, coordinated, international approach is needed. This shines through in her recent contribution in co-chairing the team that produced the "CEOS Strategy for Carbon Observations from Space." A NASA-funded community

Potential of bias correction for downscaling passive microwave and soil moisture data

USDA-ARS?s Scientific Manuscript database

Passive microwave satellites such as SMOS (Soil Moisture and Ocean Salinity) or SMAP (Soil Moisture Active Passive) observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...

Gulf of Mexico Coastal Ocean Observing System: The Gulf Component of the U.S. Integrated Ocean Observing System

NASA Astrophysics Data System (ADS)

Bernard, L. J.; Moersdorf, P. F.

2005-05-01

The United States is developing an Integrated Ocean Observing System (IOOS) as the U.S. component of the international Global Ocean Observing System (GOOS). IOOS consists of: (1) a coastal observing system for the U.S. EEZ, estuaries, and Great Lakes; and (2) a contribution to the global component of GOOS focused on climate and maritime services. The coastal component will consist of: (1) a National Backbone of observations and products from our coastal ocean supported by federal agencies; and (2) contributions of Regional Coastal Ocean Observing Systems (RCOOS). The Gulf of Mexico Coastal Ocean Observing System (GCOOS) is one of eleven RCOOS. This paper describes how GCOOS is progressing as a system of systems to carry out data collection, analysis, product generation, dissemination of information, and data archival. These elements are provided by federal, state, and local government agencies, academic institutions, non-government organization, and the private sector. This end-to-end system supports the seven societal goals of the IOOS, as provided by the U.S. Commission on Ocean Policy: detect and forecast oceanic components of climate variability, facilitate safe and efficient marine operations, ensure national security, manage marine resources, preserve and restore healthy marine ecosystems, mitigate natural hazards, and ensure public health. The initial building blocks for GCOOS include continuing in situ observations, satellite products, models, and other information supported by federal and state government, private industry, and academia. GCOOS has compiled an inventory of such activities, together with descriptions, costs, sources of support, and possible out-year budgets. These activities provide information that will have broader use as they are integrated and enhanced. GCOOS has begun that process by several approaches. First, GCOOS has established a web site (www.gcoos.org) which is a portal to such activities and contains pertinent information

Chandra Observations of the Solar System

NASA Astrophysics Data System (ADS)

Lisse, Carey

2014-11-01

Many solar system objects are now known to emit X-rays due to charge-exchange between highly charged solar wind (SW) minor ions and neutrals in their extended atmospheres, including Earth, Venus, Mars, Jupiter, and the heliosphere, with total power outputs on the MW - GW scale. (Currently only upper limits exist for Saturn and Pluto.) Chandra observations of their morphology, spectra, and time dependence provide important information about the neutral atmosphere structure and the SW flux and charge state. Chandra observations of solar x-ray scattering from Earth, Venus, Mars, Jupiter, Saturn, and the Moon have also provided important clues for the scattering material and the solar radiation field at the body. We present here a 15 year summary of Chandra's solar system observations.

Evaluating the Utility of Satellite Soil Moisture Retrievals over Irrigated Areas and the Ability of Land Data Assimilation Methods to Correct for Unmodeled Processes

NASA Technical Reports Server (NTRS)

Kumar, S. V.; Peters-Lidard, C. D.; Santanello, J. A.; Reichle, R. H.; Draper, C. S.; Koster, R. D.; Nearing, G.; Jasinski, M. F.

2015-01-01

Earth's land surface is characterized by tremendous natural heterogeneity and human-engineered modifications, both of which are challenging to represent in land surface models. Satellite remote sensing is often the most practical and effective method to observe the land surface over large geographical areas. Agricultural irrigation is an important human-induced modification to natural land surface processes, as it is pervasive across the world and because of its significant influence on the regional and global water budgets. In this article, irrigation is used as an example of a human-engineered, often unmodeled land surface process, and the utility of satellite soil moisture retrievals over irrigated areas in the continental US is examined. Such retrievals are based on passive or active microwave observations from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), the Advanced Microwave Scanning Radiometer 2 (AMSR2), the Soil Moisture Ocean Salinity (SMOS) mission, WindSat and the Advanced Scatterometer (ASCAT). The analysis suggests that the skill of these retrievals for representing irrigation effects is mixed, with ASCAT-based products somewhat more skillful than SMOS and AMSR2 products. The article then examines the suitability of typical bias correction strategies in current land data assimilation systems when unmodeled processes dominate the bias between the model and the observations. Using a suite of synthetic experiments that includes bias correction strategies such as quantile mapping and trained forward modeling, it is demonstrated that the bias correction practices lead to the exclusion of the signals from unmodeled processes, if these processes are the major source of the biases. It is further shown that new methods are needed to preserve the observational information about unmodeled processes during data assimilation.

Computerized Observation System (COS) for Field Experiences.

ERIC Educational Resources Information Center

Reed, Thomas M.; And Others

The Computerized Observation System (COS) is a software program which an observer can use with a portable microcomputer to document preservice and inservice teacher performance. Specific observable behavior such as appropriate questions and responses shown to increase student achievement are recorded as Low Inference Observation Measures. Time on…

Earth Observing System, Conclusions and Recommendations

NASA Technical Reports Server (NTRS)

1984-01-01

The following Earth Observing Systems (E.O.S.) recommendations were suggested: (1) a program must be initiated to ensure that present time series of Earth science data are maintained and continued. (2) A data system that provides easy, integrated, and complete access to past, present, and future data must be developed as soon as possible. (3) A long term research effort must be sustained to study and understand these time series of Earth observations. (4) The E.O.S. should be established as an information system to carry out those aspects of the above recommendations which go beyond existing and currently planned activities. (5) The scientific direction of the E.O.S. should be established and continued through an international scientific steering committee.

Cost-effectiveness of a New Opportunistic Screening Strategy for Walk-in Fingertip HbA1c Testing at Community Pharmacies in Japan.

PubMed

Shono, Aiko; Kondo, Masahide; Hoshi, Shu-Ling; Okubo, Reiko; Yahagi, Naoya

2018-06-01

A new opportunistic community-based strategy was launched in Japan in April 2014 to detect lifestyle-related diseases, including diabetes, by creating Specimen Measurement Offices (SMOs). SMOs offer walk-in fingertip HbA 1c testing. This article aimed to assess the value-for-money of HbA 1c testing services at SMOs by conducting a cost-effectiveness analysis. We compared two scenarios: 1 ) status quo, defined as HbA 1c testing that is available only through conventional screening, and 2 ) HbA 1c testing available at SMOs as a complement to the status quo scenario. The model consisted of a screening module with a decision tree and a disease progression module with a Markov model. We calculated incremental cost-effectiveness ratios (i.e., cost per quality-adjusted life-years [QALYs]) over the lifetime analytic horizon as the primary end point of the cost-effectiveness analysis. In this model, we assumed the participant cohort to be people 40-74 years of age who sought walk-in fingertip HbA 1c testing at SMOs on the premises of community pharmacies. Costs and outcomes were discounted at a rate of 3%. The cost-effectiveness was analyzed from a societal perspective. The incremental cost per individual for those 40-74 years of age was estimated to be -527 U.S. dollars (USD) (-52,722 Japanese yen [JPY]) for HbA 1c testing at SMOs compared with the status quo. Incremental effectiveness was estimated to be 0.0203 QALYs for HbA 1c testing at SMOs compared with the status quo. Therefore, this cost-effectiveness analysis showed that compared with the status quo, HbA 1c testing at SMOs was more effective and had lower cost for the population studied. We consider our results to be robust because most simulations were under the threshold of USD 50,000 (JPY 5,000,000) per QALYs gained, by sensitivity analysis. These results will be useful to managers of pharmacies or other health institutions and/or policy makers in local government. © 2018 by the American Diabetes Association.

An Observer's View of the ORAC System at UKIRT

NASA Astrophysics Data System (ADS)

Wright, G. S.; Bridger, A. B.; Pickup, D. A.; Tan, M.; Folger, M.; Economou, F.; Adamson, A. J.; Currie, M. J.; Rees, N. P.; Purves, M.; Kackley, R. D.

The Observatory Reduction and Acquisition Control system (ORAC) was commissioned with its first instrument at the UK Infrared Telescope (UKIRT) in October 1999, and with all of the other UKIRT instrumentation this year. ORAC's advance preparation Observing Tool makes it simpler to prepare and carry out observations. Its Observing Manager gives observers excellent feedback on their observing as it goes along, reducing wasted time. The ORAC pipelined Data Reduction system produces near-publication quality reduced data at the telescope. ORAC is now in use for all observing at UKIRT, including flexibly scheduled nights and service observing. This paper provides an observer's perspective of the system and its performance.

Determining temporal scales of the soil moisture variations by Empirical Mode Decompositions and wavelet methods and its use for validation of SMOS data

NASA Astrophysics Data System (ADS)

Usowicz, Jerzy, B.; Marczewski, Wojciech; Usowicz, Boguslaw; Lipiec, Jerzy; Lukowski, Mateusz I.

2010-05-01

This paper presents the results of the time series analysis of the soil moisture observed at two test sites Podlasie, Polesie, in the Cal/Val AO 3275 campaigns in Poland, during the interval 2006-2009. The test sites have been selected on a basis of their contrasted hydrological conditions. The region Podlasie (Trzebieszow) is essentially drier than the wetland region Polesie (Urszulin). It is worthwhile to note that the soil moisture variations can be represented as a non-stationary random process, and therefore appropriate analysis methods are required. The so-called Empirical Mode Decomposition (EMD) method has been chosen, since it is one of the best methods for the analysis of non-stationary and nonlinear time series. To confirm the results obtained by the EMD we have also used the wavelet methods. Firstly, we have used EMD (analyze step) to decompose the original time series into the so-called Intrinsic Mode Functions (IMFs) and then by grouping and addition similar IMFs (synthesize step) to obtain a few signal components with corresponding temporal scales. Such an adaptive procedure enables to decompose the original time series into diurnal, seasonal and trend components. Revealing of all temporal scales which operates in the original time series is our main objective and this approach may prove to be useful in other studies. Secondly, we have analyzed the soil moisture time series from both sites using the cross-wavelet and wavelet coherency. These methods allow us to study the degree of spatial coherence, which may vary in various intervals of time. We hope the obtained results provide some hints and guidelines for the validation of ESA SMOS data. References: B. Usowicz, J.B. Usowicz, Spatial and temporal variation of selected physical and chemical properties of soil, Institute of Agrophysics, Polish Academy of Sciences, Lublin 2004, ISBN 83-87385-96-4 Rao, A.R., Hsu, E.-C., Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series

NANOOS, the Northwest Association of Networked Ocean Observing Systems: a regional Integrated Ocean Observing System (IOOS) for the Pacific Northwest US

NASA Astrophysics Data System (ADS)

Newton, J.; Martin, D.; Kosro, M.

2012-12-01

NANOOS is the Northwest Association of Networked Ocean Observing Systems, the Pacific Northwest Regional Association of the United States Integrated Ocean Observing System (US IOOS). User driven since its inception in 2003, this regional observing system is responding to a variety of scientific and societal needs across its coastal ocean, estuaries, and shorelines. Regional priorities have been solicited and re-affirmed through active engagement with users and stakeholders. NANOOS membership is composed of an even mix of academic, governmental, industry, and non-profit organizations, who appoint representatives to the NANOOS Governing Council who confirm the priority applications of the observing system. NANOOS regional priorities are: Maritime Operations, Regional Fisheries, Ecosystem Assessment, Coastal Hazards, and Climate. NANOOS' regional coastal ocean observing system is implemented by seven partners (three universities, three state agencies, and one industry). Together, these partners conduct the observations, modeling, data management and communication, analysis products, education and outreach activities of NANOOS. Observations, designed to span coastal ocean, shorelines, and estuaries, include physical, chemical, biological and geological measurements. To date, modeling has been more limited in scope, but has provided the system with increased coverage for some parameters. The data management and communication system for NANOOS, led by the NANOOS Visualization System (NVS) is the cornerstone of the user interaction with NANOOS. NVS gives users access to observational data, both real time and archived, as well as modeling output. Given the diversity of user needs, measurements, and the complexity of the coastal environment, the challenge for the system is large. NANOOS' successes take advantage of technological advances, including real-time data transmission, profiling buoys, gliders, HF radars, and modeling. The most profound challenges NANOOS faces stem

Satellite observed global variations in ecosystem-scale plant water storage

NASA Astrophysics Data System (ADS)

Tian, F.; Wigneron, J. P.; Brandt, M.; Fensholt, R.

2017-12-01

Plant water storage is a key component in ecohydrological processes and tightly coupled with global carbon and energy budgets. Field measurements of individual trees have revealed diurnal and seasonal variations in plant water storage across different tree species and sizes. However, global estimation of plant water storage is challenged by up-scaling from individual trees to an ecosystem scale. The L-band passive microwaves are sensitive to water stored in the stems, branches and leaves, with dependence on the vegetation structure. Thus, the L-band vegetation optical depth (L-VOD) parameter retrieved from satellite passive microwave observations can be used as a proxy for ecosystem-scale plant water storage. Here, we employ the recently developed SMOS (Soil Moisture and Ocean Salinity) L-VOD dataset to investigate spatial patterns in global plant water storage and its diurnal and seasonal variations. In addition, we compare the spatiotemporal patterns between plant water storage and canopy greenness (i.e., enhanced vegetation indices, EVI) to gain ecohydrological insights among different territorial biomes, including boreal forest and tropical woodland. Generally, seasonal dynamics of plant water storage is much smaller than canopy greenness, yet the temporal coupling of these two traits is totally different between boreal and tropical regions, which could be related to their strategies in plant water regulation.

Toward improving the representation of the water cycle at High Northern Latitudes

NASA Astrophysics Data System (ADS)

Lahoz, William; Svendby, Tove; Hamer, Paul; Blyverket, Jostein; Kristiansen, Jørn; Luijting, Hanneke

2016-04-01

The rapid warming at northern latitude regions in recent decades has resulted in a lengthening of the growing season, greater photosynthetic activity and enhanced carbon sequestration by the ecosystem. These changes are likely to intensify summer droughts, tree mortality and wildfires. A potential major climate change feedback is the release of carbon-bearing compounds from soil thawing. These changes make it important to have information on the land surface (soil moisture and temperature) at high northern latitude regions. The availability of soil moisture measurements from several satellite platforms provides an opportunity to address issues associated with the effects of climate change, e.g., assessing multi-decadal links between increasing temperatures, snow cover, soil moisture variability and vegetation dynamics. The relatively poor information on water cycle parameters for biomes at northern high latitudes make it important that efforts are expended on improving the representation of the water cycle at these latitudes. In a collaboration between NILU and Met Norway, we evaluate the soil moisture observations over Norway from the ESA satellite SMOS (Soil Moisture and Ocean Salinity) using in situ ground based soil moisture measurements, with reference to drought and flood episodes. We will use data assimilation of the quality-controlled SMOS soil moisture observations into a land surface model and a numerical weather prediction model to assess the added value from satellite observations of soil moisture for improving the representation of the water cycle at high northern latitudes. This presentation provides first results from this work. We discuss the evaluation of SMOS soil moisture data (and from other satellites) against ground-based in situ data over Norway; the performance of the SMOS soil moisture data for selected drought and flood conditions over Norway; and the first results from data assimilation experiments with land surface models and numerical

Observing System Simulation Experiments for Fun and Profit

NASA Technical Reports Server (NTRS)

Prive, Nikki C.

2015-01-01

Observing System Simulation Experiments can be powerful tools for evaluating and exploring both the behavior of data assimilation systems and the potential impacts of future observing systems. With great power comes great responsibility - given a pure modeling framework, how can we be sure our results are meaningful? The challenges and pitfalls of OSSE calibration and validation will be addressed, as well as issues of incestuousness, selection of appropriate metrics, and experiment design. The use of idealized observational networks to investigate theoretical ideas in a fully complex modeling framework will also be discussed

Designing the Climate Observing System of the Future

NASA Astrophysics Data System (ADS)

Weatherhead, Elizabeth C.; Wielicki, Bruce A.; Ramaswamy, V.; Abbott, Mark; Ackerman, Thomas P.; Atlas, Robert; Brasseur, Guy; Bruhwiler, Lori; Busalacchi, Antonio J.; Butler, James H.; Clack, Christopher T. M.; Cooke, Roger; Cucurull, Lidia; Davis, Sean M.; English, Jason M.; Fahey, David W.; Fine, Steven S.; Lazo, Jeffrey K.; Liang, Shunlin; Loeb, Norman G.; Rignot, Eric; Soden, Brian; Stanitski, Diane; Stephens, Graeme; Tapley, Byron D.; Thompson, Anne M.; Trenberth, Kevin E.; Wuebbles, Donald

2018-01-01

Climate observations are needed to address a large range of important societal issues including sea level rise, droughts, floods, extreme heat events, food security, and freshwater availability in the coming decades. Past, targeted investments in specific climate questions have resulted in tremendous improvements in issues important to human health, security, and infrastructure. However, the current climate observing system was not planned in a comprehensive, focused manner required to adequately address the full range of climate needs. A potential approach to planning the observing system of the future is presented in this article. First, this article proposes that priority be given to the most critical needs as identified within the World Climate Research Program as Grand Challenges. These currently include seven important topics: melting ice and global consequences; clouds, circulation and climate sensitivity; carbon feedbacks in the climate system; understanding and predicting weather and climate extremes; water for the food baskets of the world; regional sea-level change and coastal impacts; and near-term climate prediction. For each Grand Challenge, observations are needed for long-term monitoring, process studies and forecasting capabilities. Second, objective evaluations of proposed observing systems, including satellites, ground-based and in situ observations as well as potentially new, unidentified observational approaches, can quantify the ability to address these climate priorities. And third, investments in effective climate observations will be economically important as they will offer a magnified return on investment that justifies a far greater development of observations to serve society's needs.

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

NASA Technical Reports Server (NTRS)

Lievens, H.; Martens, B.; Verhoest, N. E. C.; Hahn, S.; Reichle, R. H.; Miralles, D. G.

2017-01-01

Active radar backscatter (s?) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s? and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s? or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s? and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

The Global Ocean Observing System: One perspective

NASA Technical Reports Server (NTRS)

Wilson, J. Ron

1992-01-01

This document presents a possible organization for a Global Ocean Observing System (GOOS) within the Intergovernmental Oceanographic Commission and the joint ocean programs with the World Meteorological Organization. The document and the organization presented here is not intended to be definitive, complete or the best possible organization for such an observation program. It is presented at this time to demonstrate three points. The first point to be made is that an international program office for GOOS along the lines of the WOCE and TOGA IPOs is essential. The second point is that national programs will have to continue to collect data at the scale of WOCE plus TOGA and more. The third point is that there are many existing groups and committees within the IOC and joint IOC/WMO ocean programs that can contribute essential experience to and form part of the basis of a Global Ocean Observing System. It is particularly important to learn from what has worked and what has not worked in the past if a successful ocean observing system is to result.

Semantics-enabled knowledge management for global Earth observation system of systems

NASA Astrophysics Data System (ADS)

King, Roger L.; Durbha, Surya S.; Younan, Nicolas H.

2007-10-01

The Global Earth Observation System of Systems (GEOSS) is a distributed system of systems built on current international cooperation efforts among existing Earth observing and processing systems. The goal is to formulate an end-to-end process that enables the collection and distribution of accurate, reliable Earth Observation data, information, products, and services to both suppliers and consumers worldwide. One of the critical components in the development of such systems is the ability to obtain seamless access of data across geopolitical boundaries. In order to gain support and willingness to participate by countries around the world in such an endeavor, it is necessary to devise mechanisms whereby the data and the intellectual capital is protected through procedures that implement the policies specific to a country. Earth Observations (EO) are obtained from a multitude of sources and requires coordination among different agencies and user groups to come to a shared understanding on a set of concepts involved in a domain. It is envisaged that the data and information in a GEOSS context will be unprecedented and the current data archiving and delivery methods need to be transformed into one that allows realization of seamless interoperability. Thus, EO data integration is dependent on the resolution of conflicts arising from a variety of areas. Modularization is inevitable in distributed environments to facilitate flexible and efficient reuse of existing ontologies. Therefore, we propose a framework for modular ontologies based knowledge management approach for GEOSS and present methods to enable efficient reasoning in such systems.

Classification framework for partially observed dynamical systems

NASA Astrophysics Data System (ADS)

Shen, Yuan; Tino, Peter; Tsaneva-Atanasova, Krasimira

2017-04-01

We present a general framework for classifying partially observed dynamical systems based on the idea of learning in the model space. In contrast to the existing approaches using point estimates of model parameters to represent individual data items, we employ posterior distributions over model parameters, thus taking into account in a principled manner the uncertainty due to both the generative (observational and/or dynamic noise) and observation (sampling in time) processes. We evaluate the framework on two test beds: a biological pathway model and a stochastic double-well system. Crucially, we show that the classification performance is not impaired when the model structure used for inferring posterior distributions is much more simple than the observation-generating model structure, provided the reduced-complexity inferential model structure captures the essential characteristics needed for the given classification task.

The Integrated Ocean Observing System Data Assembly Center

NASA Astrophysics Data System (ADS)

Bouchard, R. H.; Henderson, D.; Burnett, W.; Hervey, R. V.; Crout, R.

2008-05-01

The Integrated Ocean Observing System (IOOS) is the U.S. contribution to the Global Ocean Observing System and the Global Earth Observing System of Systems (GEOSS). As the Integrated Ocean Observing System Data Assembly Center (IOOS DAC), the National Oceanic and Atmospheric Administration`s (NOAA) National Data Buoy Center (NDBC) collects data from ocean observing systems and performs quality control on the data. Once the IOOS DAC performs the quality control, it distributes them in real-time: (1) in World Meteorological Organization alphanumeric data formats via the Global Telecommunications System (GTS) that provides instant availability to national and international users (2) in text files via its website (http://www.ndbc.noaa.gov) that provide easy access and use, and (3) in netCDF format via its OPeNDAP/DODS Server (http://dods.ndbc.noaa.gov) that provides higher resolution data than available in WMO alphanumeric or text file formats. The IOOS DAC routinely checks and distributes data from about 200 NDBC stations that include meteorological and oceanographic observations from buoys and coastal stations, water-level estimations from tsunameters (DART), and climate monitoring from buoys (Tropical Atmosphere Ocean array (TAO)). The IOOS DAC operates continuously - 24 hours per day, 7 days per week. In addition to data from NDBC`s platforms, the IOOS DAC applies its scientific expertise and data management and communications capabilities to facilitate partnerships for the exchange and application of data and to coordinate and leverage regional assets and resources from about 350 IOOS Partner stations. The IOOS DAC through its quality control process provides feedback to its partners on the quality of their observation that can lead to improved quality of the observations. The NDBC-IOOS Data Partnerships span the Western Hemisphere with data collection from the Beaufort Sea to the Peru Current, from the International Date Line to the central Atlantic Ocean, and

Interoperable Access to Near Real Time Ocean Observations with the Observing System Monitoring Center

NASA Astrophysics Data System (ADS)

O'Brien, K.; Hankin, S.; Mendelssohn, R.; Simons, R.; Smith, B.; Kern, K. J.

2013-12-01

The Observing System Monitoring Center (OSMC), a project funded by the National Oceanic and Atmospheric Administration's Climate Observations Division (COD), exists to join the discrete 'networks' of In Situ ocean observing platforms -- ships, surface floats, profiling floats, tide gauges, etc. - into a single, integrated system. The OSMC is addressing this goal through capabilities in three areas focusing on the needs of specific user groups: 1) it provides real time monitoring of the integrated observing system assets to assist management in optimizing the cost-effectiveness of the system for the assessment of climate variables; 2) it makes the stream of real time data coming from the observing system available to scientific end users into an easy-to-use form; and 3) in the future, it will unify the delayed-mode data from platform-focused data assembly centers into a standards- based distributed system that is readily accessible to interested users from the science and education communities. In this presentation, we will be focusing on the efforts of the OSMC to provide interoperable access to the near real time data stream that is available via the Global Telecommunications System (GTS). This is a very rich data source, and includes data from nearly all of the oceanographic platforms that are actively observing. We will discuss how the data is being served out using a number of widely used 'web services' (including OPeNDAP and SOS) and downloadable file formats (KML, csv, xls, netCDF), so that it can be accessed in web browsers and popular desktop analysis tools. We will also be discussing our use of the Environmental Research Division's Data Access Program (ERDDAP), available from NOAA/NMFS, which has allowed us to achieve our goals of serving the near real time data. From an interoperability perspective, it's important to note that access to the this stream of data is not just for humans, but also for machine-to-machine requests. We'll also delve into how we

Soil Moisture Retrieval During a Corn Growth Cycle using L-band (1.6 GHz) Radar Observations

NASA Technical Reports Server (NTRS)

Joseph, Alicia T.; vanderVelde, Rogier; O'Neill, Peggy E.; Lang, Roger; Gish, Tim

2007-01-01

New opportunities for large-scale soil moisture monitoring will emerge with the launch of two low frequency (L-band 1.4 GHz) radiometers: the Aquarius mission in 2009 and the Soil Moisture and Ocean Salinity (SMOS) mission in 2008. Soil moisture is an important land surface variable affecting water and heat exchanges between atmosphere, land surface and deeper ground water reservoirs. The data products from these sensors provide valuable information in a range of climate and hydrologic applications (e.g., numecal weather prediction, drought monitoring, flood forecasting, water resources management, etc.). This paper describes a unique data set that was collected during a field campaign at OPE^ (Optimizing Production Inputs for Economic and Environmental Enhancements) site in Beltsville, Maryland throughout the eompj2ete corn growing in 2002. This investigation describes a simple methodology to correct active microwave observations for vegetation effects, which could potentially be implemented in a global soil moisture monitoring algorithm. The methodology has been applied to radar observation collected during the entire corn growth season and validation against ground measurements showed that the top 5-cm soil moisture can be retrieved with an accuracy up to 0.033 [cu cm/cu cm] depending on the sensing configuration.

Optical data communication for Earth observation satellite systems

NASA Astrophysics Data System (ADS)

Fischer, J.; Loecherbach, E.

1991-10-01

The current development status of optical communication engineering in comparison to the conventional microwave systems and the different configurations of the optical data communication for Earth observation satellite systems are described. An outlook to future optical communication satellite systems is given. During the last decade Earth observation became more and more important for the extension of the knowledge about our planet and the human influence on nature. Today pictures taken by satellites are used, for example, to discover mineral resources or to predict harvest, crops, climate, and environment variations and their influence on the population. A new and up to date application for Earth observation satellites can be the verification of disarmament arrangements and the control of crises areas. To solve these tasks a system of Earth observing satellites with sensors tailored to the envisaged mission is necessary. Besides these low Earth orbiting satellites, a global Earth observation system consists of at least two data relay satellites. The communication between the satellites will be established via Inter-Satellite Links (ISL) and Inter-Orbit Links (IOL). On these links, bitrates up to 1 Gbit/s must be taken into account. Due to the increasing scarcity of suitable frequencies, higher carrier frequencies must probably be considered, and possible interference with terrestrial radio relay systems are two main problems for a realization in microwave technique. One important step to tackle these problems is the use of optical frequencies for IOL's and ISL's.

Planning for the Global Earth Observation System of Systems (GEOSS)

USGS Publications Warehouse

Christian, E.

2005-01-01

The Group on Earth Observations was established to promote comprehensive, coordinated, and sustained Earth observations. Its mandate is to implement the Global Earth Observation System of Systems (GEOSS) in accord with the GEOSS 10-Year Implementation Plan and Reference Document. During the months over which the GEOSS Implementation Plan was developed, many issues surfaced and were addressed. This article discusses several of the more interesting or challenging of those issues-e.g. fitting in with existing organizations and securing stable funding - some of which have yet to be resolved fully as of this writing. Despite the relatively short period over which the Implementation Plan had to be developed, there is a good chance that the work undertaken will be influential for decades to come. ?? 2005 Elsevier Ltd. All rights reserved.

What do we learn about the impact of extreme hydrological events on tropical wetlands from the synergistic use of altimetry from Sentinel-3/SARAL-Altika and L-Band radiometry from SMOS/SMAP ?

NASA Astrophysics Data System (ADS)

Al Bitar, Ahmad; Parrens, Marie; Frappart, Frederic; Cauduro Dias de Paiva, Rodrigo; Papa, Fabrice; Kerr, Yann

2017-04-01

What do we learn about the impact of extreme hydrological events on tropical wetlands from the synergistic use of altimetry from Sentinel-3/SARAL-Altika and L-Band radiometry from SMOS/SMAP ? The question of the contribution of the tropical basins to the carbon and water cycle remains an open question in the science community. The tropical basins are highly impact by the wetlands dynamics but the also the link with extreme events like El-Nino are yet to be clarified. The main reason to this uncertainty is that the monitoring of inland water surfaces via remote sensing over tropical areas is a difficult task because of impact of vegetation and cloud cover. The most common solution is to use microwave remote sensing. In this study we combine the use of L-band microwave brightness temperatures and altimetric data from SARAL/ALTIKA and Sentinel-3 to derive water storage maps at relatively high (7days) temporal frequency. This study concerns the Amazon and Congo basin. The water fraction in inland are estimated by inversing a first order radiative model is used to derive surface water over land from the brightness temperature measured by ESA SMOS and SMAP mission at coarse resolution (25 km x 25 km) and 7-days frequency. The product is compared to the static land cover map such as ESA CCI and the International Geosphere-Biosphere Program (IGBP) and also dynamic maps from GIEMS and SWAPS products. Water storage is then obtained by combining the altimetric data from SARAL/ALTIKA and Sentinel-3 to the water surface fraction using an hypsometric approach. The water surfaces and water storage products are then compared to precipitation data from GPM TRMM datasets and river discharge data from field data. The amplitudes and time shifts of the signals is compared based on the sub-basin definition from Hydroshed database. The dataset is then divided into years of strong and weak El-Nino signal and the anomaly is between the two dataset is compared. The results show a strong

Team Formation in Partially Observable Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Agogino, Adrian K.; Tumer, Kagan

2004-01-01

Sets of multi-agent teams often need to maximize a global utility rating the performance of the entire system where a team cannot fully observe other teams agents. Such limited observability hinders team-members trying to pursue their team utilities to take actions that also help maximize the global utility. In this article, we show how team utilities can be used in partially observable systems. Furthermore, we show how team sizes can be manipulated to provide the best compromise between having easy to learn team utilities and having them aligned with the global utility, The results show that optimally sized teams in a partially observable environments outperform one team in a fully observable environment, by up to 30%.

Construction of a patient observation system using KINECTTM

NASA Astrophysics Data System (ADS)

Miyaura, Kazunori; Kumazaki, Yu; Fukushima, Chika; Kato, Shingo; Saitoh, Hidetoshi

2014-03-01

Improvement in the positional accuracy of irradiation is expected by capturing patient motion (intra-fractional error) during irradiation. The present study reports the construction of a patient observation system using Microsoft® KINECTTM. By tracking movement, we made it possible to add a depth component to the acquired position coordinates and to display three-axis (X, Y, and Z) movement. Moreover, the developed system can be displayed in a graph which is constructed from the coordinate position at each time interval. Using the developed system, an observer can easily visualize patient movement. When the body phantom was moved a known distance in the X, Y, and Z directions, good coincidence was shown with each axis. We built a patient observation system which captures a patient's motion using KINECTTM.

An Introduction to Observing System Simulation Experiments

NASA Technical Reports Server (NTRS)

Prive, Nikki C.

2017-01-01

Observing System Simulation Experiments (OSSEs) are used to estimate the potential impact of proposed new instruments and data on numerical weather prediction. OSSEs can also be used to help design new observing platforms and to investigate the behavior of data assimilation systems. A basic overview of how to design and perform an OSSE will be given, as well as best practices and pitfalls. Some examples using the OSSE framework developed at the NASA Global Modeling and Assimilation Office will be shown.

Earth Observing System Covariance Realism Updates

NASA Technical Reports Server (NTRS)

Ojeda Romero, Juan A.; Miguel, Fred

2017-01-01

This presentation will be given at the International Earth Science Constellation Mission Operations Working Group meetings June 13-15, 2017 to discuss the Earth Observing System Covariance Realism updates.

An Observation-based Assessment of Instrument Requirements for a Future Precipitation Process Observing System

NASA Astrophysics Data System (ADS)

Nelson, E.; L'Ecuyer, T. S.; Wood, N.; Smalley, M.; Kulie, M.; Hahn, W.

2017-12-01

Global models exhibit substantial biases in the frequency, intensity, duration, and spatial scales of precipitation systems. Much of this uncertainty stems from an inadequate representation of the processes by which water is cycled between the surface and atmosphere and, in particular, those that govern the formation and maintenance of cloud systems and their propensity to form the precipitation. Progress toward improving precipitation process models requires observing systems capable of quantifying the coupling between the ice content, vertical mass fluxes, and precipitation yield of precipitating cloud systems. Spaceborne multi-frequency, Doppler radar offers a unique opportunity to address this need but the effectiveness of such a mission is heavily dependent on its ability to actually observe the processes of interest in the widest possible range of systems. Planning for a next generation precipitation process observing system should, therefore, start with a fundamental evaluation of the trade-offs between sensitivity, resolution, sampling, cost, and the overall potential scientific yield of the mission. Here we provide an initial assessment of the scientific and economic trade-space by evaluating hypothetical spaceborne multi-frequency radars using a combination of current real-world and model-derived synthetic observations. Specifically, we alter the field of view, vertical resolution, and sensitivity of a hypothetical Ka- and W-band radar system and propagate those changes through precipitation detection and intensity retrievals. The results suggest that sampling biases introduced by reducing sensitivity disproportionately affect the light rainfall and frozen precipitation regimes that are critical for warm cloud feedbacks and ice sheet mass balance, respectively. Coarser spatial resolution observations introduce regime-dependent biases in both precipitation occurrence and intensity that depend on cloud regime, with even the sign of the bias varying within a

Susquehanna River Basin Hydrologic Observing System (SRBHOS)

NASA Astrophysics Data System (ADS)

Reed, P. M.; Duffy, C. J.; Dressler, K. A.

2004-12-01

In response to the NSF-CUAHSI initiative for a national network of Hydrologic Observatories, we propose to initiate the Susquehanna River Basin Hydrologic Observing System (SRBHOS), as the northeast node. The Susquehanna has a drainage area of 71, 410 km2. From the headwaters near Cooperstown, NY, the river is formed within the glaciated Appalachian Plateau physiographic province, crossing the Valley and Ridge, then the Piedmont, before finishing its' 444 mile journey in the Coastal Plain of the Chesapeake Bay. The Susquehanna is the major source of water and nutrients to the Chesapeake. It has a rich history in resource development (logging, mining, coal, agriculture, urban and heavy industry), with an unusual resilience to environmental degradation, which continues today. The shallow Susquehanna is one of the most flood-ravaged rivers in the US with a decadal regularity of major damage from hurricane floods and rain-on-snow events. As a result of this history, it has an enormous infrastructure for climate, surface water and groundwater monitoring already in place, including the nations only regional groundwater monitoring system for drought detection. Thirty-six research institutions have formed the SRBHOS partnership to collaborate on a basin-wide network design for a new scientific observing system. Researchers at the partner universities have conducted major NSF research projects within the basin, setting the stage and showing the need for a new terrestrial hydrologic observing system. The ultimate goal of SRBHOS is to close water, energy and solute budgets from the boundary layer to the water table, extending across plot, hillslope, watershed, and river basin scales. SRBHOS is organized around an existing network of testbeds (legacy watershed sites) run by the partner universities, and research institutions. The design of the observing system, when complete, will address fundamental science questions within major physiographic regions of the basin. A nested

NASA's mission to planet Earth: Earth observing system

NASA Technical Reports Server (NTRS)

1993-01-01

The topics covered include the following: global climate change; radiation, clouds, and atmospheric water; the ocean; the troposphere - greenhouse gases; land cover and the water cycle; polar ice sheets and sea level; the stratosphere - ozone chemistry; volcanoes; the Earth Observing System (EOS) - how NASA will support studies of global climate change?; research and assessment - EOS Science Investigations; EOS Data and Information System (EOSDIS); EOS observations - instruments and spacecraft; a national international effort; and understanding the Earth System.

Considering Combined or Separated Roughness and Vegetation Effects in Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Parrens, Marie; Wigernon, Jean-Pierre; Richaume, Philippe; Al Bitar, Ahmad; Mialon, Arnaud; Fernandez-Moran, Roberto; Al-Yarri, Amen; O'Neill, Peggy; Kerr, Yann

2016-01-01

For more than six years, the Soil Moisture and Ocean Salinity (SMOS) mission has provided multi angular and full-polarization brightness temperature (TB) measurements at L-band. Geophysical products such as soil moisture (SM) and vegetation optical depth at nadir (tau(sub nad)) are retrieved by an operational algorithm using TB observations at different angles of incidence and polarizations. However, the quality of the retrievals depends on several surface effects, such as vegetation, soil roughness and texture, etc. In the microwave forward emission model used in the retrievals (L-band Microwave Emission Model, L-MEB),soil roughness is modeled with a semi-empirical equation using four main parameters (Q(sub r), H(sub r), N(sub rp), with p = H or V polarizations). At present, these parameters are calibrated with data provided by airborne studies and in situ measurements made at a local scale that is not necessarily representative of the large SMOS footprints (43 km on average) at global scale. In this study, we evaluate the impact of the calibrated values of N(sub rp) and H(sub r) on the SM and tau(sub nad) retrievals based on SMOS TB measurements (SMOS Level 3 product) over the Soil Climate Analysis Network (SCAN) network located in North America over five years (2011-2015). In this study, Qr was set equal to zero and we assumed that N(sub rH)= N(sub rV). The retrievals were performed by varying N(sub rp) from -1 to 2 by steps of 1 and H(sub r) from 0 to 0.6 by steps of 0.1. At satellite scale, the results show that combining vegetation and roughness effects in a single parameter provides the best results in terms of soil moisture retrievals, as evaluated against the in situ SM data. Even though our retrieval approach was very simplified, as we did not account for pixel heterogeneity, the accuracy we obtained in the SM retrievals was almost systematically better than those of the Level 3 product. Improved results were also obtained in terms of optical depth

Estimation of Surface Runoff in the Jucar River Basin from Rainfall Data and SMOS Soil Moisture

NASA Astrophysics Data System (ADS)

Garcia Leal, Julio A.; Estrela, Teodoro; Fidalgo, Arancha; Gabaldo, Onofre; Gonzalez Robles, Maura; Herrera Daza, Eddy; Khodayar, Samiro; Lopez-Baeza, Ernesto

2013-04-01

SMOS soil moisture values available at the closest DGG node immediately after saturation produced by the rain. The results are shown as maps of precipitation and soil moisture obtained using a V4 integration method between a linear and nearest neighbour methods. Surface runoff maps are consequently obtained using the SCS-CN equation given earlier. These results have also been compared to COSMO-CLM model simulations for the same periods. It is envisaged to obtain precipitation maps from MSG-SEVIRI data.

Promoting discovery and access to real time observations produced by regional coastal ocean observing systems

NASA Astrophysics Data System (ADS)

Anderson, D. M.; Snowden, D. P.; Bochenek, R.; Bickel, A.

2015-12-01

In the U.S. coastal waters, a network of eleven regional coastal ocean observing systems support real-time coastal and ocean observing. The platforms supported and variables acquired are diverse, ranging from current sensing high frequency (HF) radar to autonomous gliders. The system incorporates data produced by other networks and experimental systems, further increasing the breadth of the collection. Strategies promoted by the U.S. Integrated Ocean Observing System (IOOS) ensure these data are not lost at sea. Every data set deserves a description. ISO and FGDC compliant metadata enables catalog interoperability and record-sharing. Extensive use of netCDF with the Climate and Forecast convention (identifying both metadata and a structured format) is shown to be a powerful strategy to promote discovery, interoperability, and re-use of the data. To integrate specialized data which are often obscure, quality control protocols are being developed to homogenize the QC and make these data more integrate-able. Data Assembly Centers have been established to integrate some specialized streams including gliders, animal telemetry, and HF radar. Subsets of data that are ingested into the National Data Buoy Center are also routed to the Global Telecommunications System (GTS) of the World Meteorological Organization to assure wide international distribution. From the GTS, data are assimilated into now-cast and forecast models, fed to other observing systems, and used to support observation-based decision making such as forecasts, warnings, and alerts. For a few years apps were a popular way to deliver these real-time data streams to phones and tablets. Responsive and adaptive web sites are an emerging flexible strategy to provide access to the regional coastal ocean observations.

Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

NASA Astrophysics Data System (ADS)

Sure, A.; Dikshit, O.

2017-12-01

Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

Observing Natural Hazards: Tsunami, Hurricane, and El Niño Observations from the NDBC Ocean Observing System of Systems

NASA Astrophysics Data System (ADS)

O'Neil, K.; Bouchard, R.; Burnett, W. H.; Aldrich, C.

2009-12-01

The National Oceanic and Atmospheric Administration’s (NOAA) National Data Buoy Center (NDBC) operates and maintains the NDBC Ocean Observing Systems of Systems (NOOSS), comprised of 3 networks that provide critical information before and during and after extreme hazards events, such as tsunamis, hurricanes, and El Niños. While each system has its own mission, they have in common the requirement to remain on station in remote areas of the ocean to provide reliable and accurate observations. After the 2004 Sumatran Tsunami, NOAA expanded its network of tsunameters from six in the Pacific Ocean to a vast network of 39 stations providing information to Tsunami Warning Centers to enable faster and more accurate tsunami warnings for coastal communities in the Pacific, Atlantic, Caribbean and the Gulf of Mexico. The tsunameter measurements are used to detect the amplitude and period of the tsunamis, and the data can be assimilated into models for the prediction and impact of the tsunamis to coastal communities. The network has been used for the detection of tsunamis generated by earthquakes, including the 2006 and 2007 Kuril Islands, 2007 Peru, and Solomon Islands, and most recently for the 2009 Dusky Sound, New Zealand earthquake. In August 2009, the NOAA adjusted its 2009 Atlantic Hurricane Seasonal Outlooks from above normal to near or below normal activity, primarily due to a strengthening El Niño. A key component in the detection of that El Niño was the Tropical Atmosphere Ocean Array (TAO) operated by NDBC. TAO provides real-time data for improved detection, understanding, and prediction of El Niño and La Niña. The 55-buoy TAO array spans the central and eastern equatorial Pacific providing real-time and post-deployment recovery data to support climate analysis and forecasts. Although, in this case, the El Niño benefits the tropical Atlantic, the alternate manifestation, La Niña typically enhances hurricane activity in the Atlantic. The various phases of

Exploring our outer solar system - The Giant Planet System Observers

NASA Astrophysics Data System (ADS)

Cooper, J. F.; Sittler, E. C., Jr.; Sturner, S. J.; Pitman, J. T.

As space-faring peoples now work together to plan and implement future missions that robotically prepare for landing humans to explore the Moon, and later Mars, the time is right to develop evolutionary approaches for extending this next generation of exploration beyond Earth's terrestrial planet neighbors to the realm of the giant planets. And while initial fly-by missions have been hugely successful in providing exploratory surveys of what lies beyond Mars, we need to consider now what robotic precursor mission capabilities we need to emplace that prepare us properly, and comprehensively, for long-term robotic exploration, and eventual human habitation, beyond Mars to the outer reaches of our solar system. To develop practical strategies that can establish prioritized capabilities, and then develop a means for achieving those capabilities within realistic budget and technology considerations, and in reasonable timeframes, is our challenge. We suggest one component of such an approach to future outer planets exploration is a series of Giant Planets System Observer (GPSO) missions that provide for long- duration observations, monitoring, and relay functions to help advance our understanding of the outer planets and thereby enable a sound basis for planning their eventual exploration by humans. We envision these missions as being comparable to taking Hubble-class remote-sensing facilities, along with the space physics capabilities of long-lived geospace and heliospheric missions, to the giant planet systems and dedicating long observing lifetimes (HST, 16 yr.; Voyagers, 29 yr.) to the exhaustive study and characterization of those systems. GPSO missions could feature 20-yr+ extended mission lifetimes, direct inject trajectories to maximize useful lifetime on target, placement strategies that take advantage of natural environment shielding (e.g., Ganymede magnetic field) where possible, orbit designs having favorable planetary system viewing geometries, comprehensive

Spanish Earth Observation Satellite System

NASA Astrophysics Data System (ADS)

Borges, A.; Cerezo, F.; Fernandez, M.; Lomba, J.; Lopez, M.; Moreno, J.; Neira, A.; Quintana, C.; Torres, J.; Trigo, R.; Urena, J.; Vega, E.; Vez, E.

2010-12-01

The Spanish Ministry of Industry, Tourism and Trade (MITyC) and the Ministry of Defense (MoD) signed an agreement in 2007 for the development of a "Spanish Earth Observation Satellite System" based, in first instance, on two satellites: a high resolution optical satellite, called SEOSAT/Ingenio, and a radar satellite based on SAR technology, called SEOSAR/Paz. SEOSAT/Ingenio is managed by MITyC through the Centre for the Development of Industrial Technology (CDTI), with technical and contractual support from the European Space Agency (ESA). HISDESA T together with the Spanish Instituto Nacional de Técnica Aeroespacial (INTA, National Institute for Aerospace Technology) will be responsible for the in-orbit operation and the commercial operation of both satellites, and for the technical management of SEOSAR/Paz on behalf of the MoD. In both cases EADS CASA Espacio (ECE) is the prime contractor leading the industrial consortia. The ground segment development will be assigned to a Spanish consortium. This system is the most important contribution of Spain to the European Programme Global Monitoring for Environment and Security, GMES. This paper presents the Spanish Earth Observation Satellite System focusing on SEOSA T/Ingenio Programme and with special emphasis in the potential contribution to the ESA Third Party Missions Programme and to the Global Monitoring for Environment and Security initiative (GMES) Data Access.

NASA's Earth Observing System Data and Information System - EOSDIS

NASA Technical Reports Server (NTRS)

Ramapriyan, Hampapuram K.

2011-01-01

This slide presentation reviews the work of NASA's Earth Observing System Data and Information System (EOSDIS), a petabyte-scale archive of environmental data that supports global climate change research. The Earth Science Data Systems provide end-to-end capabilities to deliver data and information products to users in support of understanding the Earth system. The presentation contains photographs from space of recent events, (i.e., the effects of the tsunami in Japan, and the wildfires in Australia.) It also includes details of the Data Centers that provide the data to EOSDIS and Science Investigator-led Processing Systems. Information about the Land, Atmosphere Near-real-time Capability for EOS (LANCE) and some of the uses that the system has made possible are reviewed. Also included is information about how to access the data, and evolutionary plans for the future of the system.

A system decomposition approach to the design of functional observers

NASA Astrophysics Data System (ADS)

Fernando, Tyrone; Trinh, Hieu

2014-09-01

This paper reports a system decomposition that allows the construction of a minimum-order functional observer using a state observer design approach. The system decomposition translates the functional observer design problem to that of a state observer for a smaller decomposed subsystem. Functional observability indices are introduced, and a closed-form expression for the minimum order required for a functional observer is derived in terms of those functional observability indices.

The Australian Integrated Marine Observing System

NASA Astrophysics Data System (ADS)

Proctor, R.; Meyers, G.; Roughan, M.; Operators, I.

2008-12-01

The Integrated Marine Observing System (IMOS) is a 92M project established with 50M from the National Collaborative Research Infrastructure Strategy (NCRIS) and co-investments from 10 operators including Universities and government agencies (see below). It is a nationally distributed set of equipment established and maintained at sea, oceanographic data and information services that collectively will contribute to meeting the needs of marine research in both open oceans and over the continental shelf around Australia. In particular, if sustained in the long term, it will permit identification and management of climate change in the marine environment, an area of research that is as yet almost a blank page, studies relevant to conservation of marine biodiversity and research on the role of the oceans in the climate system. While as an NCRIS project IMOS is intended to support research, the data streams are also useful for many societal, environmental and economic applications, such as management of offshore industries, safety at sea, management of marine ecosystems and fisheries and tourism. The infrastructure also contributes to Australia's commitments to international programs of ocean observing and international conventions, such as the 1982 Law of the Sea Convention that established the Australian Exclusive Economic Zone, the United Nations Framework Convention on Climate Change, the Global Ocean Observing System and the intergovernmental coordinating activity Global Earth Observation System of Systems. IMOS is made up of nine national facilities that collect data, using different components of infrastructure and instruments, and two facilities that manage and provide access to data and enhanced data products, one for in situ data and a second for remotely sensed satellite data. The observing facilities include three for the open (bluewater) ocean (Argo Australia, Enhanced Ships of Opportunity and Southern Ocean Time Series), three facilities for coastal

GENERAL EARTHQUAKE-OBSERVATION SYSTEM (GEOS).

USGS Publications Warehouse

Borcherdt, R.D.; Fletcher, Joe B.; Jensen, E.G.; Maxwell, G.L.; VanSchaack, J.R.; Warrick, R.E.; Cranswick, E.; Johnston, M.J.S.; McClearn, R.

1985-01-01

Microprocessor technology has permitted the development of a General Earthquake-Observation System (GEOS) useful for most seismic applications. Central-processing-unit control via robust software of system functions that are isolated on hardware modules permits field adaptability of the system to a wide variety of active and passive seismic experiments and straightforward modification for incorporation of improvements in technology. Various laboratory tests and numerous deployments of a set of the systems in the field have confirmed design goals, including: wide linear dynamic range (16 bit/96 dB); broad bandwidth (36 hr to 600 Hz; greater than 36 hr available); selectable sensor-type (accelerometer, seismometer, dilatometer); selectable channels (1 to 6); selectable record mode (continuous, preset, trigger); large data capacity (1. 4 to 60 Mbytes); selectable time standard (WWVB, master, manual); automatic self-calibration; simple field operation; full capability to adapt system in the field to a wide variety of experiments; low power; portability; and modest costs. System design goals for a microcomputer-controlled system with modular software and hardware components as implemented on the GEOS are presented. The systems have been deployed for 15 experiments, including: studies of near-source strong motion; high-frequency microearthquakes; crustal structure; down-hole wave propagation; teleseismicity; and earth-tidal strains.

A reduced adaptive observer for multivariable systems. [using reduced dynamic ordering

NASA Technical Reports Server (NTRS)

Carroll, R. L.; Lindorff, D. P.

1973-01-01

An adaptive observer for multivariable systems is presented for which the dynamic order of the observer is reduced, subject to mild restrictions. The observer structure depends directly upon the multivariable structure of the system rather than a transformation to a single-output system. The number of adaptive gains is at most the sum of the order of the system and the number of input parameters being adapted. Moreover, for the relatively frequent specific cases for which the number of required adaptive gains is less than the sum of system order and input parameters, the number of these gains is easily determined by inspection of the system structure. This adaptive observer possesses all the properties ascribed to the single-input single-output adpative observer. Like the other adaptive observers some restriction is required of the allowable system command input to guarantee convergence of the adaptive algorithm, but the restriction is more lenient than that required by the full-order multivariable observer. This reduced observer is not restricted to cycle systems.

The wireless networking system of Earthquake precursor mobile field observation

NASA Astrophysics Data System (ADS)

Wang, C.; Teng, Y.; Wang, X.; Fan, X.; Wang, X.

2012-12-01

The mobile field observation network could be real-time, reliably record and transmit large amounts of data, strengthen the physical signal observations in specific regions and specific period, it can improve the monitoring capacity and abnormal tracking capability. According to the features of scatter everywhere, a large number of current earthquake precursor observation measuring points, networking technology is based on wireless broadband accessing McWILL system, the communication system of earthquake precursor mobile field observation would real-time, reliably transmit large amounts of data to the monitoring center from measuring points through the connection about equipment and wireless accessing system, broadband wireless access system and precursor mobile observation management center system, thereby implementing remote instrument monitoring and data transmition. At present, the earthquake precursor field mobile observation network technology has been applied to fluxgate magnetometer array geomagnetic observations of Tianzhu, Xichang,and Xinjiang, it can be real-time monitoring the working status of the observational instruments of large area laid after the last two or three years, large scale field operation. Therefore, it can get geomagnetic field data of the local refinement regions and provide high-quality observational data for impending earthquake tracking forecast. Although, wireless networking technology is very suitable for mobile field observation with the features of simple, flexible networking etc, it also has the phenomenon of packet loss etc when transmitting a large number of observational data due to the wireless relatively weak signal and narrow bandwidth. In view of high sampling rate instruments, this project uses data compression and effectively solves the problem of data transmission packet loss; Control commands, status data and observational data transmission use different priorities and means, which control the packet loss rate within

Observing System Forecast Experiments at the DAO

NASA Technical Reports Server (NTRS)

Atlas, Robert

2001-01-01

Since the advent of meteorological satellites in the 1960's, numerous experiments have been conducted in order to evaluate the impact of these and other data on atmospheric analysis and prediction. Such studies have included both OSE'S and OSSE's. The OSE's were conducted to evaluate the impact of specific observations or classes of observations on analyses and forecasts. Such experiments have been performed for selected types of conventional data and for various satellite data sets as they became available. (See for example the 1989 ECMWF/EUMETSAT workshop proceedings on "The use of satellite data in operational numerical weather prediction" and the references contained therein.) The ODYSSEY were conducted to evaluate the potential for future observing systems to improve Numerical Weather Prediction NWP and to plan for the Global Weather Experiment and more recently for EVANS (Atlas et al., 1985a; Arnold and Day, 1986; Hoffman et al., 1990). In addition, OSSE's have been run to evaluate trade-offs in the design of observing systems and observing networks (Atlas and Emmitt, 1991; Rohaly and Krishnamurti, 1993), and to test new methodology for data assimilation (Atlas and Bloom, 1989).

NASA's Earth Observing Data and Information System

NASA Technical Reports Server (NTRS)

Mitchell, Andrew E.; Behnke, Jeanne; Lowe, Dawn; Ramapriyan, H. K.

2009-01-01

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of NASA Earth observation program for over 10 years. It is one of the largest civilian science information system in the US, performing ingest, archive and distribution of over 3 terabytes of data per day much of which is from NASA s flagship missions Terra, Aqua and Aura. The system supports a variety of science disciplines including polar processes, land cover change, radiation budget, and most especially global climate change. The EOSDIS data centers, collocated with centers of science discipline expertise, archive and distribute standard data products produced by science investigator-led processing systems. Key to the success of EOSDIS is the concept of core versus community requirements. EOSDIS supports a core set of services to meet specific NASA needs and relies on community-developed services to meet specific user needs. EOSDIS offers a metadata registry, ECHO (Earth Observing System Clearinghouse), through which the scientific community can easily discover and exchange NASA s Earth science data and services. Users can search, manage, and access the contents of ECHO s registries (data and services) through user-developed and community-tailored interfaces or clients. The ECHO framework has become the primary access point for cross-Data Center search-and-order of EOSDIS and other Earth Science data holdings archived at the EOSDIS data centers. ECHO s Warehouse Inventory Search Tool (WIST) is the primary web-based client for discovering and ordering cross-discipline data from the EOSDIS data centers. The architecture of the EOSDIS provides a platform for the publication, discovery, understanding and access to NASA s Earth Observation resources and allows for easy integration of new datasets. The EOSDIS also has developed several methods for incorporating socioeconomic data into its data collection. Over the years, we have developed several methods for determining

NASDA's earth observation satellite data archive policy for the earth observation data and information system (EOIS)

NASA Technical Reports Server (NTRS)

Sobue, Shin-ichi; Yoshida, Fumiyoshi; Ochiai, Osamu

1996-01-01

NASDA's new Advanced Earth Observing Satellite (ADEOS) is scheduled for launch in August, 1996. ADEOS carries 8 sensors to observe earth environmental phenomena and sends their data to NASDA, NASA, and other foreign ground stations around the world. The downlink data bit rate for ADEOS is 126 MB/s and the total volume of data is about 100 GB per day. To archive and manage such a large quantity of data with high reliability and easy accessibility it was necessary to develop a new mass storage system with a catalogue information database using advanced database management technology. The data will be archived and maintained in the Master Data Storage Subsystem (MDSS) which is one subsystem in NASDA's new Earth Observation data and Information System (EOIS). The MDSS is based on a SONY ID1 digital tape robotics system. This paper provides an overview of the EOIS system, with a focus on the Master Data Storage Subsystem and the NASDA Earth Observation Center (EOC) archive policy for earth observation satellite data.

HARMFUL ALGAL BLOOMS OBSERVING SYSTEM PILOT PROJECT

EPA Science Inventory

The HABSOS Pilot Project is being developed through a partnership of federal, state and academic organizations as proof-of-concept for a coastal observing system in the Gulf of Mexico. The goal is to design a HAB data management system and develop the regional communication infra...

Enhancing the USDA Global Crop Assessment Decision Support System Using SMAP Soil Moisture Data

NASA Astrophysics Data System (ADS)

Bolten, J. D.; Mladenova, I. E.; Crow, W. T.; Reynolds, C. A.

2016-12-01

The Foreign Agricultural Services (FAS) is a subdivision of U.S. Department of Agriculture (USDA) that is in charge with providing information on current and expected crop supply and demand estimates. Knowledge of the amount of water in the root zone is an essential source of information for the crop analysts as it governs the crop development and crop growth, which in turn determine the end-of-season yields. USDA FAS currently relies on root zone soil moisture (RZSM) estimates generated using the modified two-layer Palmer Model (PM). PM is a simple water-balance hydrologic model that is driven by daily precipitation observations and minimum and maximum temperature data. These forcing data are based on ground meteorological station measurements from the World Meteorological Organization (WMO), and gridded weather data from the former U.S. Air Force Weather Agency (AFWA), currently called U.S. Air Force 557th Weather Wing. The PM was extended by adding a data assimilation (DA) unit that provides the opportunity to routinely ingest satellite-based soil moisture observations. This allows us to adjust for precipitation-related inaccuracies and enhance the quality of the PM soil moisture estimates. The current operational DA system is based on a 1-D Ensample Kalman Filter approach and relies on observations obtained from the Soil Moisture Ocean Salinity Mission (SMOS). Our talk will demonstrate the value of assimilating two satellite products (i.e. a passive and active) and discuss work that is done in preparation for ingesting soil moisture observations from the Soil Moisture Active Passive (SMAP) mission.

Earth Observation System Flight Dynamics System Covariance Realism

NASA Technical Reports Server (NTRS)

Zaidi, Waqar H.; Tracewell, David

2016-01-01

This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.

Weather Observation Systems and Efficiency of Fighting Forest Fires

NASA Astrophysics Data System (ADS)

Khabarov, N.; Moltchanova, E.; Obersteiner, M.

2007-12-01

Weather observation is an essential component of modern forest fire management systems. Satellite and in-situ based weather observation systems might help to reduce forest loss, human casualties and destruction of economic capital. In this paper, we develop and apply a methodology to assess the benefits of various weather observation systems on reductions of burned area due to early fire detection. In particular, we consider a model where the air patrolling schedule is determined by a fire hazard index. The index is computed from gridded daily weather data for the area covering parts Spain and Portugal. We conduct a number of simulation experiments. First, the resolution of the original data set is artificially reduced. The reduction of the total forest burned area associated with air patrolling based on a finer weather grid indicates the benefit of using higher spatially resolved weather observations. Second, we consider a stochastic model to simulate forest fires and explore the sensitivity of the model with respect to the quality of input data. The analysis of combination of satellite and ground monitoring reveals potential cost saving due to a "system of systems effect" and substantial reduction in burned area. Finally, we estimate the marginal improvement schedule for loss of life and economic capital as a function of the improved fire observing system.

Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

2016-01-01

An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system

NASA Astrophysics Data System (ADS)

Ciais, P.; Dolman, A. J.; Bombelli, A.; Duren, R.; Peregon, A.; Rayner, P. J.; Miller, C.; Gobron, N.; Kinderman, G.; Marland, G.; Gruber, N.; Chevallier, F.; Andres, R. J.; Balsamo, G.; Bopp, L.; Bréon, F.-M.; Broquet, G.; Dargaville, R.; Battin, T. J.; Borges, A.; Bovensmann, H.; Buchwitz, M.; Butler, J.; Canadell, J. G.; Cook, R. B.; DeFries, R.; Engelen, R.; Gurney, K. R.; Heinze, C.; Heimann, M.; Held, A.; Henry, M.; Law, B.; Luyssaert, S.; Miller, J.; Moriyama, T.; Moulin, C.; Myneni, R. B.; Nussli, C.; Obersteiner, M.; Ojima, D.; Pan, Y.; Paris, J.-D.; Piao, S. L.; Poulter, B.; Plummer, S.; Quegan, S.; Raymond, P.; Reichstein, M.; Rivier, L.; Sabine, C.; Schimel, D.; Tarasova, O.; Valentini, R.; Wang, R.; van der Werf, G.; Wickland, D.; Williams, M.; Zehner, C.

2014-07-01

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations. We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO2 and CH4 fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data. Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

NASA Technical Reports Server (NTRS)

Larson, Jay W.

1998-01-01

Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Virtual Observation System for Earth System Model: An Application to ACME Land Model Simulations

DOE PAGES

Wang, Dali; Yuan, Fengming; Hernandez, Benjamin; ...

2017-01-01

Investigating and evaluating physical-chemical-biological processes within an Earth system model (EMS) can be very challenging due to the complexity of both model design and software implementation. A virtual observation system (VOS) is presented to enable interactive observation of these processes during system simulation. Based on advance computing technologies, such as compiler-based software analysis, automatic code instrumentation, and high-performance data transport, the VOS provides run-time observation capability, in-situ data analytics for Earth system model simulation, model behavior adjustment opportunities through simulation steering. A VOS for a terrestrial land model simulation within the Accelerated Climate Modeling for Energy model is also presentedmore » to demonstrate the implementation details and system innovations.« less

Observation and integrated Earth-system science: A roadmap for 2016-2025

NASA Astrophysics Data System (ADS)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, Venkatachalam; Trenberth, Kevin; Asrar, Ghassem; Balmaseda, Magdalena; Burrows, John P.; Ciais, Philippe; Drinkwater, Mark; Friedlingstein, Pierre; Gobron, Nadine; Guilyardi, Eric; Halpern, David; Heimann, Martin; Johannessen, Johnny; Levelt, Pieternel F.; Lopez-Baeza, Ernesto; Penner, Joyce; Scholes, Robert; Shepherd, Ted

2016-05-01

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types of observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016-2025 and some of the issues to be faced. Observations that are organised on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the

Nonlinear observer designs for fuel cell power systems

NASA Astrophysics Data System (ADS)

Gorgun, Haluk

A fuel cell is an electrochemical device that combines hydrogen and oxygen, with the aid of electro-catalysts, to produce electricity. A fuel cell consists of a negatively charged anode, a positively charged cathode and an electrolyte, which transports protons or ions. A low temperature fuel cell has an electrical potential of about 0.7 Volt when generating a current density of 300--500 mA/cm2. Practical fuel cell power systems will require a combination of several cells in series (a stack) to satisfy the voltage requirements of specific applications. Fuel cells are suitable for a potentially wide variety of applications, from stationary power generation in the range of hundreds of megawatts to portable electronics in the range of a couple of watts. Efficient operation of a fuel cell system requires advanced feedback control designs. Reliable measurements from the system are necessary to implement such designs. However, most of the commercially available sensors do not operate properly in the reformate and humidified gas streams in fuel cell systems. Sensors working varying degrees of success are too big and costly, and sensors that are potentially low cost are not reliable or do not have the required life time [28]. Observer designs would eliminate sensor needs for measurements, and make feedback control implementable. Since the fuel cell system dynamics are highly nonlinear, observer design is not an easy task. In this study we aim to develop nonlinear observer design methods applicable to fuel cell systems. In part I of the thesis we design an observer to estimate the hydrogen partial pressure in the anode channel. We treat inlet partial pressure as an unknown slowly varying parameter and develop an adaptive observer that employs a nonlinear voltage injection term. However in this design Fuel Processing System (FPS) dynamics are not modelled, and their effect on the anode dynamics are treated as plant uncertainty. In part II of the thesis we study the FPS

Carbon Dioxide Observational Platform System (CO-OPS), feasibility study

NASA Technical Reports Server (NTRS)

Bouquet, D. L.; Hall, D. W.; Mcelveen, R. P.

1987-01-01

The Carbon Dioxide Observational Platform System (CO-OPS) is a near-space, geostationary, multi-user, unmanned microwave powered monitoring platform system. This systems engineering feasibility study addressed identified existing requirements such as: carbon dioxide observational data requirements, communications requirements, and eye-in-the-sky requirements of other groups like the Defense Department, the Forestry Service, and the Coast Guard. In addition, potential applications in: earth system science, space system sciences, and test and verification (satellite sensors and data management techniques) were considered. The eleven month effort is summarized. Past work and methods of gathering the required observational data were assessed and rough-order-of magnitude cost estimates have shown the CO-OPS system to be most cost effective (less than $30 million within a 10 year lifetime). It was also concluded that there are no technical, schedule, or obstacles that would prevent achieving the objectives of the total 5-year CO-OPS program.

JWST Planetary Observations Within the Solar System

NASA Technical Reports Server (NTRS)

Lunine, Jonathan; Hammel, Heidi; Schaller, Emily; Sonneborn, George; Orton, Glenn; Rieke, George; Rieke, Marcia

2010-01-01

JWST provides capabilities unmatched by other telescopic facilities in the near to mid infrared part of the electromagnetic spectrum. Its combination of broad wavelength range, high sensitivity and near diffraction-limited imaging around two microns wavelength make it a high value facility for a variety of Solar System targets. Beyond Neptune, a class of cold, large bodies that include Pluto, Triton and Eris exhibits surface deposits of nitrogen, methane, and other molecules that are poorly observed from the ground, but for which JWST might provide spectral mapping at high sensitivity and spatial resolution difficult to match with the current generation of ground-based observatories. The observatory will also provide unique sensitivity in a variety of near and mid infrared windows for observing relatively deep into the atmospheres of Uranus and Neptune, searching there for minor species. It will examine the Jovian aurora in a wavelength regime where the background atmosphere is dark. Special provision of a subarray observing strategy may allow observation of Jupiter and Saturn over a larger wavelength range despite their large surface brightnesses, allowing for detailed observation of transient phenomena including large scale storms and impact-generation disturbances. JWST's observations of Saturn's moon Titan will overlap with and go beyond the 2017 end-of-mission for Cassini, providing an important extension to the time-series of meteorological studies for much of northern hemisphere summer. It will overlap with a number of other planetary missions to targets for which JWST can make unique types of observations. JWST provides a platform for linking solar system and extrasolar planet studies through its unique observational capabilities in both arenas.

Computerized Systems for Collecting Real-Time Observational Data.

ERIC Educational Resources Information Center

Kahng, SungWoo; Iwata, Brian

1998-01-01

A survey of 15 developers of computerized real-time observation systems found many systems have incorporated laptop or handheld computers as well as bar-code scanners. Most systems used IBM-compatible software, and ranged from free to complete systems costing more than $1,500. Data analysis programs were included with most programs. (Author/CR)

A net-centric system of services model for the Integrated Earth Observation System (IEOS) and the Integrated Ocean Observing System (IOOS)

NASA Astrophysics Data System (ADS)

Ardanuy, Philip; Bensman, Ed; Bergen, Bill; Chen, Bob; Griffith, Frank; Sutton, Cary; Hood, Carroll; Ritchie, Adrian; Tarro, Andre

2006-08-01

This paper considers an evolved technique for significantly enhanced enterprise-level data processing, reprocessing, archival, dissemination, and utilization. There is today a robust working paradigm established with the Advanced Weather Interactive Processing System (AWIPS)-NOAA/NWS's information integration and fusion capability. This process model extends vertically, and seamlessly, from environmental sensing through the direct delivery of societal benefit. NWS, via AWIPS, is the primary source of weather forecast and warning information in the nation. AWIPS is the tested and proven "the nerve center of operations" at all 122 NWS Weather Forecast Offices (WFOs) and 13 River Forecast Centers (RFCs). However, additional line organizations whose role in satisfying NOAA's five mission goals (ecosystems, climate, weather & water, commerce & transportation, and mission support) in multiple program areas might be facilitated through utilization of AWIPS-like functionalities, including the National Marine Fisheries Service (NMFS); National Environmental Satellite, Data, and Information Service (NESDIS); Office of Oceanic & Atmospheric Research (OAR); and the National Ocean Service (NOS). In addition to NOAA's mission goals, there are nine diverse, recommended, and important societal benefit areas in the US Integrated Earth Observation System (IEOS). This paper shows how the satisfaction of this suite of goals and benefit areas can be optimized by leveraging several key ingredients: (1) the evolution of AWIPS towards a net-centric system of services concept of operations; (2) infusion of technologies and concepts from pathfinder systems; (3) the development of new observing systems targeted at deliberate, and not just serendipitous, societal benefit; and (4) the diverse, nested local, regional, national, and international scales of the different benefits and goal areas, and their interoperability and interplay across the system of systems.

The Earth Phenomena Observing System: Intelligent Autonomy for Satellite Operations

NASA Technical Reports Server (NTRS)

Ricard, Michael; Abramson, Mark; Carter, David; Kolitz, Stephan

2003-01-01

Earth monitoring systems of the future may include large numbers of inexpensive small satellites, tasked in a coordinated fashion to observe both long term and transient targets. For best performance, a tool which helps operators optimally assign targets to satellites will be required. We present the design of algorithms developed for real-time optimized autonomous planning of large numbers of small single-sensor Earth observation satellites. The algorithms will reduce requirements on the human operators of such a system of satellites, ensure good utilization of system resources, and provide the capability to dynamically respond to temporal terrestrial phenomena. Our initial real-time system model consists of approximately 100 satellites and large number of points of interest on Earth (e.g., hurricanes, volcanoes, and forest fires) with the objective to maximize the total science value of observations over time. Several options for calculating the science value of observations include the following: 1) total observation time, 2) number of observations, and the 3) quality (a function of e.g., sensor type, range, slant angle) of the observations. An integrated approach using integer programming, optimization and astrodynamics is used to calculate optimized observation and sensor tasking plans.

Building a Global Earth Observation System of Systems (GEOSS) and Its Interoperability Challenges

NASA Astrophysics Data System (ADS)

Ryan, B. J.

2015-12-01

Launched in 2005 by industrialized nations, the Group on Earth Observations (GEO) began building the Global Earth Observation System of Systems (GEOSS). Consisting of both a policy framework, and an information infrastructure, GEOSS, was intended to link and/or integrate the multitude of Earth observation systems, primarily operated by its Member Countries and Participating Organizations, so that users could more readily benefit from global information assets for a number of society's key environmental issues. It was recognized that having ready access to observations from multiple systems was a prerequisite for both environmental decision-making, as well as economic development. From the very start, it was also recognized that the shear complexity of the Earth's system cannot be captured by any single observation system, and that a federated, interoperable approach was necessary. While this international effort has met with much success, primarily in advancing broad, open data policies and practices, challenges remain. In 2014 (Geneva, Switzerland) and 2015 (Mexico City, Mexico), Ministers from GEO's Member Countries, including the European Commission, came together to assess progress made during the first decade (2005 to 2015), and approve implementation strategies and mechanisms for the second decade (2016 to 2025), respectively. The approved implementation strategies and mechanisms are intended to advance GEOSS development thereby facilitating the increased uptake of Earth observations for informed decision-making. Clearly there are interoperability challenges that are technological in nature, and several will be discussed in this presentation. There are, however, interoperability challenges that can be better characterized as economic, governmental and/or political in nature, and these will be discussed as well. With the emergence of the Sustainable Development Goals (SDGs), the World Conference on Disaster Risk Reduction (WCDRR), and the United Nations

Current systematic carbon-cycle observations and the need for implementing a policy-relevant carbon observing system

Treesearch

P. Ciais; A. J. Dolman; A. Bombelli; R. Duren; A. Peregon; P. J. Rayner; C. Miller; N. Gobron; G. Kinderman; G. Marland; N. Gruber; F. Chevallier; R. J. Andres; G. Balsamo; L. Bopp; F.-M. Bréon; G. Broquet; R. Dargaville; T. J. Battin; A. Borges; H. Bovensmann; M. Buchwitz; J. Butler; J. G. Canadell; R. B. Cook; R. DeFries; R. Engelen; K. R. Gurney; C. Heinze; M. Heimann; A. Held; M. Henry; B. Law; S. Luyssaert; J. Miller; T. Moriyama; C. Moulin; R. B. Myneni; C. Nussli; M. Obersteiner; D. Ojima; Y. Pan; J.-D. Paris; S. L. Piao; B. Poulter; S. Plummer; S. Quegan; P. Raymond; M. Reichstein; L. Rivier; C. Sabine; D. Schimel; O. Tarasova; R. Valentini; R. Wang; G. van der Werf; D. Wickland; M. Williams; C. Zehner

2014-01-01

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires...

Temporal Stability of Soil Moisture and Radar Backscatter Observed by the Advanced Synthetic Aperture Radar (ASAR)

PubMed Central

Wagner, Wolfgang; Pathe, Carsten; Doubkova, Marcela; Sabel, Daniel; Bartsch, Annett; Hasenauer, Stefan; Blöschl, Günter; Scipal, Klaus; Martínez-Fernández, José; Löw, Alexander

2008-01-01

The high spatio-temporal variability of soil moisture is the result of atmospheric forcing and redistribution processes related to terrain, soil, and vegetation characteristics. Despite this high variability, many field studies have shown that in the temporal domain soil moisture measured at specific locations is correlated to the mean soil moisture content over an area. Since the measurements taken by Synthetic Aperture Radar (SAR) instruments are very sensitive to soil moisture it is hypothesized that the temporally stable soil moisture patterns are reflected in the radar backscatter measurements. To verify this hypothesis 73 Wide Swath (WS) images have been acquired by the ENVISAT Advanced Synthetic Aperture Radar (ASAR) over the REMEDHUS soil moisture network located in the Duero basin, Spain. It is found that a time-invariant linear relationship is well suited for relating local scale (pixel) and regional scale (50 km) backscatter. The observed linear model coefficients can be estimated by considering the scattering properties of the terrain and vegetation and the soil moisture scaling properties. For both linear model coefficients, the relative error between observed and modelled values is less than 5 % and the coefficient of determination (R2) is 86 %. The results are of relevance for interpreting and downscaling coarse resolution soil moisture data retrieved from active (METOP ASCAT) and passive (SMOS, AMSR-E) instruments. PMID:27879759

"New Space Explosion" and Earth Observing System Capabilities

NASA Astrophysics Data System (ADS)

Stensaas, G. L.; Casey, K.; Snyder, G. I.; Christopherson, J.

2017-12-01

This presentation will describe recent developments in spaceborne remote sensing, including introduction to some of the increasing number of new firms entering the market, along with new systems and successes from established players, as well as industry consolidation reactions to these developments from communities of users. The information in this presentation will include inputs from the results of the Joint Agency Commercial Imagery Evaluation (JACIE) 2017 Civil Commercial Imagery Evaluation Workshop and the use of the US Geological Survey's Requirements Capabilities and Analysis for Earth Observation (RCA-EO) centralized Earth observing systems database and how system performance parameters are used with user science applications requirements.

Observations of the Pluto-Charon System

NASA Technical Reports Server (NTRS)

Tholen, David J.

2004-01-01

We are continuing the analysis of adaptive optics observations of the Pluto-Charon system, with the goal of confirming the orbital eccentricity reported by Tholen and Bule (1997). Previous work on these data, obtained with the Hokupa's adaptive optics system and Gemini North and reported by Tholea (2002), utilized only a portion of the full set of 348 images taken on 8 nights between 2001 and 2002, and was based on a preliminary calibration of the image scale and position angle of the detector. For each of the three observing runs, independent calibrations were performed using the motion of an asteroid past a fixed stellar source to remove any minor differences in the way the instrument was mounted on the telescope for each run. The image scales determined for each run are good to better than 1 part in 1000, while the individual position angle determinations are good at least 0.1 deg. The preliminary analysis reported at last year's DPS meeting indicated consistency with the orbit determined from the HST observations acquired a decade ago, however, a more careful analysis yields a longitude of periapsis of 132.2 degrees plus or minus 9.3 degrees, disagreeing with the HST results: Finally, possible explanation for the differences in orbital solutions are considered.

The disagreement between the ideal observer and human observers in hardware and software imaging system optimization: theoretical explanations and evidence

NASA Astrophysics Data System (ADS)

He, Xin

2017-03-01

The ideal observer is widely used in imaging system optimization. One practical question remains open: do the ideal and human observers have the same preference in system optimization and evaluation? Based on the ideal observer's mathematical properties proposed by Barrett et. al. and the empirical properties of human observers investigated by Myers et. al., I attempt to pursue the general rules regarding the applicability of the ideal observer in system optimization. Particularly, in software optimization, the ideal observer pursues data conservation while humans pursue data presentation or perception. In hardware optimization, the ideal observer pursues a system with the maximum total information, while humans pursue a system with the maximum selected (e.g., certain frequency bands) information. These different objectives may result in different system optimizations between human and the ideal observers. Thus, an ideal observer optimized system is not necessarily optimal for humans. I cite empirical evidence in search and detection tasks, in hardware and software evaluation, in X-ray CT, pinhole imaging, as well as emission computed tomography to corroborate the claims. (Disclaimer: the views expressed in this work do not necessarily represent those of the FDA)

Altimetric system: Earth observing system. Volume 2h: Panel report

NASA Technical Reports Server (NTRS)

Bindschadler, Robert A.; Born, George; Chase, Robert R. P.; Fu, Lee-Lueng; Mouginis-Mark, Peter; Parsons, Chester; Tapley, Byron

1987-01-01

A rationale and recommendations for planning, implementing, and operating an altimetric system aboard the Earth observing system (Eos) spacecraft is provided. In keeping with the recommendations of the Eos Science and Mission Requirements Working Group, a complete altimetric system is defined that is capable of perpetuating the data set to be derived from TOPEX/Poseidon, enabling key scientific questions to be addressed. Since the scientific utility and technical maturity of spaceborne radar altimeters is well documented, the discussion is limited to highlighting those Eos-specific considerations that materially impact upon radar altimetric measurements.

Economic Value of an Advanced Climate Observing System

NASA Astrophysics Data System (ADS)

Wielicki, B. A.; Cooke, R.; Young, D. F.; Mlynczak, M. G.

2013-12-01

Scientific missions increasingly need to show the monetary value of knowledge advances in budget-constrained environments. For example, suppose a climate science mission promises to yield decisive information on the rate of human caused global warming within a shortened time frame. How much should society be willing to pay for this knowledge today? The US interagency memo on the social cost of carbon (SCC) creates a standard yardstick for valuing damages from carbon emissions. We illustrate how value of information (VOI) calculations can be used to monetize the relative value of different climate observations. We follow the SCC, setting uncertainty in climate sensitivity to a truncated Roe and Baker (2007) distribution, setting discount rates of 2.5%, 3% and 5%, and using one of the Integrated Assessment Models sanctioned in SCC (DICE, Nordhaus 2008). We consider three mitigation scenarios: Business as Usual (BAU), a moderate mitigation response DICE Optimal, and a strong response scenario (Stern). To illustrate results, suppose that we are on the BAU emissions scenario, and that we would switch to the Stern emissions path if we learn with 90% confidence that the decadal rate of temperature change reaches or exceeds 0.2 C/decade. Under the SCC assumptions, the year in which this happens, if it happens, depends on the uncertain climate sensitivity and on the emissions path. The year in which we become 90% certain that it happens depends, in addition, on our Earth observations, their accuracy, and their completeness. The basic concept is that more accurate observations can shorten the time for societal decisions. The economic value of the resulting averted damages depends on the discount rate, and the years in which the damages occur. A new climate observation would be economically justified if the net present value (NPV) of the difference in averted damages, relative to the existing systems, exceeds the NPV of the system costs. Our results (Cooke et al. 2013

OBSERVATIONS OF HIERARCHICAL SOLAR-TYPE MULTIPLE STAR SYSTEMS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, Lewis C. Jr.; Tokovinin, Andrei; Mason, Brian D.

2015-10-15

Twenty multiple stellar systems with solar-type primaries were observed at high angular resolution using the PALM-3000 adaptive optics system at the 5 m Hale telescope. The goal was to complement the knowledge of hierarchical multiplicity in the solar neighborhood by confirming recent discoveries by the visible Robo-AO system with new near-infrared observations with PALM-3000. The physical status of most, but not all, of the new pairs is confirmed by photometry in the Ks band and new positional measurements. In addition, we resolved for the first time five close sub-systems: the known astrometric binary in HIP 17129AB, companions to the primariesmore » of HIP 33555, and HIP 118213, and the companions to the secondaries in HIP 25300 and HIP 101430. We place the components on a color–magnitude diagram and discuss each multiple system individually.« less

The framework of a UAS-aided flash flood modeling system for coastal regions

NASA Astrophysics Data System (ADS)

Zhang, H.; Xu, H.

2016-02-01

Flash floods cause severe economic damage and are one of the leading causes of fatalities connected with natural disasters in the Gulf Coast region. Current flash flood modeling systems rely on empirical hydrological models driven by precipitation estimates only. Although precipitation is the driving factor for flash floods, soil moisture, urban drainage system and impervious surface have been recognized to have significant impacts on the development of flash floods. We propose a new flash flooding modeling system that integrates 3-D hydrological simulation with satellite and multi-UAS observations. It will have three advantages over existing modeling systems. First, it will incorporate 1-km soil moisture data through integrating satellite images from European SMOS mission and NASA's SMAP mission. The utilization of high-resolution satellite images will provide essential information to determine antecedent soil moisture condition, which is an essential control on flood generation. Second, this system is able to adjust flood forecasting based on real-time inundation information collected by multi-UAS. A group of UAS will be deployed during storm events to capture the changing extent of flooded areas and water depth at multiple critical locations simultaneously. Such information will be transmitted to a hydrological model to validate and improve flood simulation. Third, the backbone of this system is a state-of-the-art 3-D hydrological model that assimilates the hydrological information from satellites and multi-UAS. The model is able to address surface water-groundwater interactions and reflect the effects of various infrastructures. Using Web-GIS technologies, the modeling results will be available online as interactive flood maps accessible to the public. To support the development and verification of this modeling system, surface and subsurface hydrological observations will be conducted in a number of small watersheds in the Coastal Bend region. We envision this

NOAO observing proposal processing system

NASA Astrophysics Data System (ADS)

Bell, David J.; Gasson, David; Hartman, Mia

2002-12-01

Since going electronic in 1994, NOAO has continued to refine and enhance its observing proposal handling system. Virtually all related processes are now handled electronically. Members of the astronomical community can submit proposals through email, web form or via Gemini's downloadable Phase-I Tool. NOAO staff can use online interfaces for administrative tasks, technical reviews, telescope scheduling, and compilation of various statistics. In addition, all information relevant to the TAC process is made available online. The system, now known as ANDES, is designed as a thin-client architecture (web pages are now used for almost all database functions) built using open source tools (FreeBSD, Apache, MySQL, Perl, PHP) to process descriptively-marked (LaTeX, XML) proposal documents.

SCHeMA web-based observation data information system

NASA Astrophysics Data System (ADS)

Novellino, Antonio; Benedetti, Giacomo; D'Angelo, Paolo; Confalonieri, Fabio; Massa, Francesco; Povero, Paolo; Tercier-Waeber, Marie-Louise

2016-04-01

It is well recognized that the need of sharing ocean data among non-specialized users is constantly increasing. Initiatives that are built upon international standards will contribute to simplify data processing and dissemination, improve user-accessibility also through web browsers, facilitate the sharing of information across the integrated network of ocean observing systems; and ultimately provide a better understanding of the ocean functioning. The SCHeMA (Integrated in Situ Chemical MApping probe) Project is developing an open and modular sensing solution for autonomous in situ high resolution mapping of a wide range of anthropogenic and natural chemical compounds coupled to master bio-physicochemical parameters (www.schema-ocean.eu). The SCHeMA web system is designed to ensure user-friendly data discovery, access and download as well as interoperability with other projects through a dedicated interface that implements the Global Earth Observation System of Systems - Common Infrastructure (GCI) recommendations and the international Open Geospatial Consortium - Sensor Web Enablement (OGC-SWE) standards. This approach will insure data accessibility in compliance with major European Directives and recommendations. Being modular, the system allows the plug-and-play of commercially available probes as well as new sensor probess under development within the project. The access to the network of monitoring probes is provided via a web-based system interface that, being implemented as a SOS (Sensor Observation Service), is providing standard interoperability and access tosensor observations systems through O&M standard - as well as sensor descriptions - encoded in Sensor Model Language (SensorML). The use of common vocabularies in all metadatabases and data formats, to describe data in an already harmonized and common standard is a prerequisite towards consistency and interoperability. Therefore, the SCHeMA SOS has adopted the SeaVox common vocabularies populated by

Big Data in the Earth Observing System Data and Information System

NASA Technical Reports Server (NTRS)

Lynnes, Chris; Baynes, Katie; McInerney, Mark

2016-01-01

Approaches that are being pursued for the Earth Observing System Data and Information System (EOSDIS) data system to address the challenges of Big Data were presented to the NASA Big Data Task Force. Cloud prototypes are underway to tackle the volume challenge of Big Data. However, advances in computer hardware or cloud won't help (much) with variety. Rather, interoperability standards, conventions, and community engagement are the key to addressing variety.

Earth Observing System (EOS) advanced altimetry

NASA Technical Reports Server (NTRS)

Parsons, C. L.; Walsh, E. J.

1988-01-01

In the post-TOPEX era, satellite radar altimeters will be developed with the capability of measuring the earth's surface topography over a wide swath of coverage, rather than just at the satellite's nadir. The identification of potential spacecraft flight missions in the future was studied. The best opportunity was found to be the Earth Observing System (EOS). It is felt that an instrument system that has a broad appeal to the earth sciences community stands a much better chance of being selected as an EOS instrument. Consequently, the Topography and Rain Radar Imager (TARRI) will be proposed as a system that has the capability to profile the Earth's topography regardless of the surface type. The horizontal and height resolutions of interest are obviously significantly different over land, ice, and water; but, the use of radar to provide an all-weather observation capability is applicable to the whole earth. The scientific guidance for the design and development of this instrument and the eventual scientific utilization of the data produced by the TARRI will be provided by seven science teams. The teams are formed around scientific disciplines and are titled: Geology/Geophysics, Hydrology/Rain, Oceanography, Ice/Snow, Geodesy/Orbit/Attitude, Cartography, and Surface Properties/Techniques.

INTAROS: Development of an integrated Arctic observation system under Horizon 2020

NASA Astrophysics Data System (ADS)

Beszczynska-Möller, Agnieszka; Sandven, Stein; Sagen, Hanne

2017-04-01

INTAROS is a research and innovation action funded under the H2020-BG-09 call for the five-year period 2016-2021. INTAROS will develop an integrated Arctic Observation System (iAOS) by extending, improving and unifying existing systems in the different regions of the Arctic. INTAROS will have a strong multidisciplinary focus, with tools for integration of data from atmosphere, ocean, cryosphere and terrestrial sciences, provided by institutions in Europe, North America and Asia. Satellite earth observation (EO) data plays an increasingly important role in such observing systems, because the amount of EO data for observing the global climate and environment grows year by year. EO data will therefore be integrated into iAOS based on existing products and databases. In situ observing systems are much more limited due to logistical constraints and cost limitations. The sparseness of in situ data is therefore the largest gap in the overall observing system. INTAROS will assess strengths and weaknesses of existing Arctic observing systems and contribute with innovative solutions to fill some of the critical gaps in the selected networks. INTAROS will develop a platform, iAOS, to search for and access data from distributed databases. The evolution into a sustainable Arctic observing system requires coordination, mobilization and cooperation between the existing European and international infrastructures (in-situ and remote, including space-based), the modeling communities and relevant stakeholder groups. INTAROS will include development of community-based observing systems, where local knowledge is merged with scientific data. Multidisciplinary data integrated under INTAROS will contribute to better understanding of interactions and coupling in the complex Arctic ice-ocean-land-atmosphere system. An integrated Arctic Observation System will enable better-informed decisions and better-documented processes within key sectors (e.g. local communities, shipping, tourism

SEU induced errors observed in microprocessor systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asenek, V.; Underwood, C.; Oldfield, M.

In this paper, the authors present software tools for predicting the rate and nature of observable SEU induced errors in microprocessor systems. These tools are built around a commercial microprocessor simulator and are used to analyze real satellite application systems. Results obtained from simulating the nature of SEU induced errors are shown to correlate with ground-based radiation test data.

Effects of Different Observational Systems and Time Sequences Upon Non-Participant Observers' Behavioral Ratings.

ERIC Educational Resources Information Center

Wodarski, John S.; And Others

Four different observational systems and two time sequences were employed to determine the extent to which they would yield different incidences of anti-social behavior. Two videotapes, randomly chosen from a pool of 30 tapes, were utilized. These illustrated the behaviors of anti-social children in a natural setting. Six observers were reliably…

Linear system identification via backward-time observer models

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh Q.

1992-01-01

Presented here is an algorithm to compute the Markov parameters of a backward-time observer for a backward-time model from experimental input and output data. The backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) for the backward-time system identification. The identified backward-time system Markov parameters are used in the Eigensystem Realization Algorithm to identify a backward-time state-space model, which can be easily converted to the usual forward-time representation. If one reverses time in the model to be identified, what were damped true system modes become modes with negative damping, growing as the reversed time increases. On the other hand, the noise modes in the identification still maintain the property that they are stable. The shift from positive damping to negative damping of the true system modes allows one to distinguish these modes from noise modes. Experimental results are given to illustrate when and to what extent this concept works.

Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian

2017-04-01

West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were

(TES) Thermal Enclosure System with (COS) Crystal Observation System

NASA Technical Reports Server (NTRS)

1993-01-01

The COS consists of a specially designed (VDA) Vapor Diffusion Apparatus tray with 6 chambers, a video camera for each chamber, a lighting system, and associated hardware. By observing the crystal growth in each chamber, researchers can identify which conditions and concentrations of proteins and precipitants are best for promoting the crystal growth to a particular protein.

The Jupiter System Observer: Probing the Foundations of Planetary Systems

NASA Astrophysics Data System (ADS)

Senske, D.; Prockter, L.; Collins, G.; Cooper, J.; Hendrix, A.; Hibbitts, K.; Kivelson, M.; Orton, G.; Schubert, G.; Showman, A.; Turtle, E.; Williams, D.; Kwok, J.; Spilker, T.; Tan-Wang, G.

2007-12-01

Galileo's observations in the 1600's of the dynamic system of Jupiter and its moons launched a revolution in understanding the way planetary systems operate. Now, some 400 years later, the discovery of extra solar planetary systems with Jupiter-sized bodies has led to a similar revolution in thought regarding how these systems form and evolve. From the time of Galileo, the Jovian system has been viewed as a solar system in miniature, providing a laboratory to study, diverse and dynamic processes in a single place. The icy Galilean satellites provide a window into solar system history by preserving in their cratering records a chronology dating back nearly 4.5 By and extending to the present. The continuously erupting volcanoes of Io may provide insight into the era when magma oceans were common. The discovery of an internally generated magnetic field at Ganymede, one of only three terrestrial bodies to possess such a field, is a place to gain insight as to how dynamos work. The confirmation and characterization of icy satellite subsurface oceans impacts the way habitability is considered. Understanding the composition and volatile inventory of Jupiter can shed light into how planets accrete from the solar nebulae. Finally, like our sun, Jupiter influences its system through its extensive magnetic field. In early 2007, NASA's Science Mission Directorate formed four Science Definition Teams (SDTs) to formulate science goals and objectives in anticipation of the initiation of a flagship-class mission to the outer solar system (Europa, Jupiter system, Titan and Enceladus). The Jupiter System Observer (JSO) mission concept emphasizes overall Jupiter system science: 1) Jupiter and its atmosphere, 2) the geology and geophysics of the Galilean satellites (Io, Europa, Ganymede and Callisto), 3) the magnetosphere environment - both Jupiter's and Ganymede's&pand 4) interactions within the system. Focusing on the unique geology, presence of an internal magnetic field and

System study of the carbon dioxide observational platform system (CO-OPS): Project overview

NASA Technical Reports Server (NTRS)

Stephens, J. Briscoe; Thompson, Wilbur E.

1987-01-01

The resulting options from a system study for a near-space, geo-stationary, observational monitoring platform system for use in the Department of Energy's (DOE) National Carbon Dioxide Observational Platform System (CO-OPS) on the greenhouse effect are discussed. CO-OPS is being designed to operate continuously for periods of up to 3 months in quasi-fixed position over most global regional targets of interest and could make horizon observations over a land-sea area of circular diameter up to about 600 to 800 statute miles. This affords the scientific and engineering community a low-cost means of operating their payloads for monitoring the regional parameters they deem relevant to their investigations of the carbon dioxide greenhouse effect at one-tenth the cost of most currently utilized comparable remote sensing techniques.

Sensitivity of Active and Passive Microwave Observations to Soil Moisture during Growing Corn

NASA Astrophysics Data System (ADS)

Judge, J.; Monsivais-Huertero, A.; Liu, P.; De Roo, R. D.; England, A. W.; Nagarajan, K.

2011-12-01

Soil moisture (SM) in the root zone is a key factor governing water and energy fluxes at the land surface and its accurate knowledge is critical to predictions of weather and near-term climate, nutrient cycles, crop-yield, and ecosystem productivity. Microwave observations, such as those at L-band, are highly sensitive to soil moisture in the upper few centimeters (near-surface). The two satellite-based missions dedicated to soil moisture estimation include, the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission and the planned NASA Soil Moisture Active/Passive (SMAP) [4] mission. The SMAP mission will include active and passive sensors at L-band to provide global observations of SM, with a repeat coverage of every 2-3 days. These observations can significantly improve root zone soil moisture estimates through data assimilation into land surface models (LSMs). Both the active (radar) and passive (radiometer) microwave sensors measure radiation quantities that are functions of soil dielectric constant and exhibit similar sensitivities to SM. In addition to the SM sensitivity, radar backscatter is highly sensitive to roughness of soil surface and scattering within the vegetation. These effects may produce a much larger dynamic range in backscatter than that produced due to SM changes alone. In this study, we discuss the field observations of active and passive signatures of growing corn at L-band from several seasons during the tenth Microwave, Water and Energy Balance Experiment (MicroWEX-10) conducted in North Central Florida, and to understand the sensitivity of these signatures to soil moisture under dynamic vegetation conditions. The MicroWEXs are a series of season-long field experiments conducted during the growing seasons of sweet corn, cotton, and energy cane over the past six years (for example, [22]). The corn was planted on July 5 and harvested on September 23, 2011 during MicroWEX-10. The size of the field was 0.04 km2 and the soils

AtlantOS - Optimizing and Enhancing the Integrated Atlantic Ocean Observing System

NASA Astrophysics Data System (ADS)

Reitz, Anja; Visbeck, Martin; AtlantOS Consortium, the

2016-04-01

Atlantic Ocean observation is currently undertaken through loosely-coordinated, in-situ observing networks, satellite observations and data management arrangements of heterogeneous international, national and regional design to support science and a wide range of information products. Thus there is tremendous opportunity to develop the systems towards a fully integrated Atlantic Ocean Observing System consistent with the recently developed 'Framework of Ocean Observing'. The vision of AtlantOS is to improve and innovate Atlantic observing by using the Framework of Ocean Observing to obtain an international, more sustainable, more efficient, more integrated, and fit-for-purpose system. Hence, the AtlantOS initiative will have a long-lasting and sustainable contribution to the societal, economic and scientific benefit arising from this integrated approach. This will be delivered by improving the value for money, extent, completeness, quality and ease of access to Atlantic Ocean data required by industries, product supplying agencies, scientist and citizens. The overarching target of the AtlantOS initiative is to deliver an advanced framework for the development of an integrated Atlantic Ocean Observing System that goes beyond the state-of -the-art, and leaves a legacy of sustainability after the life of the project. The legacy will derive from the following aims: i) to improve international collaboration in the design, implementation and benefit sharing of ocean observing, ii) to promote engagement and innovation in all aspects of ocean observing, iii) to facilitate free and open access to ocean data and information, iv) to enable and disseminate methods of achieving quality and authority of ocean information, v) to strengthen the Global Ocean Observing System (GOOS) and to sustain observing systems that are critical for the Copernicus Marine Environment Monitoring Service and its applications and vi) to contribute to the aims of the Galway Statement on Atlantic

Demonstrating the Alaska Ocean Observing System in Prince William Sound

NASA Astrophysics Data System (ADS)

Schoch, G. Carl; McCammon, Molly

2013-07-01

The Alaska Ocean Observing System and the Oil Spill Recovery Institute developed a demonstration project over a 5 year period in Prince William Sound. The primary goal was to develop a quasi-operational system that delivers weather and ocean information in near real time to diverse user communities. This observing system now consists of atmospheric and oceanic sensors, and a new generation of computer models to numerically simulate and forecast weather, waves, and ocean circulation. A state of the art data management system provides access to these products from one internet portal at http://www.aoos.org. The project culminated in a 2009 field experiment that evaluated the observing system and performance of the model forecasts. Observations from terrestrial weather stations and weather buoys validated atmospheric circulation forecasts. Observations from wave gages on weather buoys validated forecasts of significant wave heights and periods. There was an emphasis on validation of surface currents forecasted by the ocean circulation model for oil spill response and search and rescue applications. During the 18 day field experiment a radar array mapped surface currents and drifting buoys were deployed. Hydrographic profiles at fixed stations, and by autonomous vehicles along transects, were made to acquire measurements through the water column. Terrestrial weather stations were the most reliable and least costly to operate, and in situ ocean sensors were more costly and considerably less reliable. The radar surface current mappers were the least reliable and most costly but provided the assimilation and validation data that most improved ocean circulation forecasts. We describe the setting of Prince William Sound and the various observational platforms and forecast models of the observing system, and discuss recommendations for future development.

Expert systems tools for Hubble Space Telescope observation scheduling

NASA Technical Reports Server (NTRS)

Miller, Glenn; Rosenthal, Don; Cohen, William; Johnston, Mark

1987-01-01

The utility of expert systems techniques for the Hubble Space Telescope (HST) planning and scheduling is discussed and a plan for development of expert system tools which will augment the existing ground system is described. Additional capabilities provided by these tools will include graphics-oriented plan evaluation, long-range analysis of the observation pool, analysis of optimal scheduling time intervals, constructing sequences of spacecraft activities which minimize operational overhead, and optimization of linkages between observations. Initial prototyping of a scheduler used the Automated Reasoning Tool running on a LISP workstation.

Field-Scale Soil Moisture Observations in Irrigated Agriculture Fields Using the Cosmic-ray Neutron Rover

NASA Astrophysics Data System (ADS)

Franz, T. E.; Avery, W. A.; Finkenbiner, C. E.; Wang, T.; Brocca, L.

2014-12-01

Approximately 40% of global food production comes from irrigated agriculture. With the increasing demand for food even greater pressures will be placed on water resources within these systems. In this work we aimed to characterize the spatial and temporal patterns of soil moisture at the field-scale (~500 m) using the newly developed cosmic-ray neutron rover near Waco, NE. Here we mapped soil moisture of 144 quarter section fields (a mix of maize, soybean, and natural areas) each week during the 2014 growing season (May to September). The 11 x11 km study domain also contained 3 stationary cosmic-ray neutron probes for independent validation of the rover surveys. Basic statistical analysis of the domain indicated a strong inverted parabolic relationship between the mean and variance of soil moisture. The relationship between the mean and higher order moments were not as strong. Geostatistical analysis indicated the range of the soil moisture semi-variogram was significantly shorter during periods of heavy irrigation as compared to non-irrigated periods. Scaling analysis indicated strong power law behavior between the variance of soil moisture and averaging area with minimal dependence of mean soil moisture on the slope of the power law function. Statistical relationships derived from the rover dataset offer a novel set of observations that will be useful in: 1) calibrating and validating land surface models, 2) calibrating and validating crop models, 3) soil moisture covariance estimates for statistical downscaling of remote sensing products such as SMOS and SMAP, and 4) provide center-pivot scale mean soil moisture data for optimal irrigation timing and volume amounts.

The Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution smaller than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have some first images that demonstrate the most innovative capability from EOS Terra: MODIS - 1.37 microns cirrus channel; 250 m daily cover for clouds and vegetation change; 7 solar channels for land and aerosol; new fire channels; Chlorophyll fluorescence; MISR - 9 multi angle views of clouds and vegetation; MOPITT - Global CO maps and CH4 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

An Automated Cloud Observation System (ACOS).

DTIC Science & Technology

1980-12-17

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Penn State Radar Systems: Implementation and Observations

NASA Astrophysics Data System (ADS)

Urbina, J. V.; Seal, R.; Sorbello, R.; Kuyeng, K.; Dyrud, L. P.

2014-12-01

Software Defined Radio/Radar (SDR) platforms have become increasingly popular as researchers, hobbyists, and military seek more efficient and cost-effective means for radar construction and operation. SDR platforms, by definition, utilize a software-based interface for configuration in contrast to traditional, hard-wired platforms. In an effort to provide new and improved radar sensing capabilities, Penn State has been developing advanced instruments and technologies for future radars, with primary objectives of making such instruments more capable, portable, and more cost effective. This paper will describe the design and implementation of two low-cost radar systems and their deployment in ionospheric research at both low and mid-latitudes. One radar has been installed near Penn State campus, University Park, Pennsylvania (77.97°W, 40.70°N), to make continuous meteor observations and mid-latitude plasma irregularities. The second radar is being installed in Huancayo (12.05°S, -75.33°E), Peru, which is capable of detecting E and F region plasma irregularities as well as meteor reflections. In this paper, we examine and compare the diurnal and seasonal variability of specular, non- specular, and head-echoes collected with these two new radar systems and discuss sampling biases of each meteor observation technique. We report our current efforts to validate and calibrate these radar systems with other VHF radars such as Jicamarca and SOUSY. We also present the general characteristics of continuous measurements of E-region and F-region coherent echoes using these modern radar systems and compare them with coherent radar events observed at other geographic mid-latitude radar stations.

Earth Observing System: Science Objectives and Challenges

NASA Technical Reports Server (NTRS)

King, Michael D.

1999-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. In this presentation we review the key areas of scientific uncertainty in understanding climate and global change, and follow that with a description of the EOS goals, objectives, and scientific research elements that comprise the program (instrument science teams and interdisciplinary investigations). Finally, I will describe how scientists and policy makers intend to use EOS data improve our understanding of key global change uncertainties, such as: (i) clouds and radiation, including fossil fuel and natural emissions of sulfate aerosol and its potential impact on cloud feedback, (ii) man's impact on ozone depletion, with examples of ClO and O3 obtained from the UARS satellite during the Austral Spring, and (iii) volcanic eruptions and their impact on climate, with examples from the eruption of Mt. Pinatubo.

Earth Observing System: Science Objectives and Challenges

NASA Technical Reports Server (NTRS)

King, Michael D.

1998-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. In this presentation I will describe the key areas of scientific uncertainty in understanding climate and global change, and follow that with a description of the EOS goals, objectives, and scientific research elements that comprise the program (instrument science teams and interdisciplinary investigations). Finally, I will describe how scientists and policy makers intend to use EOS data to improve our understanding of key global change uncertainties, such as: (i) clouds and radiation, including fossil fuel and natural emissions of sulfate aerosol and its potential impact on cloud feedback, (ii) man's impact on ozone depletion, with examples of ClO and O3 obtained from the UARS satellite during the Austral Spring, and (iii) volcanic eruptions and their impact on climate, with examples from the eruption of Mt. Pinatubo.

Earth Observing Data System Data and Information System (EOSDIS) Overview

NASA Technical Reports Server (NTRS)

Klene, Stephan

2016-01-01

The National Aeronautics and Space Administration (NASA) acquires and distributes an abundance of Earth science data on a daily basis to a diverse user community worldwide. The NASA Big Earth Data Initiative (BEDI) is an effort to make the acquired science data more discoverable, accessible, and usable. This presentation will provide a brief introduction to the Earth Observing System Data and Information System (EOSDIS) project and the nature of advances that have been made by BEDI to other Federal Users.

Observation and integrated Earth-system science: A roadmap for 2016–2025

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmons, Adrian; Fellous, Jean-Louis; Ramaswamy, V.

This report is the response to a request by the Committee on Space Research of the International Council for Science to prepare a roadmap on observation and integrated Earth-system science for the coming ten years. Its focus is on the combined use of observations and modelling to address the functioning, predictability and projected evolution of interacting components of the Earth system on timescales out to a century or so. It discusses how observations support integrated Earth-system science and its applications, and identifies planned enhancements to the contributing observing systems and other requirements for observations and their processing. All types ofmore » observation are considered, but emphasis is placed on those made from space. The origins and development of the integrated view of the Earth system are outlined, noting the interactions between the main components that lead to requirements for integrated science and modelling, and for the observations that guide and support them. What constitutes an Earth-system model is discussed. Summaries are given of key cycles within the Earth system. The nature of Earth observation and the arrangements for international coordination essential for effective operation of global observing systems are introduced. Instances are given of present types of observation, what is already on the roadmap for 2016–2025 and some of the issues to be faced. Observations that are organized on a systematic basis and observations that are made for process understanding and model development, or other research or demonstration purposes, are covered. Specific accounts are given for many of the variables of the Earth system. The current status and prospects for Earth-system modelling are summarized. The evolution towards applying Earth-system models for environmental monitoring and prediction as well as for climate simulation and projection is outlined. General aspects of the improvement of models, whether through refining the

Continued Analysis of EUVE Solar System Observations

NASA Technical Reports Server (NTRS)

Gladstone, G. Randall

2001-01-01

This is the final report for this project. We proposed to continue our work on extracting important results from the EUVE (Extreme UltraViolet Explorer) archive of lunar and jovian system observations. In particular, we planned to: (1) produce several monochromatic images of the Moon at the wavelengths of the brightest solar EUV emission lines; (2) search for evidence of soft X-ray emissions from the Moon and/or X-ray fluorescence at specific EUV wavelengths; (3) search for localized EUV and soft X-ray emissions associated with each of the Galilean satellites; (4) search for correlations between localized Io Plasma Torus (IPT) brightness and volcanic activity on Io; (5) search for soft X-ray emissions from Jupiter; and (6) determine the long term variability of He 58.4 nm emissions from Jupiter, and relate these to solar variability. However, the ADP review panel suggested that the work concentrate on the Jupiter/IPT observations, and provided half the requested funding. Thus we have performed no work on the first two tasks, and instead concentrated on the last three. In addition we used funds from this project to support reduction and analysis of EUVE observations of Venus. While this was not part of the original statement of work, it is entirely in keeping with extracting important results from EUVE solar system observations.

Comparison of Observation Impacts in Two Forecast Systems using Adjoint Methods

NASA Technical Reports Server (NTRS)

Gelaro, Ronald; Langland, Rolf; Todling, Ricardo

2009-01-01

An experiment is being conducted to compare directly the impact of all assimilated observations on short-range forecast errors in different operational forecast systems. We use the adjoint-based method developed by Langland and Baker (2004), which allows these impacts to be efficiently calculated. This presentation describes preliminary results for a "baseline" set of observations, including both satellite radiances and conventional observations, used by the Navy/NOGAPS and NASA/GEOS-5 forecast systems for the month of January 2007. In each system, about 65% of the total reduction in 24-h forecast error is provided by satellite observations, although the impact of rawinsonde, aircraft, land, and ship-based observations remains significant. Only a small majority (50- 55%) of all observations assimilated improves the forecast, while the rest degrade it. It is found that most of the total forecast error reduction comes from observations with moderate-size innovations providing small to moderate impacts, not from outliers with very large positive or negative innovations. In a global context, the relative impacts of the major observation types are fairly similar in each system, although regional differences in observation impact can be significant. Of particular interest is the fact that while satellite radiances have a large positive impact overall, they degrade the forecast in certain locations common to both systems, especially over land and ice surfaces. Ongoing comparisons of this type, with results expected from other operational centers, should lead to more robust conclusions about the impacts of the various components of the observing system as well as about the strengths and weaknesses of the methodologies used to assimilate them.

Observation Scheduling System

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Tran, Daniel Q.; Rabideau, Gregg R.; Schaffer, Steven R.

2011-01-01

Software has been designed to schedule remote sensing with the Earth Observing One spacecraft. The software attempts to satisfy as many observation requests as possible considering each against spacecraft operation constraints such as data volume, thermal, pointing maneuvers, and others. More complex constraints such as temperature are approximated to enable efficient reasoning while keeping the spacecraft within safe limits. Other constraints are checked using an external software library. For example, an attitude control library is used to determine the feasibility of maneuvering between pairs of observations. This innovation can deal with a wide range of spacecraft constraints and solve large scale scheduling problems like hundreds of observations and thousands of combinations of observation sequences.

Polymorphic robotic system controlled by an observing camera

NASA Astrophysics Data System (ADS)

Koçer, Bilge; Yüksel, Tugçe; Yümer, M. Ersin; Özen, C. Alper; Yaman, Ulas

2010-02-01

Polymorphic robotic systems, which are composed of many modular robots that act in coordination to achieve a goal defined on the system level, have been drawing attention of industrial and research communities since they bring additional flexibility in many applications. This paper introduces a new polymorphic robotic system, in which the detection and control of the modules are attained by a stationary observing camera. The modules do not have any sensory equipment for positioning or detecting each other. They are self-powered, geared with means of wireless communication and locking mechanisms, and are marked to enable the image processing algorithm detect the position and orientation of each of them in a two dimensional space. Since the system does not depend on the modules for positioning and commanding others, in a circumstance where one or more of the modules malfunction, the system will be able to continue operating with the rest of the modules. Moreover, to enhance the compatibility and robustness of the system under different illumination conditions, stationary reference markers are employed together with global positioning markers, and an adaptive filtering parameter decision methodology is enclosed. To the best of authors' knowledge, this is the first study to introduce a remote camera observer to control modules of a polymorphic robotic system.

Science-Grade Observing Systems as Process Observatories: Mapping and Understanding Nonlinearity and Multiscale Memory with Models and Observations

NASA Astrophysics Data System (ADS)

Barros, A. P.; Wilson, A. M.; Miller, D. K.; Tao, J.; Genereux, D. P.; Prat, O.; Petersen, W. A.; Brunsell, N. A.; Petters, M. D.; Duan, Y.

2015-12-01

Using the planet as a study domain and collecting observations over unprecedented ranges of spatial and temporal scales, NASA's EOS (Earth Observing System) program was an agent of transformational change in Earth Sciences over the last thirty years. The remarkable space-time organization and variability of atmospheric and terrestrial moist processes that emerged from the analysis of comprehensive satellite observations provided much impetus to expand the scope of land-atmosphere interaction studies in Hydrology and Hydrometeorology. Consequently, input and output terms in the mass and energy balance equations evolved from being treated as fluxes that can be used as boundary conditions, or forcing, to being viewed as dynamic processes of a coupled system interacting at multiple scales. Measurements of states or fluxes are most useful if together they map, reveal and/or constrain the underlying physical processes and their interactions. This can only be accomplished through an integrated observing system designed to capture the coupled physics, including nonlinear feedbacks and tipping points. Here, we first review and synthesize lessons learned from hydrometeorology studies in the Southern Appalachians and in the Southern Great Plains using both ground-based and satellite observations, physical models and data-assimilation systems. We will specifically focus on mapping and understanding nonlinearity and multiscale memory of rainfall-runoff processes in mountainous regions. It will be shown that beyond technical rigor, variety, quantity and duration of measurements, the utility of observing systems is determined by their interpretive value in the context of physical models to describe the linkages among different observations. Second, we propose a framework for designing science-grade and science-minded process-oriented integrated observing and modeling platforms for hydrometeorological studies.

Observed ices in the Solar System

USGS Publications Warehouse

Clark, Roger N.; Grundy, Will; Carlson, Robert R.; Noll, Keith; Gudipati, Murthy; Castillo-Rogez, Julie C.

2013-01-01

Ices have been detected and mapped on the Earth and all planets and/or their satellites further from the sun. Water ice is the most common frozen volatile observed and is also unambiguously detected or inferred in every planet and/or their moon(s) except Venus. Carbon dioxide is also extensively found in all systems beyond the Earth except Pluto although it sometimes appears to be trapped rather than as an ice on some objects. The largest deposits of carbon dioxide ice is on Mars. Sulfur dioxide ice is found in the Jupiter system. Nitrogen and methane ices are common beyond the Uranian system. Saturn’s moon Titan probably has the most complex active chemistry involving ices, with benzene (C6H6) and many tentative or inferred compounds including ices of Cyanoacetylene (HC3N), Toluene (C7H8), Cyanogen (C2N2), Acetonitrile (CH3CN), H2O, CO2, and NH3. Confirming compounds on Titan is hampered by its thick smoggy atmosphere. Ammonia was predicted on many icy moons but is notably absent among the definitively detected ices with the possible exception of Enceladus. Comets, storehouses of many compounds that could exist as ices in their nuclei, have only had small amounts of water ice definitively detected on their surfaces. Only one asteroid has had a direct detection of surface water ice, although its presence can be inferred in others. This chapter reviews some of the properties of ices that lead to their detection, and surveys the ices that have been observed on solid surfaces throughout the Solar System.

Atmospheric Observations from Unmanned Aircraft Systems

NASA Technical Reports Server (NTRS)

Newman, Paul A.

2008-01-01

Unmanned Aircraft Systems (UASs) provide a new and exciting avenue for atmospheric observations. NASA has a number of UASs. Amongst these are the Ikhana (24 hrs., 7000 km), the Altair (120 hrs., 6500 km), the Aerosonde (30 hrs., 3000 km), and the Global Hawk (30 hrs., 22,000 km). This presentation provides a brief history of UASs which is followed by a description of their capabilities. The presentation concludes by describing an example mission - the UAS Aura Validation Experiment (UAS-AVE). This mission will be flown on the NASA Global Hawk in the Spring/Summer of 2009. The goals fo the mission are to: 1) provide Aura validation observations, 2) sample the break up of the Arctic polar vortex, 3) observed cross-Pacific transport of aerosols and pollutants such as ozone, and 4) sample intense water advective events that impact the U.S. west coast (atmospheric rivers). Because of their range and duration, UASs provide new and exciting opportunities for atmospheric science.

IEOOS: the Spanish Institute of Oceanography Observing System

NASA Astrophysics Data System (ADS)

Tel, E.; Balbin, R.; Cabanas, J. M.; Garcia, M. J.; Garcia-Martinez, M. C.; Gonzalez-Pola, C.; Lavin, A.; Lopez-Jurado, J. L.; Rodriguez, C.; Ruiz-Villarreal, M.; Sanchez-Leal, R. F.; Vargas-Yanez, M.; Velez-Belchi, P.

2015-10-01

Since its foundation, 100 years ago, the Spanish Institute of Oceanography (IEO) has been observing and measuring the ocean characteristics. Here is a summary of the initiatives of the IEO in the field of the operational oceanography (OO). Some systems like the tide gauges network has been working for more than 70 years. The IEO standard sections began at different moments depending on the local projects, and nowadays there are more than 180 coastal stations and deep-sea ones that are systematically sampled, obtaining physical and biochemical measurements. At this moment, the IEO Observing System (IEOOS) includes 6 permanent moorings equipped with currentmeters, an open-sea ocean-meteorological buoy offshore Santander and an SST satellital image reception station. It also supports the Spanish contribution to the ARGO international program with 47 deployed profilers, and continuous monitoring thermosalinometers, meteorological stations and ADCP onboard the IEO research vessels. The system is completed with the IEO contribution to the RAIA and Gibraltar observatories, and the development of regional prediction models. All these systematic measurements allow the IEO to give responses to ocean research activities, official agencies requirements and industrial and main society demands as navigation, resource management, risks management, recreation, etc, as well as for management development pollution-related economic activities or marine ecosystems. All these networks are linked to international initiatives, framed largely in supranational programs Earth observation sponsored by the United Nations or the European Union. The synchronic observation system permits following spatio-temporal description of some events, as new deep water formation in the Mediterranean Sea and the injection of heat to intermediate waters in the Bay of Biscay after some colder northern storms in winter 2005.

Air-sea fluxes and satellite-based estimation of water masses formation

NASA Astrophysics Data System (ADS)

Sabia, Roberto; Klockmann, Marlene; Fernandez-Prieto, Diego; Donlon, Craig

2015-04-01

Recent work linking satellite-based measurements of sea surface salinity (SSS) and sea surface temperature (SST) with traditional physical oceanography has demonstrated the capability of generating routinely satellite-derived surface T-S diagrams [1] and analyze the distribution/dynamics of SSS and its relative surface density with respect to in-situ measurements. Even more recently [2,3], this framework has been extended by exploiting these T-S diagrams as a diagnostic tool to derive water masses formation rates and areas. A water mass describes a water body with physical properties distinct from the surrounding water, formed at the ocean surface under specific conditions which determine its temperature and salinity. The SST and SSS (and thus also density) at the ocean surface are largely determined by fluxes of heat and freshwater. The surface density flux is a function of the latter two and describes the change of the density of seawater at the surface. To obtain observations of water mass formation is of great interest, since they serve as indirect observations of the thermo-haline circulation. The SSS data which has become available through the SMOS [4] and Aquarius [5] satellite missions will provide the possibility of studying also the effect of temporally-varying SSS fields on water mass formation. In the present study, the formation of water masses as a function of SST and SSS is derived from the surface density flux by integrating the latter over a specific area and time period in bins of SST and SSS and then taking the derivative of the total density flux with respect to density. This study presents a test case using SMOS SSS, OSTIA SST, as well as Argo ISAS SST and SSS for comparison, heat fluxes from the NOCS Surface Flux Data Set v2.0, OAFlux evaporation and CMORPH precipitation. The study area, initially referred to the North Atlantic, is extended over two additional ocean basins and the study period covers the 2011-2012 timeframe. Yearly, seasonal

Reduced-Rank Array Modes of the California Current Observing System

NASA Astrophysics Data System (ADS)

Moore, Andrew M.; Arango, Hernan G.; Edwards, Christopher A.

2018-01-01

The information content of the ocean observing array spanning the U.S. west coast is explored using the reduced-rank array modes (RAMs) derived from a four-dimensional variational (4D-Var) data assimilation system covering a period of three decades. RAMs are an extension of the original formulation of array modes introduced by Bennett (1985) but in the reduced model state-space explored by the 4D-Var system, and reveal the extent to which this space is activated by the observations. The projection of the RAMs onto the empirical orthogonal functions (EOFs) of the 4D-Var background error correlation matrix provides a quantitative measure of the effectiveness of the measurements in observing the circulation. It is found that much of the space spanned by the background error covariance is unconstrained by the present ocean observing system. The RAM spectrum is also used to introduce a new criterion to prevent 4D-Var from overfitting the model to the observations.

The Earth Observing System Terra Mission

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.; Einaudi, Franco (Technical Monitor)

2000-01-01

Langley's remarkable solar and lunar spectra collected from Mt. Whitney inspired Arrhenius to develop the first quantitative climate model in 1896. After the launch in Dec. 16 1999, NASA's Earth Observing AM Satellite (EOS-Terra) will repeat Langley's experiment, but for the entire planet, thus pioneering a wide array of calibrated spectral observations from space of the Earth System. Conceived in response to real environmental problems, EOS-Terra, in conjunction with other international satellite efforts, will fill a major gap in current efforts by providing quantitative global data sets with a resolution better than 1 km on the physical, chemical and biological elements of the earth system. Thus, like Langley's data, EOS-Terra can revolutionize climate research by inspiring a new generation of climate system models and enable us to assess the human impact on the environment. In the talk I shall review the historical perspective of the Terra mission and the key new elements of the mission. We expect to have first images that demonstrate the most innovative capability from EOS Terra 5 instruments: MODIS - 1.37 micron cirrus cloud channel; 250m daily coverage for clouds and vegetation change; 7 solar channels for land and aerosol studies; new fire channels; Chlorophyll fluorescence; MISR - first 9 multi angle views of clouds and vegetation; MOPITT - first global CO maps and C114 maps; ASTER - Thermal channels for geological studies with 15-90 m resolution.

Microscopic video observation of capillary vessel systems using diffuse back lighting

NASA Astrophysics Data System (ADS)

Sakai, Minako; Arai, Hiroki; Iwai, Toshiaki

2017-04-01

We have been developing a simple and practical video microscopy system based on absorption spectra of biological substance to perform spectroscopic observation of living tissues. The diffuse backlighting effect is actively used in the developed system, which is generated by multiple light scattering in the tissue. It is demonstrated that the light specularly reflected from the skin surface can be completely suppressed in the microscopic observation and the biological activity of the capillary vessel systems distributed under the skin can be successfully observed. As a result, we can confirm the effectiveness of the video microscopy system using diffuse backlighting and the applicability of our developed system.

Accelerating assimilation development for new observing systems using EFSO

NASA Astrophysics Data System (ADS)

Lien, Guo-Yuan; Hotta, Daisuke; Kalnay, Eugenia; Miyoshi, Takemasa; Chen, Tse-Chun

2018-03-01

To successfully assimilate data from a new observing system, it is necessary to develop appropriate data selection strategies, assimilating only the generally useful data. This development work is usually done by trial and error using observing system experiments (OSEs), which are very time and resource consuming. This study proposes a new, efficient methodology to accelerate the development using ensemble forecast sensitivity to observations (EFSO). First, non-cycled assimilation of the new observation data is conducted to compute EFSO diagnostics for each observation within a large sample. Second, the average EFSO conditionally sampled in terms of various factors is computed. Third, potential data selection criteria are designed based on the non-cycled EFSO statistics, and tested in cycled OSEs to verify the actual assimilation impact. The usefulness of this method is demonstrated with the assimilation of satellite precipitation data. It is shown that the EFSO-based method can efficiently suggest data selection criteria that significantly improve the assimilation results.

The Influence of Observation Errors on Analysis Error and Forecast Skill Investigated with an Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, N. C.; Errico, R. M.; Tai, K.-S.

2013-01-01

The Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework is used to explore the response of analysis error and forecast skill to observation quality. In an OSSE, synthetic observations may be created that have much smaller error than real observations, and precisely quantified error may be applied to these synthetic observations. Three experiments are performed in which synthetic observations with magnitudes of applied observation error that vary from zero to twice the estimated realistic error are ingested into the Goddard Earth Observing System Model (GEOS-5) with Gridpoint Statistical Interpolation (GSI) data assimilation for a one-month period representing July. The analysis increment and observation innovation are strongly impacted by observation error, with much larger variances for increased observation error. The analysis quality is degraded by increased observation error, but the change in root-mean-square error of the analysis state is small relative to the total analysis error. Surprisingly, in the 120 hour forecast increased observation error only yields a slight decline in forecast skill in the extratropics, and no discernable degradation of forecast skill in the tropics.

The diversity of planetary system architectures: contrasting theory with observations

NASA Astrophysics Data System (ADS)

Miguel, Y.; Guilera, O. M.; Brunini, A.

2011-10-01

In order to explain the observed diversity of planetary system architectures and relate this primordial diversity to the initial properties of the discs where they were born, we develop a semi-analytical model for computing planetary system formation. The model is based on the core instability model for the gas accretion of the embryos and the oligarchic growth regime for the accretion of the solid cores. Two regimes of planetary migration are also included. With this model, we consider different initial conditions based on recent results of protoplanetary disc observations to generate a variety of planetary systems. These systems are analysed statistically, exploring the importance of several factors that define the planetary system birth environment. We explore the relevance of the mass and size of the disc, metallicity, mass of the central star and time-scale of gaseous disc dissipation in defining the architecture of the planetary system. We also test different values of some key parameters of our model to find out which factors best reproduce the diverse sample of observed planetary systems. We assume different migration rates and initial disc profiles, in the context of a surface density profile motivated by similarity solutions. According to this, and based on recent protoplanetary disc observational data, we predict which systems are the most common in the solar neighbourhood. We intend to unveil whether our Solar system is a rarity or whether more planetary systems like our own are expected to be found in the near future. We also analyse which is the more favourable environment for the formation of habitable planets. Our results show that planetary systems with only terrestrial planets are the most common, being the only planetary systems formed when considering low-metallicity discs, which also represent the best environment for the development of rocky, potentially habitable planets. We also found that planetary systems like our own are not rare in the

Using high-resolution soil moisture modelling to assess the uncertainty of microwave remotely sensed soil moisture products at the correct spatial and temporal support

NASA Astrophysics Data System (ADS)

Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.

2012-04-01

Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture content throughout the river basin. Space-borne remote sensing may provide this information with a high temporal and spatial resolution and with a global coverage. Currently three microwave soil moisture products are available: AMSR-E, ASCAT and SMOS. The quality of these satellite-based products is often assessed by comparing them with in-situ observations of soil moisture. This comparison is however hampered by the difference in spatial and temporal support (i.e., resolution, scale), because the spatial resolution of microwave satellites is rather low compared to in-situ field measurements. Thus, the aim of this study is to derive a method to assess the uncertainty of microwave satellite soil moisture products at the correct spatial support. To overcome the difference in support size between in-situ soil moisture observations and remote sensed soil moisture, we used a stochastic, distributed unsaturated zone model (SWAP, van Dam (2000)) that is upscaled to the support of different satellite products. A detailed assessment of the SWAP model uncertainty is included to ensure that the uncertainty in satellite soil moisture is not overestimated due to an underestimation of the model uncertainty. We simulated unsaturated water flow up to a depth of 1.5m with a vertical resolution of 1 to 10 cm and on a horizontal grid of 1 km2 for the period Jan 2010 - Jun 2011. The SWAP model was first calibrated and validated on in-situ data of the REMEDHUS soil moisture network (Spain). Next, to evaluate the satellite products, the model was run for areas in the proximity of 79 meteorological stations in Spain, where model results were aggregated to the correct support of the satellite

CAROLS: a new airborne L-band radiometer for ocean surface and land observations.

PubMed

Zribi, Mehrez; Pardé, Mickael; Boutin, Jacquline; Fanise, Pascal; Hauser, Daniele; Dechambre, Monique; Kerr, Yann; Leduc-Leballeur, Marion; Reverdin, Gilles; Skou, Niels; Søbjærg, Sten; Albergel, Clement; Calvet, Jean Christophe; Wigneron, Jean Pierre; Lopez-Baeza, Ernesto; Rius, Antonio; Tenerelli, Joseph

2011-01-01

The "Cooperative Airborne Radiometer for Ocean and Land Studies" (CAROLS) L-Band radiometer was designed and built as a copy of the EMIRAD II radiometer constructed by the Technical University of Denmark team. It is a fully polarimetric and direct sampling correlation radiometer. It is installed on board a dedicated French ATR42 research aircraft, in conjunction with other airborne instruments (C-Band scatterometer-STORM, the GOLD-RTR GPS system, the infrared CIMEL radiometer and a visible wavelength camera). Following initial laboratory qualifications, three airborne campaigns involving 21 flights were carried out over South West France, the Valencia site and the Bay of Biscay (Atlantic Ocean) in 2007, 2008 and 2009, in coordination with in situ field campaigns. In order to validate the CAROLS data, various aircraft flight patterns and maneuvers were implemented, including straight horizontal flights, circular flights, wing and nose wags over the ocean. Analysis of the first two campaigns in 2007 and 2008 leads us to improve the CAROLS radiometer regarding isolation between channels and filter bandwidth. After implementation of these improvements, results show that the instrument is conforming to specification and is a useful tool for Soil Moisture and Ocean Salinity (SMOS) satellite validation as well as for specific studies on surface soil moisture or ocean salinity.

The RITMARE Ocean Observing System for the Italian Seas

NASA Astrophysics Data System (ADS)

Crise, A.

2016-02-01

Among its objectives, the Italian RITMARE Flagship Programme has the aim to produce a prototype of the RITMARE Ocean observing system explicitelly designed to provide a powerful infrastructure to the Italian marine science community, to help implement national and Europen environmental regulations and to contribute to the future European Ocean Observing System. The projects takes advantage of the existing platforms (fixed-point moorings, HF and X-band radars, gliders, satellite products), that constitute the basic components of the system. The structure of the RITMARE Ocean observing system is composed by a permanent component (mooring network, satellite images, HF radars) and relocatable component (gliders, drifters, relocatable infrastructures). The increasing number of available relocatable/expandable platforms allow a much larger flexibility in term of allocation of observations but requires an sampling strategy the can be modified according the scientific and socio-economic priorities. As an example, RITMARE focus is set on an experiment on the South Adriatic Pit convective area and its dynamic interactions with the adjacent Bari Canyon cascading site. (Central Mediterranean Sea). Additional effort is paid to support innovation for sensors (e.g. ship-borne LIDAR, stereo-optic directional wave detection, X-band radar innovative products), operational employment of gliders (e.g. Wave Glider) and new class of operational models. The integration can be obtained at different level: the is expected to be achieved at ICT level by defining standard interfaces (NedCDF, SOS) and catalogs in order to facilitate the discovery, viewing and downloading services of data and products. The implementation of a distributed platform-oriented RT repositories adopt a number of THREDDS web servers that act as endpoints for the RITMARE portal. The final aim is to decouple the platforms from the observations, moving from a set of observation to a suite of Essential Ocean Variables by

Study on observation planning of LAMOST focal plane positioning system and its simulation

NASA Astrophysics Data System (ADS)

Zhai, Chao; Jin, Yi; Peng, Xiaobo; Xing, Xiaozheng

2006-06-01

Fiber Positioning System of LAMOST focal plane based on subarea thinking, adopts a parallel controllable positioning plan, the structure is designed as a round area and overlapped each other in order to eliminate the un-observation region. But it also makes the observation efficiency of the system become an important problem. In this paper According to the system, the model of LAMOST focal plane Observation Planning including 4000 fiber positioning units is built, Stars are allocated using netflow algorithm and mechanical collisions are diminished through the retreat algorithm, then the simulation of the system's observation efficiency is carried out. The problem of observation efficiency of LAMOST focal plane is analysed systemic and all-sided from the aspect of overlapped region, fiber positioning units, observation radius, collisions and so on. The observation efficiency of the system in theory is describes and the simulation indicates that the system's observation efficiency is acceptable. The analyses play an indicative role on the design of the LAMOST focal plane structure.

Status of the NASA GMAO Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, Nikki C.; Errico, Ronald M.

2014-01-01

An Observing System Simulation Experiment (OSSE) is a pure modeling study used when actual observations are too expensive or difficult to obtain. OSSEs are valuable tools for determining the potential impact of new observing systems on numerical weather forecasts and for evaluation of data assimilation systems (DAS). An OSSE has been developed at the NASA Global Modeling and Assimilation Office (GMAO, Errico et al 2013). The GMAO OSSE uses a 13-month integration of the European Centre for Medium- Range Weather Forecasts 2005 operational model at T511/L91 resolution for the Nature Run (NR). Synthetic observations have been updated so that they are based on real observations during the summer of 2013. The emulated observation types include AMSU-A, MHS, IASI, AIRS, and HIRS4 radiance data, GPS-RO, and conventional types including aircraft, rawinsonde, profiler, surface, and satellite winds. The synthetic satellite wind observations are colocated with the NR cloud fields, and the rawinsondes are advected during ascent using the NR wind fields. Data counts for the synthetic observations are matched as closely as possible to real data counts, as shown in Figure 2. Errors are added to the synthetic observations to emulate representativeness and instrument errors. The synthetic errors are calibrated so that the statistics of observation innovation and analysis increments in the OSSE are similar to the same statistics for assimilation of real observations, in an iterative method described by Errico et al (2013). The standard deviations of observation minus forecast (xo-H(xb)) are compared for the OSSE and real data in Figure 3. The synthetic errors include both random, uncorrelated errors, and an additional correlated error component for some observational types. Vertically correlated errors are included for conventional sounding data and GPS-RO, and channel correlated errors are introduced to AIRS and IASI (Figure 4). HIRS, AMSU-A, and MHS have a component of horizontally

A Digital Video System for Observing and Recording Occultations

NASA Astrophysics Data System (ADS)

Barry, M. A. Tony; Gault, Dave; Pavlov, Hristo; Hanna, William; McEwan, Alistair; Filipović, Miroslav D.

2015-09-01

Stellar occultations by asteroids and outer solar system bodies can offer ground based observers with modest telescopes and camera equipment the opportunity to probe the shape, size, atmosphere, and attendant moons or rings of these distant objects. The essential requirements of the camera and recording equipment are: good quantum efficiency and low noise; minimal dead time between images; good horological faithfulness of the image timestamps; robustness of the recording to unexpected failure; and low cost. We describe an occultation observing and recording system which attempts to fulfil these requirements and compare the system with other reported camera and recorder systems. Five systems have been built, deployed, and tested over the past three years, and we report on three representative occultation observations: one being a 9 ± 1.5 s occultation of the trans-Neptunian object 28978 Ixion (m v =15.2) at 3 seconds per frame; one being a 1.51 ± 0.017 s occultation of Deimos, the 12 km diameter satellite of Mars, at 30 frames per second; and one being a 11.04 ± 0.4 s occultation, recorded at 7.5 frames per second, of the main belt asteroid 361 Havnia, representing a low magnitude drop (Δm v = ~0.4) occultation.

Data acquisition system for operational earth observation missions

NASA Technical Reports Server (NTRS)

Deerwester, J. M.; Alexander, D.; Arno, R. D.; Edsinger, L. E.; Norman, S. M.; Sinclair, K. F.; Tindle, E. L.; Wood, R. D.

1972-01-01

The data acquisition system capabilities expected to be available in the 1980 time period as part of operational Earth observation missions are identified. By data acquisition system is meant the sensor platform (spacecraft or aircraft), the sensors themselves and the communication system. Future capabilities and support requirements are projected for the following sensors: film camera, return beam vidicon, multispectral scanner, infrared scanner, infrared radiometer, microwave scanner, microwave radiometer, coherent side-looking radar, and scatterometer.

The Global Geodetic Observing System: Recent Activities and Accomplishments

NASA Astrophysics Data System (ADS)

Gross, R. S.

2017-12-01

The Global Geodetic Observing System (GGOS) of the International Association of Geodesy (IAG) provides the basis on which future advances in geosciences can be built. By considering the Earth system as a whole (including the geosphere, hydrosphere, cryosphere, atmosphere and biosphere), monitoring Earth system components and their interactions by geodetic techniques and studying them from the geodetic point of view, the geodetic community provides the global geosciences community with a powerful tool consisting mainly of high-quality services, standards and references, and theoretical and observational innovations. The mission of GGOS is: (a) to provide the observations needed to monitor, map and understand changes in the Earth's shape, rotation and mass distribution; (b) to provide the global frame of reference that is the fundamental backbone for measuring and consistently interpreting key global change processes and for many other scientific and societal applications; and (c) to benefit science and society by providing the foundation upon which advances in Earth and planetary system science and applications are built. The goals of GGOS are: (1) to be the primary source for all global geodetic information and expertise serving society and Earth system science; (2) to actively promote, sustain, improve, and evolve the integrated global geodetic infrastructure needed to meet Earth science and societal requirements; (3) to coordinate with the international geodetic services that are the main source of key parameters and products needed to realize a stable global frame of reference and to observe and study changes in the dynamic Earth system; (4) to communicate and advocate the benefits of GGOS to user communities, policy makers, funding organizations, and society. In order to accomplish its mission and goals, GGOS depends on the IAG Services, Commissions, and Inter-Commission Committees. The Services provide the infrastructure and products on which all contributions

IEOOS: the Spanish Institute of Oceanography Observing System

NASA Astrophysics Data System (ADS)

Tel, Elena; Balbin, Rosa; Cabanas, Jose-Manuel; Garcia, Maria-Jesus; Garcia-Martinez, M. Carmen; Gonzalez-Pola, Cesar; Lavin, Alicia; Lopez-Jurado, Jose-Luis; Rodriguez, Carmen; Ruiz-Villarreal, Manuel; Sánchez-Leal, Ricardo F.; Vargas-Yáñez, Manuel; Vélez-Belchí, Pedro

2016-03-01

Since its foundation, 100 years ago, the Spanish Institute of Oceanography (IEO) has been observing and measuring the ocean characteristics. Here is a summary of the initiatives of the IEO in the field of the operational oceanography. Some systems like the tide gauges network has been working for more than 70 years. The standard sections began at different moments depending on the local projects, and nowadays there are more than 180 coastal stations and deep-sea ones that are systematically sampled, obtaining physical and biochemical measurements. At this moment, the Observing System includes six permanent moorings equipped with current meters, an open-sea ocean-meteorological buoy offshore Santander and a sea-surface temperature satellite image station. It also supports the Spanish contribution to the Argo international programme with 47 deployed profilers, and continuous monitoring thermosalinometers, meteorological stations and vessel-mounted acoustic Doppler current profilers on the research vessel fleet. The system is completed with the contribution to the Northwest Iberian peninsula and Gibraltar observatories, and the development of regional prediction models. All these systematic measurements allow the IEO to give responses to ocean research activities, official agencies requirements and industrial and main society demands such as navigation, resource management, risks management, recreation, as well as for management development pollution-related economic activities or marine ecosystems. All these networks are linked to international initiatives, framed largely in supranational programmes of Earth observation sponsored by the United Nations or the European Union. The synchronic observation system permits a spatio-temporal description of some events, such as new deep water formation in the Mediterranean Sea and the injection of heat to intermediate waters in the Bay of Biscay after some colder northern storms in winter 2005.

OSCAR/Surface: Metadata for the WMO Integrated Observing System WIGOS

NASA Astrophysics Data System (ADS)

Klausen, Jörg; Pröscholdt, Timo; Mannes, Jürg; Cappelletti, Lucia; Grüter, Estelle; Calpini, Bertrand; Zhang, Wenjian

2016-04-01

The World Meteorological Organization (WMO) Integrated Global Observing System (WIGOS) is a key WMO priority underpinning all WMO Programs and new initiatives such as the Global Framework for Climate Services (GFCS). It does this by better integrating WMO and co-sponsored observing systems, as well as partner networks. For this, an important aspect is the description of the observational capabilities by way of structured metadata. The 17th Congress of the Word Meteorological Organization (Cg-17) has endorsed the semantic WIGOS metadata standard (WMDS) developed by the Task Team on WIGOS Metadata (TT-WMD). The standard comprises of a set of metadata classes that are considered to be of critical importance for the interpretation of observations and the evolution of observing systems relevant to WIGOS. The WMDS serves all recognized WMO Application Areas, and its use for all internationally exchanged observational data generated by WMO Members is mandatory. The standard will be introduced in three phases between 2016 and 2020. The Observing Systems Capability Analysis and Review (OSCAR) platform operated by MeteoSwiss on behalf of WMO is the official repository of WIGOS metadata and an implementation of the WMDS. OSCAR/Surface deals with all surface-based observations from land, air and oceans, combining metadata managed by a number of complementary, more domain-specific systems (e.g., GAWSIS for the Global Atmosphere Watch, JCOMMOPS for the marine domain, the WMO Radar database). It is a modern, web-based client-server application with extended information search, filtering and mapping capabilities including a fully developed management console to add and edit observational metadata. In addition, a powerful application programming interface (API) is being developed to allow machine-to-machine metadata exchange. The API is based on an ISO/OGC-compliant XML schema for the WMDS using the Observations and Measurements (ISO19156) conceptual model. The purpose of the

Introduction to Observing System Simulation Experiments (OSSEs)

NASA Technical Reports Server (NTRS)

Prive, Nikki C.

2014-01-01

This presentation gives a brief overview of Observing System Simulation Experiments (OSSEs), including what OSSEs are, and how and why they are performed. The intent is to educate the audience in light of the OSSE-related sections of the Forecast Improvement Act (H.R. 2413).

Solar System Observations with the James Webb Space Telescope

NASA Technical Reports Server (NTRS)

Norwood, James; Hammel, Heidi; Milam, Stefanie; Stansberry, John; Lunine, Jonathan; Chanover, Nancy; Hines, Dean; Sonneborn, George; Tiscareno, Matthew; Brown, Michael;

Novel classification system of rib fractures observed in infants.

PubMed

Love, Jennifer C; Derrick, Sharon M; Wiersema, Jason M; Pinto, Deborrah C; Greeley, Christopher; Donaruma-Kwoh, Marcella; Bista, Bibek

2013-03-01

Rib fractures are considered highly suspicious for nonaccidental injury in the pediatric clinical literature; however, a rib fracture classification system has not been developed. As an aid and impetus for rib fracture research, we developed a concise schema for classifying rib fracture types and fracture location that is applicable to infants. The system defined four fracture types (sternal end, buckle, transverse, and oblique) and four regions of the rib (posterior, posterolateral, anterolateral, and anterior). It was applied to all rib fractures observed during 85 consecutive infant autopsies. Rib fractures were found in 24 (28%) of the cases. A total of 158 rib fractures were identified. The proposed schema was adequate to classify 153 (97%) of the observed fractures. The results indicate that the classification system is sufficiently robust to classify rib fractures typically observed in infants and should be used by researchers investigating infant rib fractures. © 2013 American Academy of Forensic Sciences.

Linear system identification via backward-time observer models

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh

1993-01-01

This paper presents an algorithm to identify a state-space model of a linear system using a backward-time approach. The procedure consists of three basic steps. First, the Markov parameters of a backward-time observer are computed from experimental input-output data. Second, the backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) from which a backward-time state-space model is realized using the Eigensystem Realization Algorithm. Third, the obtained backward-time state space model is converted to the usual forward-time representation. Stochastic properties of this approach will be discussed. Experimental results are given to illustrate when and to what extent this concept works.

Earth observing system - Concepts and implementation strategy

NASA Technical Reports Server (NTRS)

Hartle, R. E.

1986-01-01

The concepts of an Earth Observing System (EOS), an information system being developed by the EOS Science and Mission Requirements Working Group for international use and planned to begin in the 1990s, are discussed. The EOS is designed to study the factors that control the earth's hydrologic cycle, biochemical cycles, and climatologic processes by combining the measurements from remote sensing instruments, in situ measurement devices, and a data and information system. Three EOS platforms are planned to be launched into low, polar, sun-synchronous orbits during the Space Station's Initial Operating Configuration, one to be provided by ESA and two by the United States.

Evaluation of tropical Pacific observing systems using NCEP and GFDL ocean data assimilation systems

NASA Astrophysics Data System (ADS)

Xue, Yan; Wen, Caihong; Yang, Xiaosong; Behringer, David; Kumar, Arun; Vecchi, Gabriel; Rosati, Anthony; Gudgel, Rich

2017-08-01

The TAO/TRITON array is the cornerstone of the tropical Pacific and ENSO observing system. Motivated by the recent rapid decline of the TAO/TRITON array, the potential utility of TAO/TRITON was assessed for ENSO monitoring and prediction. The analysis focused on the period when observations from Argo floats were also available. We coordinated observing system experiments (OSEs) using the global ocean data assimilation system (GODAS) from the National Centers for Environmental Prediction and the ensemble coupled data assimilation (ECDA) from the Geophysical Fluid Dynamics Laboratory for the period 2004-2011. Four OSE simulations were conducted with inclusion of different subsets of in situ profiles: all profiles (XBT, moorings, Argo), all except the moorings, all except the Argo and no profiles. For evaluation of the OSE simulations, we examined the mean bias, standard deviation difference, root-mean-square difference (RMSD) and anomaly correlation against observations and objective analyses. Without assimilation of in situ observations, both GODAS and ECDA had large mean biases and RMSD in all variables. Assimilation of all in situ data significantly reduced mean biases and RMSD in all variables except zonal current at the equator. For GODAS, the mooring data is critical in constraining temperature in the eastern and northwestern tropical Pacific, while for ECDA both the mooring and Argo data is needed in constraining temperature in the western tropical Pacific. The Argo data is critical in constraining temperature in off-equatorial regions for both GODAS and ECDA. For constraining salinity, sea surface height and surface current analysis, the influence of Argo data was more pronounced. In addition, the salinity data from the TRITON buoys played an important role in constraining salinity in the western Pacific. GODAS was more sensitive to withholding Argo data in off-equatorial regions than ECDA because it relied on local observations to correct model biases and

Towards An Oceanographic Component Of A Global Earth Observation System Of Systems: Progress And Challenges

NASA Astrophysics Data System (ADS)

Ackleson, S. G.

2012-12-01

Ocean observatories (systems of coordinated sensors and platforms providing real-time in situ observations across multiple temporal and spatial scales) have advanced rapidly during the past several decades with the integration of novel hardware, development of advanced cyber-infrastructures and data management software, and the formation of researcher networks employing fixed, drifting, and mobile assets. These advances have provided persistent, real-time, multi-disciplinary observations representing even the most extreme environmental conditions, enabled unique and informative views of complicated ocean processes, and aided in the development of more accurate and higher fidelity ocean models. Combined with traditional ship-based and remotely sensed observations, ocean observatories have yielded new knowledge across a broad spectrum of earth-ocean scales that would likely not exist otherwise. These developments come at a critical time in human history when the demands of global population growth are creating unprecedented societal challenges associated with rapid climatic change and unsustainable consumption of key ocean resources. Successfully meeting and overcoming these challenges and avoiding the ultimate tragedy of the commons will require greater knowledge of environmental processes than currently exists, including interactions between the ocean, the overlying atmosphere, and the adjacent land and synthesizing new knowledge into effective policy and management structures. To achieve this, researchers must have free and ready access to comprehensive data streams (oceanic, atmospheric, and terrestrial), regardless of location and collection system. While the precedent for the concept of free and open access to environmental data is not new (it traces back to the International Geophysical Year, 1957), implementing procedures and standards on a global scale is proving to be difficult, both logistically and politically. Observatories have been implemented in many

Observer Use of Standardized Observation Protocols in Consequential Observation Systems

ERIC Educational Resources Information Center

Bell, Courtney A.; Yi, Qi; Jones, Nathan D.; Lewis, Jennifer M.; McLeod, Monica; Liu, Shuangshuang

2014-01-01

Evidence from a handful of large-scale studies suggests that although observers can be trained to score reliably using observation protocols, there are concerns related to initial training and calibration activities designed to keep observers scoring accurately over time (e.g., Bell, et al, 2012; BMGF, 2012). Studies offer little insight into how…

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

NASA Technical Reports Server (NTRS)

King, Michael D.

2004-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special but not exclusive look at the latest earth observing mission, Aura.

NASA's Earth Observing System (EOS): Observing the Atmosphere, Land, Oceans, and Ice from Space

NASA Technical Reports Server (NTRS)

King, Michael D.

2005-01-01

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by whch scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. During this year, the last of the first series of EOS missions, Aura, was launched. Aura is designed exclusively to conduct research on the composition, chemistry, and dynamics of the Earth's upper and lower atmosphere, employing multiple instruments on a single spacecraft. Aura is the third in a series of major Earth observing satellites to study the environment and climate change and is part of NASA's Earth Science Enterprise. The first and second missions, Terra and Aqua, are designed to study the land, oceans, atmospheric constituents (aerosols, clouds, temperature, and water vapor), and the Earth's radiation budget. The other seven EOS spacecraft include satellites to study (i) land cover & land use change, (ii) solar irradiance and solar spectral variation, (iii) ice volume, (iv) ocean processes (vector wind and sea surface topography), and (v) vertical variations of clouds, water vapor, and aerosols up to and including the stratosphere. Aura's chemistry measurements will also follow up on measurements that began with NASA's Upper Atmosphere Research Satellite and continue the record of satellite ozone data collected from the TOMS missions. In this presentation I will describe how scientists are using EOS data to examine the health of the earth's atmosphere, including atmospheric chemistry, aerosol properties, and cloud properties, with a special look at the latest earth observing mission, Aura.

The 1990 Reference Handbook: Earth Observing System

NASA Technical Reports Server (NTRS)

1990-01-01

An overview of the Earth Observing System (EOS) including goals and requirements is given. Its role in the U.S. Global Change Research Program and the International--Biosphere Program is addressed. The EOS mission requirements, science, fellowship program, data and information systems architecture, data policy, space measurement, and mission elements are presented along with the management of EOS. Descriptions of the facility instruments, instrument investigations, and interdisciplinary investigations are also present. The role of the National Oceanic and Atmospheric Administration in the mission is mentioned.

Development of KIAPS Observation Processing Package for Data Assimilation System

NASA Astrophysics Data System (ADS)

Kang, Jeon-Ho; Chun, Hyoung-Wook; Lee, Sihye; Han, Hyun-Jun; Ha, Su-Jin

2015-04-01

The Korea Institute of Atmospheric Prediction Systems (KIAPS) was founded in 2011 by the Korea Meteorological Administration (KMA) to develop Korea's own global Numerical Weather Prediction (NWP) system as nine year (2011-2019) project. Data assimilation team at KIAPS has been developing the observation processing system (KIAPS Package for Observation Processing: KPOP) to provide optimal observations to the data assimilation system for the KIAPS Global Model (KIAPS Integrated Model - Spectral Element method based on HOMME: KIM-SH). Currently, the KPOP is capable of processing the satellite radiance data (AMSU-A, IASI), GPS Radio Occultation (GPS-RO), AIRCRAFT (AMDAR, AIREP, and etc…), and synoptic observation (SONDE and SURFACE). KPOP adopted Radiative Transfer for TOVS version 10 (RTTOV_v10) to get brightness temperature (TB) for each channel at top of the atmosphere (TOA), and Radio Occultation Processing Package (ROPP) 1-dimensional forward module to get bending angle (BA) at each tangent point. The observation data are obtained from the KMA which has been composited with BUFR format to be converted with ODB that are used for operational data assimilation and monitoring at the KMA. The Unified Model (UM), Community Atmosphere - Spectral Element (CAM-SE) and KIM-SH model outputs are used for the bias correction (BC) and quality control (QC) of the observations, respectively. KPOP provides radiance and RO data for Local Ensemble Transform Kalman Filter (LETKF) and also provides SONDE, SURFACE and AIRCRAFT data for Three-Dimensional Variational Assimilation (3DVAR). We are expecting all of the observation type which processed in KPOP could be combined with both of the data assimilation method as soon as possible. The preliminary results from each observation type will be introduced with the current development status of the KPOP.

Experimental land observing data system feasibility study

NASA Technical Reports Server (NTRS)

Buckley, J. L.; Kraiman, H.

1982-01-01

An end-to-end data system to support a Shuttle-based Multispectral Linear Array (MLA) mission in the mid-1980's was defined. The experimental Land Observing System (ELOS) is discussed. A ground system that exploits extensive assets from the LANDSAT-D Program to effectively meet the objectives of the ELOS Mission was defined. The goal of 10 meter pixel precision, the variety of data acquisition capabilities, and the use of Shuttle are key to the mission requirements, Ground mission management functions are met through the use of GSFC's Multi-Satellite Operations Control Center (MSOCC). The MLA Image Generation Facility (MIGF) combines major hardware elements from the Applications Development Data System (ADDS) facility and LANDSAT Assessment System (LAS) with a special purpose MLA interface unit. LANDSAT-D image processing techniques, adapted to MLA characteristics, form the basis for the use of existing software and the definition of new software required.

Value of Available Global Soil Moisture Products for Agricultural Monitoring

NASA Astrophysics Data System (ADS)

Mladenova, Iliana; Bolten, John; Crow, Wade; de Jeu, Richard

2016-04-01

The first operationally derived and publicly distributed global soil moil moisture product was initiated with the launch of the Advanced Scanning Microwave Mission on the NASA's Earth Observing System Aqua satellite (AMSR-E). AMSR-E failed in late 2011, but its legacy is continued by AMSR2, launched in 2012 on the JAXA Global Change Observation Mission-Water (GCOM-W) mission. AMSR is a multi-frequency dual-polarization instrument, where the lowest two frequencies (C- and X-band) were used for soil moisture retrieval. Theoretical research and small-/field-scale airborne campaigns, however, have demonstrated that soil moisture would be best monitored using L-band-based observations. This consequently led to the development and launch of the first L-band-based mission-the ESA's Soil Moisture Ocean Salinity (SMOS) mission (2009). In early 2015 NASA launched the second L-band-based mission, the Soil Moisture Active Passive (SMAP). These satellite-based soil moisture products have been demonstrated to be invaluable sources of information for mapping water stress areas, crop monitoring and yield forecasting. Thus, a number of agricultural agencies routinely utilize and rely on global soil moisture products for improving their decision making activities, determining global crop production and crop prices, identifying food restricted areas, etc. The basic premise of applying soil moisture observations for vegetation monitoring is that the change in soil moisture conditions will precede the change in vegetation status, suggesting that soil moisture can be used as an early indicator of expected crop condition change. Here this relationship was evaluated across multiple microwave frequencies by examining the lag rank cross-correlation coefficient between the soil moisture observations and the Normalized Difference Vegetation Index (NDVI). A main goal of our analysis is to evaluate and inter-compare the value of the different soil moisture products derived using L-band (SMOS

An optimization approach for observation association with systemic uncertainty applied to electro-optical systems

NASA Astrophysics Data System (ADS)

Worthy, Johnny L.; Holzinger, Marcus J.; Scheeres, Daniel J.

2018-06-01

The observation to observation measurement association problem for dynamical systems can be addressed by determining if the uncertain admissible regions produced from each observation have one or more points of intersection in state space. An observation association method is developed which uses an optimization based approach to identify local Mahalanobis distance minima in state space between two uncertain admissible regions. A binary hypothesis test with a selected false alarm rate is used to assess the probability that an intersection exists at the point(s) of minimum distance. The systemic uncertainties, such as measurement uncertainties, timing errors, and other parameter errors, define a distribution about a state estimate located at the local Mahalanobis distance minima. If local minima do not exist, then the observations are not associated. The proposed method utilizes an optimization approach defined on a reduced dimension state space to reduce the computational load of the algorithm. The efficacy and efficiency of the proposed method is demonstrated on observation data collected from the Georgia Tech Space Object Research Telescope.

The function of the earth observing system - Data information system Distributed Active Archive Centers

NASA Technical Reports Server (NTRS)

Lapenta, C. C.

1992-01-01

The functionality of the Distributed Active Archive Centers (DAACs) which are significant elements of the Earth Observing System Data and Information System (EOSDIS) is discussed. Each DAAC encompasses the information management system, the data archival and distribution system, and the product generation system. The EOSDIS DAACs are expected to improve the access to earth science data set needed for global change research.

Chandra X-Ray Observatory Observations of the Jovian System

NASA Technical Reports Server (NTRS)

Elsner, R. F.; Bhardwaj, A.; Gladstone, R.; Waite, J. H.; Ford, P.; Branduari-Raymont, G.

2005-01-01

Chandra X-ray Observatory (CXO) and XMM-Newton observations of x-rays from the Jovian system have answered questions that arose from early observations with the Einstein and Rosat X-ray Observatories, but in the process of vastly increasing our knowledge of x-ray emission from Jupiter and its environs they have also raised new questions and point to new opportunities for future studies. We will review recent x-ray results on the Jovian system, from the point of view of the CXO, and discuss various questions that have arisen in the course of our studies. We will discuss prospects for more observations in the immediate future, and how they might address open questions. Finally we will briefly describe ways in which an imaging x-ray spectrometer in the vicinity of the Jovian system could provide a wealth of data and results concerning Jupiter's x-ray auroral and disk emission, elemental abundance measurements for the Galilean moons, and detailed studies of x-ray emission from the Io Plasma Torus.

Sea Surface Salinity : Research Challenges and Opportunities

NASA Technical Reports Server (NTRS)

Halpern, David; Lagerloef, Gary; Font, Jordi

2012-01-01

Sea surface salinity (SSS) can be important in regulating sea surface temperature (SST). Two technological breakthrough satellite SSS missions, Aquarius and Soil Moisture and Ocean Salinity (SMOS), are currently producing high-quality SSS data. This paper provides an overview of the importance of SSS for weather and climate applications and describes the Aquarius and SMOS missions. The newness of adequately sampled SSS data prompted a first-time at-sea field campaign devoted to improved understanding of SSS variations.

Earth observing system. Data and information system. Volume 2A: Report of the EOS Data Panel

NASA Technical Reports Server (NTRS)

1986-01-01

The purpose of this report is to provide NASA with a rationale and recommendations for planning, implementing, and operating an Earth Observing System data and information system that can evolve to meet the Earth Observing System's needs in the 1990s. The Earth Observing System (Eos), defined by the Eos Science and Mission Requirements Working Group, consists of a suite of instruments in low Earth orbit acquiring measurements of the Earth's atmosphere, surface, and interior; an information system to support scientific research; and a vigorous program of scientific research, stressing study of global-scale processes that shape and influence the Earth as a system. The Eos data and information system is conceived as a complete research information system that would transcend the traditional mission data system, and include additional capabilties such as maintaining long-term, time-series data bases and providing access by Eos researchers to relevant non-Eos data. The Working Group recommends that the Eos data and information system be initiated now, with existing data, and that the system evolve into one that can meet the intensive research and data needs that will exist when Eos spacecraft are returning data in the 1990s.

Industrial use of land observation satellite systems

NASA Technical Reports Server (NTRS)

Henderson, F. B., III

1984-01-01

The principal industrial users of land observation satellite systems are the geological industries; oil/gas, mining, and engineering/environmental companies. The primary system used is LANDSAT/MSS. Currently, use is also being made of the limited amounts of SKYLAB photography, SEASAT and SIR-A radar, and the new LANDSAT/TM data available. Although considered experimental, LANDSAT data is now used operationally by several hundred exploration and engineering companies worldwide as a vastly improved geological mapping tool to help direct more expensive geophysical and drilling phases, leading to more efficient decision-making and results. Future needs include global LANDSAT/TM; higher spatial resolution; stereo and radar; improved data handling, processing distribution and archiving systems, and integrated geographical information systems (GIS). For a promising future, governments must provide overall continuity (government and/or private sector) of such systems, insure continued government R and D, and commit to operating internationally under the civil Open Skies policy.

Virtual Estimator for Piecewise Linear Systems Based on Observability Analysis

PubMed Central

Morales-Morales, Cornelio; Adam-Medina, Manuel; Cervantes, Ilse; Vela-Valdés and, Luis G.; García Beltrán, Carlos Daniel

2013-01-01

This article proposes a virtual sensor for piecewise linear systems based on observability analysis that is in function of a commutation law related with the system's outpu. This virtual sensor is also known as a state estimator. Besides, it presents a detector of active mode when the commutation sequences of each linear subsystem are arbitrary and unknown. For the previous, this article proposes a set of virtual estimators that discern the commutation paths of the system and allow estimating their output. In this work a methodology in order to test the observability for piecewise linear systems with discrete time is proposed. An academic example is presented to show the obtained results. PMID:23447007

Telescope Automation and Remote Observing System (TAROS)

NASA Astrophysics Data System (ADS)

Wilson, G.; Czezowski, A.; Hovey, G. R.; Jarnyk, M. A.; Nielsen, J.; Roberts, B.; Sebo, K.; Smith, D.; Vaccarella, A.; Young, P.

2005-12-01

TAROS is a system that will allow for the Australian National University telescopes at a remote location to be operated automatically or interactively with authenticated control via the internet. TAROS is operated by a Java front-end GUI and employs the use of several Java technologies - such as Java Message Service (JMS) for communication between the telescope and the remote observer, Java Native Interface to integrate existing data acquisition software written in C++ (CICADA) with new Java programs and the JSky collection of Java GUI components for parts of the remote observer client. In this poster the design and implementation of TAROS is described.

ORAC: a modern observing system for UKIRT

NASA Astrophysics Data System (ADS)

Bridger, Alan; Wright, Gillian S.; Economou, Frossie; Tan, Min; Currie, Malcolm J.; Pickup, David A.; Adamson, Andrew J.; Rees, Nicholas P.; Purves, Maren; Kackley, Russell

2000-06-01

The steady improvement in telescope performance at UKIRT and the increase in data acquisition rates led to a strong desired for an integrated observing framework that would meet the needs of future instrumentation, as well as providing some support for existing instrumentation. Thus the Observatory Reduction and Acquisition Control (ORAC) project was created in 1997 with the goals of improving the scientific productivity in the telescope, reducing the overall ongoing support requirements, and eventually supporting the use of more flexibly scheduled observing. The project was also expected to achieve this within a tight resource allocation. In October 1999 the ORAC system was commissioned at the United Kingdom Infrared Telescope.

The NOAA Satellite Observing System Architecture Study

NASA Technical Reports Server (NTRS)

Volz, Stephen; Maier, Mark; Di Pietro, David

2016-01-01

NOAA is beginning a study, the NOAA Satellite Observing System Architecture (NSOSA) study, to plan for the future operational environmental satellite system that will follow GOES and JPSS, beginning about 2030. This is an opportunity to design a modern architecture with no pre-conceived notions regarding instruments, platforms, orbits, etc. The NSOSA study will develop and evaluate architecture alternatives to include partner and commercial alternatives that are likely to become available. The objectives will include both functional needs and strategic characteristics (e.g., flexibility, responsiveness, sustainability). Part of this study is the Space Platform Requirements Working Group (SPRWG), which is being commissioned by NESDIS. The SPRWG is charged to assess new or existing user needs and to provide relative priorities for observational needs in the context of the future architecture. SPRWG results will serve as input to the process for new foundational (Level 0 and Level 1) requirements for the next generation of NOAA satellites that follow the GOES-R, JPSS, DSCOVR, Jason-3, and COSMIC-2 missions.

Defining the Canary Islands Oceanic Platform (PLOCAN) Observing System mission

NASA Astrophysics Data System (ADS)

Delory, Eric; Hernández-Brito, Joaquín.; Llínas, Octavio

2010-05-01

A permanent multidisciplinary ocean observing system is planned as both a technological and scientific infrastructure for the Canary Islands Oceanic Platform (PLOCAN). The first component of its two-fold mission is to respond to systems and processes' in-situ environmental testing, certification and benchmarking requirements. This will generally take place in dedicated oceanic experimental areas, from the vicinity of the platform to the deep ocean. While these areas and related infrastructures still are at definition stage, an anticipated prerequisite is that testbed observing assets will have to provide a broad range of measurements in agreement with, as well as in contribution to, current and upcoming environmental and technical standards. The second component is to contribute to the global effort towards continuous and real-time multidisciplinary ocean observations. Related activities will encompass climate change parameters characterization as well as important regional specificities like the preservation and study of the region's unique marine biodiversity and sparsely explored seabed. Continuous sampling is planned to progressively expand from the platform vicinity down to the end of the continental slope - to about 3000m depth, the surrounding seabed and water column, then scale up to the region, through mobile systems and fixed open-ocean stations. Such a large and diverse spectrum of observing activities stems from the fact that the PLOCAN observing system is at the center of a long-term strategy, thus granting the opportunity to plan its mission by way of an ambitious set of ocean measurement methods and technologies.

The European Marine Observing Network and the development of an Integrated European Ocean Observing System. An EuroGOOS perspective

NASA Astrophysics Data System (ADS)

Fernandez, Vicente; Gorringe, Patrick; Nolan, Glenn

2016-04-01

The ocean benefits many sectors of society, being the biggest reservoir of heat, water, carbon and oxygen and playing a fundamental role regulating the earth's climate. We rely on the oceans for food, transport, energy and recreation. Therefore, a sustained marine observation network is crucial to further our understanding of the oceanic environment and to supply scientific data to meet society's need. Marine data and observations in Europe, collected primarily by state governmental agencies, is offered via five Regional Operational Oceanographic Systems (ROOS) within the context of EuroGOOS (http://www.eurogos.eu), an International Non-Profit Association of national governmental agencies and research organizations (40 members from 19 member states) committed to European-scale operational oceanography within the context of the Intergovernmental Global Ocean Observing System (GOOS). Strong cooperation within these regions, enabling the involvement of additional partners and countries, forms the basis of EuroGOOS work. Ocean data collected from different type of sensors (e.g. moored buoys, tide gauges, Ferrybox systems, High Frequency radars, gliders and profiling floats) is accessible to scientist and other end users through data portals and initiatives such as the European Marine Observations and Data Network (EMODnet) (www.emodnet.eu) and the Copernicus Marine Service Copernicus (www.copernicus.eu). Although a relatively mature European ocean observing capability already exists and its well-coordinated at European level, some gaps have been identified, for example the demand for ecosystem products and services, or the case that biogeochemical observations are still relatively sparse particularly in coastal and shelf seas. Assessing gaps based on the capacity of the observing system to answer key societal challenges e.g. site suitability for aquaculture and ocean energy, oil spill response and contextual oceanographic products for fisheries and ecosystems is still

Mission operations concepts for Earth Observing System (EOS)

NASA Technical Reports Server (NTRS)

Kelly, Angelita C.; Taylor, Thomas D.; Hawkins, Frederick J.

1991-01-01

Mission operation concepts are described which are being used to evaluate and influence space and ground system designs and architectures with the goal of achieving successful, efficient, and cost-effective Earth Observing System (EOS) operations. Emphasis is given to the general characteristics and concepts developed for the EOS Space Measurement System, which uses a new series of polar-orbiting observatories. Data rates are given for various instruments. Some of the operations concepts which require a total system view are also examined, including command operations, data processing, data accountability, data archival, prelaunch testing and readiness, launch, performance monitoring and assessment, contingency operations, flight software maintenance, and security.

Ground-based Observation System Development for the Moon Hyper-spectral Imaging

NASA Astrophysics Data System (ADS)

Wang, Yang; Huang, Yu; Wang, Shurong; Li, Zhanfeng; Zhang, Zihui; Hu, Xiuqing; Zhang, Peng

2017-05-01

The Moon provides a suitable radiance source for on-orbit calibration of space-borne optical instruments. A ground-based observation system dedicated to the hyper-spectral radiometry of the Moon has been developed for improving and validating the current lunar model. The observation instrument using a dispersive imaging spectrometer is particularly designed for high-accuracy observations of the lunar radiance. The simulation and analysis of the push-broom mechanism is made in detail for lunar observations, and the automated tracking and scanning is well accomplished in different observational condition. A three-month series of hyper-spectral imaging experiments of the Moon have been performed in the wavelength range from 400 to 1000 nm near Lijiang Observatory (Yunnan, China) at phase angles -83°-87°. Preliminary results and data comparison are presented, and it shows the instrument performance and lunar observation capability of this system are well validated. Beyond previous measurements, this observation system provides the entire lunar disk images of continuous spectral coverage by adopting the push-broom mode with special scanning scheme and leads to the further research of lunar photometric model.

Developing Vocabularies to Improve Understanding and Use of NOAA Observing Systems

NASA Astrophysics Data System (ADS)

Austin, M.

2014-12-01

The NOAA Observing System Integrated Analysis project (NOSIA II), is an attempt to capture and tell the story of how valuable observing systems are in producing products and services that are required to fulfill the NOAA's diverse mission. NOAA's goals and mission areas cover a broad range of environmental data; a complexity exists in terms and vocabulary as applied to the creation of observing system derived products. The NOSIA data collection focused first on decomposing NOAA's goals in the creation and acceptance of Mission Service Areas (MSAs) by NOAA senior leadership. Products and services that supported the MSAs were then identified through the process of interviewing product producers across NOAA organization. Product Data inputs including models, databases and observing system were also identified. The NOSIA model contains over 20,000 nodes each representing levels in a network connecting products, datasources, users and desired outcomes. An immediate need became apparent that the complexity and variety of the data collected required data management to mature the quality and the content of the NOSIA model. The NOSIA Analysis Database (ADB) was developed initially to improve consistency of terms and data types to allow for the linkage of observing systems, products and NOAA's Goals and mission. The ADB also allowed for the prototyping of reports and product generation in an easily accessible and comprehensive format for the first time. Web based visualization of relationships between products, datasources, users, producers were generated to make the information easily understood This includes developing ontologies/vocabularies that are used for the development of users type specific products for NOAA leadership, Observing System Portfolio mangers and the users of NOAA data.

Spectroradiometric considerations for advanced land observing systems

NASA Technical Reports Server (NTRS)

Slater, P. N.

1986-01-01

Research aimed at improving the inflight absolute radiometric calibration of advanced land observing systems was initiated. Emphasis was on the satellite sensor calibration program at White Sands. Topics addressed include: absolute radiometric calibration of advanced remote sensing; atmospheric effects on reflected radiation; inflight radiometric calibration; field radiometric methods for reflectance and atmospheric measurement; and calibration of field relectance radiometers.

Observing Arctic Ecology using Networked Infomechanical Systems

NASA Astrophysics Data System (ADS)

Healey, N. C.; Oberbauer, S. F.; Hollister, R. D.; Tweedie, C. E.; Welker, J. M.; Gould, W. A.

2012-12-01

Understanding ecological dynamics is important for investigation into the potential impacts of climate change in the Arctic. Established in the early 1990's, the International Tundra Experiment (ITEX) began observational inquiry of plant phenology, plant growth, community composition, and ecosystem properties as part of a greater effort to study changes across the Arctic. Unfortunately, these observations are labor intensive and time consuming, greatly limiting their frequency and spatial coverage. We have expanded the capability of ITEX to analyze ecological phenomenon with improved spatial and temporal resolution through the use of Networked Infomechanical Systems (NIMS) as part of the Arctic Observing Network (AON) program. The systems exhibit customizable infrastructure that supports a high level of versatility in sensor arrays in combination with information technology that allows for adaptable configurations to numerous environmental observation applications. We observe stereo and static time-lapse photography, air and surface temperature, incoming and outgoing long and short wave radiation, net radiation, and hyperspectral reflectance that provides critical information to understanding how vegetation in the Arctic is responding to ambient climate conditions. These measurements are conducted concurrent with ongoing manual measurements using ITEX protocols. Our NIMS travels at a rate of three centimeters per second while suspended on steel cables that are ~1 m from the surface spanning transects ~50 m in length. The transects are located to span soil moisture gradients across a variety of land cover types including dry heath, moist acidic tussock tundra, shrub tundra, wet meadows, dry meadows, and water tracks. We have deployed NIMS at four locations on the North Slope of Alaska, USA associated with 1 km2 ARCSS vegetation study grids including Barrow, Atqasuk, Toolik Lake, and Imnavait Creek. A fifth system has been deployed in Thule, Greenland beginning in

US Integrated Ocean Observing System (IOOS°): Delivering Benefits to Science and Society

NASA Astrophysics Data System (ADS)

Willis, Z. S.

2011-12-01

The United States Integrated Ocean Observing System (IOOS°) is a user-driven, coordinated network of people, organizations, and technology that generate and disseminate continuous data about our coastal waters, Great Lakes, and oceans supported by strong research and development activities. IOOS° is our Eyes on our Oceans, Coasts and Great Lakes that enable the United States to track, predict, manage, and adapt to changes in our marine environment and deliver critical information to decision makers to improve safety, enhance our economy and protect our environment. IOOS provides a major shift in the approach to ocean observing by drawing together the vast network of disparate federal and non-federal observing systems to produce a cohesive suite of data, information, and products on a sufficient geographic and temporal scale to support decision-making. Two interdependent components constitute the U.S. IOOS: (1) the global ocean component, and (2) the coastal component. The strength of IOOS is in its partnerships, starting with the federal agencies, the partnerships extend internationally for the global component and to the local level for the coastal component. The coastal component includes the national set of observations for the U.S. Ocean, Coasts and Great Lakes, a network of Regional Associations that are establishing Regional Coastal Ocean Observing Systems (RCOOS) and the Alliance for Coastal Technologies (ACT). The U.S. IOOS is our nation's contribution to the Global Ocean Observing System (GOOS) - the ocean component of the Global Earth Observation System of Systems (GEOSS).

The Southern California Coastal Ocean Observing System (SCCOOS): Developing A Coastal Observation System To Enable Both Science Based Decision Making And Scientific Discovery

NASA Astrophysics Data System (ADS)

Terrill, E.; John, O.

2005-05-01

The Southern California Coastal Ocean Observing System (SCCOOS) is a consortium that extends from Northern Baja CA in Mexico to Morro Bay at the southern edge of central California, and aims to streamline, coordinate, and further develop individual institutional efforts by creating an integrated, multidisciplinary coastal observatory in the Bight of Southern California for the benefit of society. By leveraging existing infrastructure, partnerships, and private, local, state, and federal resources, SCCOOS is developing a fully operational coastal observation system to address issues related to coastal water quality, marine life resources, and coastal hazards for end user communities spanning local, state, and federal interests. However, to establish a sensible observational approach to address these societal drivers, sound scientific approaches are required in both the system design and the transformation of data to useful products. Since IOOS and coastal components of the NSF Ocean Observatories Initiative (OOI) are not mutually exclusive within this framework, the SCCOOS consortium of observatory implementers have created an organizational structure that encourages dovetailing of OOI into the routine observations provided by the operational components of a regional IOOS. To begin the development, SCCOOS has grant funding from the California Coastal Conservancy as part of a $21M, statewide initiative to establish a Coastal Ocean Currents Monitoring Program, and funding from NOAA's Coastal Observing Technology System (COTS). In addition, SCCOOS is leveraging IT development that has been supported by the NSF Information Technology Research program Real-time observatories, Applications,and Data Manageemnt Network (ROADNET), and anticipates using developments which will result from the NSF Laboratory for Ocean Observatory Knowledge Integration Grid (LOOKING) program. The observational components now funded at SCCOOS include surface current mapping by HF radar; high

Detecting climate variations and change: New challenges for observing and data management systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karl, T.R.; Quayle, R.G.; Groisman, P.Ya.

1993-08-01

Several essential aspects of weather observing and the management of weather data related to improving knowledge of climate variations and change in the surface boundary layer and the consequences for socioeconomic and biogeophysical systems, are discussed. The issues include long-term homogeneous time series of routine weather observations; time- and space-scale resolution of datasets derived from the observations; information about observing systems, data collection systems, and data reduction algorithms; and the enhancement of weather observing systems to serve as climate observing systems. Although much has been learned from existing weather networks and methods of data management, the system is far frommore » perfect. Several vital areas have not received adequate attention. Particular improvements are needed in the interaction between network designers and climatologists; operational analyses that focus on detecting and documenting outliers and time-dependent biases within datasets; developing the means to cope with and minimize potential inhomogeneities in weather observing systems; and authoritative documentation of how various aspects of climate have or have not changed. In this last area, close attention must be given to time and space resolution of the data. In many instances the time and space resolution requirements for understanding why the climate changes are not synonymous with understanding how it has changed or varied. This is particularly true within the surface boundary layer. A standard global daily/monthly climate message should also be introduced to supplement current Global Telecommunication System's CLIMAT data. Overall, a call is made for improvements in routine weather observing, data management, and analysis systems. Routine observations have provided (and will continue to provide) most of the information regarding how the climate has changed during the last 100 years affecting where we live, work, and grow our food. 58 refs., 8 figs

LBT observations of the HR8799 planetary system

NASA Astrophysics Data System (ADS)

Mesa, D.; Arcidiacono, C.; Claudi, R. U.; Desidera, S.; Esposito, S.; Gratton, R.; Masciadri, E.

2013-09-01

We present here observations of the HR8799 planetary system performed in H and Ks band exploiting the AO system at the Large Binocular Telescope and the PISCES camera. Thanks to the excellent performence of the instrument we were able to detect for the first time the inner known planet of the system (HR8799) in the H band. Precise photometric and astrometric measures have been taken for all the four planets. Further, exploiting ours and previous astrometric results, we were able to put some limits on the planetary orbits of the four planets. The analysis of the dinamical stability of the system seems to show lower planetary masses than the ones adopted until now.

Using the SPICE system to help plan and interpret space science observations

NASA Technical Reports Server (NTRS)

Acton, Charles H., Jr.

1993-01-01

A portable multimission information system named SPICE is used to assemble, archive, and provide easy user access to viewing geometry and other ancillary information needed by space scientists to interpret observations of bodies within our solar system. The modular nature of this system lends it to use in planning such observations as well. With a successful proof of concept on Voyager, the SPICE system has been adapted to the Magellan, Galileo and Mars Observer missions, and to a variety of ground based operations. Adaptation of SPICE for Cassini and the Russian Mars 94/96 projects is underway, and work on Cassini will follow, SPICE has been used to support observation planning for moving targets on the Hubble Space Telescope Project. Applications for SPICE on earth science, space physics and other astrophysics missions are under consideration.

Observers for Systems with Nonlinearities Satisfying an Incremental Quadratic Inequality

NASA Technical Reports Server (NTRS)

Acikmese, Ahmet Behcet; Corless, Martin

2004-01-01

We consider the problem of state estimation for nonlinear time-varying systems whose nonlinearities satisfy an incremental quadratic inequality. These observer results unifies earlier results in the literature; and extend it to some additional classes of nonlinearities. Observers are presented which guarantee that the state estimation error exponentially converges to zero. Observer design involves solving linear matrix inequalities for the observer gain matrices. Results are illustrated by application to a simple model of an underwater.

A Conceptual Framework for Assessment of the Benefits of a Global Earth Observation System of Systems

NASA Astrophysics Data System (ADS)

Fritz, S.; Scholes, R. J.; Obersteiner, M.; Bouma, J.

2007-12-01

The aim of the Global Earth Observation System of Systems (GEOSS) is to contribute to human wellbeing though improving the information available to decision-makers at all levels relating to human health and safety, protection of the global environment, the reduction of losses from natural disasters, and achieving sustainable development. Specifically, GEOSS proposes that better international co-operation in the collection, interpretation and sharing of Earth Observation information is an important and cost-effective mechanism for achieving this aim. While there is a widespread intuition that this proposition is correct, at some point the following question needs to be answered: how much additional investment in Earth Observation (and specifically, in its international integration) is enough? This leads directly to some challenging subsidiary questions, such as how can the benefits of Earth Observation be assessed? What are the incremental costs of GEOSS? Are there societal benefit areas where the return on investment is higher than in others? The Geo-Bene project has developed a `benefit chain' concept as a framework for addressing these questions. The basic idea is that an incremental improvement in the observing system (including its data collection, interpretation and information-sharing aspects) will result in an improvement in the quality of decisions based on that information. This will in turn lead to better societal outcomes, which have a value. This incremental value must be judged against the incremental cost of the improved observation system. Since in many cases there will be large uncertainties in the estimation of both the costs and the benefits, and it may not be possible to express one or both of them in monetary terms, we show how order-of-magnitude approaches and a qualitative understanding of the shape of the cost-benefit curves can help guide rational investment decision in Earth Observation systems.

The Earth Observation Data for Habitat Monitoring (EODHaM) system

NASA Astrophysics Data System (ADS)

Lucas, Richard; Blonda, Palma; Bunting, Peter; Jones, Gwawr; Inglada, Jordi; Arias, Marcela; Kosmidou, Vasiliki; Petrou, Zisis I.; Manakos, Ioannis; Adamo, Maria; Charnock, Rebecca; Tarantino, Cristina; Mücher, Caspar A.; Jongman, Rob H. G.; Kramer, Henk; Arvor, Damien; Honrado, Joāo Pradinho; Mairota, Paola

2015-05-01

To support decisions relating to the use and conservation of protected areas and surrounds, the EU-funded BIOdiversity multi-SOurce monitoring System: from Space TO Species (BIO_SOS) project has developed the Earth Observation Data for HAbitat Monitoring (EODHaM) system for consistent mapping and monitoring of biodiversity. The EODHaM approach has adopted the Food and Agriculture Organization Land Cover Classification System (LCCS) taxonomy and translates mapped classes to General Habitat Categories (GHCs) from which Annex I habitats (EU Habitats Directive) can be defined. The EODHaM system uses a combination of pixel and object-based procedures. The 1st and 2nd stages use earth observation (EO) data alone with expert knowledge to generate classes according to the LCCS taxonomy (Levels 1 to 3 and beyond). The 3rd stage translates the final LCCS classes into GHCs from which Annex I habitat type maps are derived. An additional module quantifies changes in the LCCS classes and their components, indices derived from earth observation, object sizes and dimensions and the translated habitat maps (i.e., GHCs or Annex I). Examples are provided of the application of EODHaM system elements to protected sites and their surrounds in Italy, Wales (UK), the Netherlands, Greece, Portugal and India.

Enhancement of observability and protection of smart power system

NASA Astrophysics Data System (ADS)

Siddique, Abdul Hasib

It is important for a modern power grid to be smarter in order to provide reliable and sustainable supply of electricity. Traditional way of receiving data from the wired system is a very old and outdated technology. For a quicker and better response from the electric system, it is important to look at wireless systems as a feasible option. In order to enhance the observability and protection it is important to integrate wireless technology with the modern power system. In this thesis, wireless network based architecture for wide area monitoring and an alternate method for performing current measurement for protection of generators and motors, has been adopted. There are basically two part of this project. First part deals with the wide area monitoring of the power system and the second part focuses more on application of wireless technology from the protection point of view. A number of wireless method have been adopted in both the part, these includes Zigbee, analog transmission (Both AM and FM) and digital transmission. The main aim of our project was to propose a cost effective wide area monitoring and protection method which will enhance the observability and stability of power grid. A new concept of wireless integration in the power protection system has been implemented in this thesis work.

ALMA and VLA observations of the HD 141569 system

NASA Astrophysics Data System (ADS)

White, Jacob Aaron; Boley, A. C.; MacGregor, M. A.; Hughes, A. M.; Wilner, D. J.

2018-03-01

We present VLA 9 mm (33 GHz) and archival ALMA 2.9 mm (103 GHz) observations of the HD 141569 system. The VLA observations achieve a resolution of 0.25 arcsec (˜28 au) and a sensitivity of 4.7 μJy beam- 1. We find (1) a 52 ± 5 μJy point source at the location of HD 141569A that shows potential variability, (2) the detected flux is contained within the SED-inferred central clearing of the disc meaning the spectral index of the dust disc is steeper than previously inferred, and (3) the M dwarf companions are also detected and variable. Previous lower resolution VLA observations (semester 14A) found a higher flux density, interpreted as solely dust emission. When combined with ALMA observations, the VLA 14A observations suggested the spectral index, and grain size distribution of HD 141569's disc was shallow and an outlier among debris systems. Using archival ALMA observations of HD 141569 at 0.87 and 2.9 mm, we find a dust spectral index of αmm = 1.81 ± 0.20. The VLA 16A flux corresponds to a brightness temperature of ˜5 × 106 K, suggesting strong non-disc emission is affecting the inferred grain properties. The VLA 16A flux density of the M2V companion HD 141569B is 149 ± 9 μJy, corresponding to a brightness temperature of ˜2 × 108 K and suggesting significant stellar variability when compared to the VLA14A observations, which are smaller by a factor of ˜6.

Full Two-Body Problem Mass Parameter Observability Explored Through Doubly Synchronous Systems

NASA Astrophysics Data System (ADS)

Davis, Alex Benjamin; Scheeres, Daniel

2018-04-01

The full two-body problem (F2BP) is often used to model binary asteroid systems, representing the bodies as two finite mass distributions whose dynamics are influenced by their mutual gravity potential. The emergent behavior of the F2BP is highly coupled translational and rotational mutual motion of the mass distributions. For these systems the doubly synchronous equilibrium occurs when both bodies are tidally-locked and in a circular co-orbit. Stable oscillations about this equilibrium can be shown, for the nonplanar system, to be combinations of seven fundamental frequencies of the system and the mutual orbit rate. The fundamental frequencies arise as the linear periods of center manifolds identified about the equilibrium which are heavily influenced by each body’s mass parameters. We leverage these eight dynamical constraints to investigate the observability of binary asteroid mass parameters via dynamical observations. This is accomplished by proving the nonsingularity of the relationship between the frequencies and mass parameters for doubly synchronous systems. Thus we can invert the relationship to show that given observations of the frequencies, we can solve for the mass parameters of a target system. In so doing we are able to predict the estimation covariance of the mass parameters based on observation quality and define necessary observation accuracies for desired mass parameter certainties. We apply these tools to 617 Patroclus, a doubly synchronous Trojan binary and flyby target of the LUCY mission, as well as the Pluto and Charon system in order to predict mutual behaviors of these doubly synchronous systems and to provide observational requirements for these systems’ mass parameters

An operational, multistate, earth observation data management system

NASA Technical Reports Server (NTRS)

Eastwood, L. F., Jr.; Hill, C. T.; Morgan, R. P.; Gohagan, J. K.; Hays, T. R.; Ballard, R. J.; Crnkovich, G. G.; Schaeffer, M. A.

1977-01-01

State, local, and regional agencies involved in natural resources management were investigated as potential users of satellite remotely sensed data. This group's needs are assessed and alternative data management systems serving some of those needs are outlined. It is concluded that an operational earth observation data management system will be of most use to these user agencies if it provides a full range of information services -- from raw data acquisition to interpretation and dissemination of final information products.

Towards a regional coastal ocean observing system: An initial design for the Southeast Coastal Ocean Observing Regional Association

NASA Astrophysics Data System (ADS)

Seim, H. E.; Fletcher, M.; Mooers, C. N. K.; Nelson, J. R.; Weisberg, R. H.

2009-05-01

A conceptual design for a southeast United States regional coastal ocean observing system (RCOOS) is built upon a partnership between institutions of the region and among elements of the academic, government and private sectors. This design envisions support of a broad range of applications (e.g., marine operations, natural hazards, and ecosystem-based management) through the routine operation of predictive models that utilize the system observations to ensure their validity. A distributed information management system enables information flow, and a centralized information hub serves to aggregate information regionally and distribute it as needed. A variety of observing assets are needed to satisfy model requirements. An initial distribution of assets is proposed that recognizes the physical structure and forcing in the southeast U.S. coastal ocean. In-situ data collection includes moorings, profilers and gliders to provide 3D, time-dependent sampling, HF radar and surface drifters for synoptic sampling of surface currents, and satellite remote sensing of surface ocean properties. Nested model systems are required to properly represent ocean conditions from the outer edge of the EEZ to the watersheds. An effective RCOOS will depend upon a vital "National Backbone" (federally supported) system of in situ and satellite observations, model products, and data management. This dependence highlights the needs for a clear definition of the National Backbone components and a Concept of Operations (CONOPS) that defines the roles, functions and interactions of regional and federal components of the integrated system. A preliminary CONOPS is offered for the Southeast (SE) RCOOS. Thorough system testing is advocated using a combination of application-specific and process-oriented experiments. Estimates of costs and personnel required as initial components of the SE RCOOS are included. Initial thoughts on the Research and Development program required to support the RCOOS are

El Nino and the Global Ocean Observing System

NASA Technical Reports Server (NTRS)

Halpern, David

1999-01-01

Until a decade ago, an often-quoted expression in oceanography is that very few observations are recorded throughout the ocean. Now, the sentiment is no longer valid in the uppermost 10% of the tropical Pacific Ocean nor at the surface of the global ocean. One of the remarkable legacies of the 1985-1994 Tropical Oceans Global Atmosphere (TOGA) Program is an in situ marine meteorological and upper oceanographic measurement array throughout the equatorial Pacific to monitor the development and maintenance of El Nino episodes. The TOGA Observing System, which initially consisted of moored- and drifting-buoy arrays, a network of commercial ships, and coastal and island stations, now includes a constellation of satellites and data-assimilating models to simulate subsurface oceanographic conditions. The El Nino and La Nina tropical Pacific Ocean observing system represents the initial phase of an integrated global ocean observing system. Remarkable improvements have been made in ocean model simulation of subsurface currents, but some problems persist. For example, the simulation of the South Equatorial Current (SEC) remains an important challenge in the 2S-2N Pacific equatorial wave guide. During El Nino the SEC at the equator is reduced and sometimes the direction is reversed, becoming eastward. Both conditions allow warm water stored in the western Pacific to invade the eastern region, creating an El Nino episode. Assimilation of data is a tenet of faith to correct simulation errors caused by deficiencies in surface fluxes (especially wind stress) and parameterizations of subgrid-scale physical processes. In the first of two numerical experiments, the Pacific SEC was simulated with and without assimilation of subsurface temperature data. Along the equator, a very weak SEC occurred throughout the eastern Pacific, independent of assimilation of data. However, as displayed in the diagram, in the western Pacific there was no satisfactory agreement between the two

Extreme AO Observations of Two Triple Asteroid Systems with SPHERE

NASA Astrophysics Data System (ADS)

Yang, B.; Wahhaj, Z.; Beauvalet, L.; Marchis, F.; Dumas, C.; Marsset, M.; Nielsen, E. L.; Vachier, F.

2016-04-01

We present the discovery of a new satellite of asteroid (130) Elektra—S/2014 (130) 1—in differential imaging and in integral field spectroscopy data over multiple epochs obtained with Spectro-Polarimetric High-contrast Exoplanet Research/Very Large Telescope. This new (second) moonlet of Elektra is about 2 km across, on an eccentric orbit, and about 500 km away from the primary. For a comparative study, we also observed another triple asteroid system, (93) Minerva. For both systems, component-resolved reflectance spectra of the satellites and primary were obtained simultaneously. No significant spectral difference was observed between the satellites and the primary for either triple system. We find that the moonlets in both systems are more likely to have been created by sub-disruptive impacts as opposed to having been captured.

Sliding mode control-based linear functional observers for discrete-time stochastic systems

NASA Astrophysics Data System (ADS)

Singh, Satnesh; Janardhanan, Sivaramakrishnan

2017-11-01

Sliding mode control (SMC) is one of the most popular techniques to stabilise linear discrete-time stochastic systems. However, application of SMC becomes difficult when the system states are not available for feedback. This paper presents a new approach to design a SMC-based functional observer for discrete-time stochastic systems. The functional observer is based on the Kronecker product approach. Existence conditions and stability analysis of the proposed observer are given. The control input is estimated by a novel linear functional observer. This approach leads to a non-switching type of control, thereby eliminating the fundamental cause of chatter. Furthermore, the functional observer is designed in such a way that the effect of process and measurement noise is minimised. Simulation example is given to illustrate and validate the proposed design method.

NIRCam Coronagraphic Observations of Disks and Planetary Systems

NASA Astrophysics Data System (ADS)

Beichman, Charles A.; Ygouf, Marie; Gaspar, Andras; NIRCam Science Team

2017-06-01

The NIRCam coronagraph offers a dramatic increase in sensitivity at wavelengths of 3-5 um where young planets are brightest. While large ground-based telescopes with Extreme Adaptive Optics have an advantage in inner working angle, NIRCam's sensitivity will allow high precision photometry for known planets and searches for planets with masses below that of Saturn. For debris disk science NIRCam observations will address the scattering properties of dust, look for evidence of ices and tholins, and search for planets which affect the structure of the disk itself.The NIRCam team's GTO program includes medium-band filter observations of known young planets having 1-5 Jupiter masses. A collaborative program with the MIRI team will provide coronagraphic observations at longer wavelengths. The combined dataset will yield the exoplanet’s total luminosity and effective temperature, an estimate of the initial entropy of the newly-formed planet, and the retrieval of atmospheric properties.The program will also make deep searches for lower mass planets toward known planetary systems, nearby young M stars and debris disk systems. Achievable mass limits range from ~1 Jupiter mass beyond 20 AU for the brightest A stars to perhaps a Uranus mass within 10 AU for the closest M stars.We will discuss details of the coronagraphic program for both the exoplanet and debris disk cases with an emphasis on using APT to optimize the observations of target and reference stars.

Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Mannucci, Anthony J.; Verkhoglyadova, Olga; Stephens, Philip; Iijima, Bryron A.

2013-01-01

Modeling and imaging the Earth's ionosphere as well as understanding its structures, inhomogeneities, and disturbances is a key part of NASA's Heliophysics Directorate science roadmap. This invention provides a design tool for scientific missions focused on the ionosphere. It is a scientifically important and technologically challenging task to assess the impact of a new observation system quantitatively on our capability of imaging and modeling the ionosphere. This question is often raised whenever a new satellite system is proposed, a new type of data is emerging, or a new modeling technique is developed. The proposed constellation would be part of a new observation system with more low-Earth orbiters tracking more radio occultation signals broadcast by Global Navigation Satellite System (GNSS) than those offered by the current GPS and COSMIC observation system. A simulation system was developed to fulfill this task. The system is composed of a suite of software that combines the Global Assimilative Ionospheric Model (GAIM) including first-principles and empirical ionospheric models, a multiple- dipole geomagnetic field model, data assimilation modules, observation simulator, visualization software, and orbit design, simulation, and optimization software.

A data delivery system for IMOS, the Australian Integrated Marine Observing System

NASA Astrophysics Data System (ADS)

Proctor, R.; Roberts, K.; Ward, B. J.

2010-09-01

The Integrated Marine Observing System (IMOS, www.imos.org.au), an AUD 150 m 7-year project (2007-2013), is a distributed set of equipment and data-information services which, among many applications, collectively contribute to meeting the needs of marine climate research in Australia. The observing system provides data in the open oceans around Australia out to a few thousand kilometres as well as the coastal oceans through 11 facilities which effectively observe and measure the 4-dimensional ocean variability, and the physical and biological response of coastal and shelf seas around Australia. Through a national science rationale IMOS is organized as five regional nodes (Western Australia - WAIMOS, South Australian - SAIMOS, Tasmania - TASIMOS, New SouthWales - NSWIMOS and Queensland - QIMOS) surrounded by an oceanic node (Blue Water and Climate). Operationally IMOS is organized as 11 facilities (Argo Australia, Ships of Opportunity, Southern Ocean Automated Time Series Observations, Australian National Facility for Ocean Gliders, Autonomous Underwater Vehicle Facility, Australian National Mooring Network, Australian Coastal Ocean Radar Network, Australian Acoustic Tagging and Monitoring System, Facility for Automated Intelligent Monitoring of Marine Systems, eMarine Information Infrastructure and Satellite Remote Sensing) delivering data. IMOS data is freely available to the public. The data, a combination of near real-time and delayed mode, are made available to researchers through the electronic Marine Information Infrastructure (eMII). eMII utilises the Australian Academic Research Network (AARNET) to support a distributed database on OPeNDAP/THREDDS servers hosted by regional computing centres. IMOS instruments are described through the OGC Specification SensorML and where-ever possible data is in CF compliant netCDF format. Metadata, conforming to standard ISO 19115, is automatically harvested from the netCDF files

Earth Observing System. Science and Mission Requirements, Volume 1, Part 1

NASA Technical Reports Server (NTRS)

1984-01-01

The Earth Observing System (EOS) is a planned NASA program, which will carry the multidisciplinary Earth science studies employing a variety of remote sensing techniques in the 1990's, as a prime mission, using the Space Station polar platform. The scientific rationale, recommended observational needs, the broad system configuration and a recommended implementation strategy to achieve the stated mission goals are provided.

State deadbeat response and observability in multi-modal systems

NASA Technical Reports Server (NTRS)

Conner, L. T., Jr.; Stanford, D. P.

1984-01-01

Two aspects of multimodal systems are examined. It is shown that any completely controllable system with state dimension n not exceeding three allows a choice of feedback matrices resulting in a state deadbeat response. Some of the results presented here are valid for arbitrary n, and it is suggested that for all n the state deadbeat response can be obtained under the hypothesis of complete controllability. The controllability canonical form for a multimodal system is refined by introducing a notion of observability which is dual to controllability for these systems.

Development of the AuScope Australian Earth Observing System

NASA Astrophysics Data System (ADS)

Rawling, T.

2017-12-01

Advances in monitoring technology and significant investment in new national research initiatives, will provide significant new opportunities for delivery of novel geoscience data streams from across the Australian continent over the next decade. The AuScope Australian Earth Observing System (AEOS) is linking field and laboratory infrastructure across Australia to form a national sensor array focusing on the Solid Earth. As such AuScope is working with these programs to deploy observational infrastructure, including MT, passive seismic, and GNSS networks across the entire Australian Continent. Where possible the observational grid will be co-located with strategic basement drilling in areas of shallow cover and tied with national reflection seismic and sampling transects. This integrated suite of distributed earth observation and imaging sensors will provide unprecedented imaging fidelity of our crust, across all length and time scales, to fundamental and applied researchers in the earth, environmental and geospatial sciences. The AEOS will the Earth Science community's Square Kilometer Array (SKA) - a distributed telescope that looks INTO the earth rather than away from it - a 10 million SKA. The AEOS is strongly aligned with other community strategic initiatives including the UNCOVER research program as well as other National Collaborative Research Infrastructure programs such as the Terrestrial Environmental Research Network (TERN) and the Integrated Marine Observing System (IMOS) providing an interdisciplinary collaboration platform across the earth and environmental sciences. There is also very close alignment between AuScope and similar international programs such as EPOS, the USArray and EarthCube - potential collaborative linkages we are currently in the process of pursuing more fomally. The AuScope AEOS Infrastructure System is ultimately designed to enable the progressive construction, refinement and ongoing enrichment of a live, "FAIR" four

EXTREME AO OBSERVATIONS OF TWO TRIPLE ASTEROID SYSTEMS WITH SPHERE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, B.; Wahhaj, Z.; Dumas, C.

We present the discovery of a new satellite of asteroid (130) Elektra—S/2014 (130) 1—in differential imaging and in integral field spectroscopy data over multiple epochs obtained with Spectro-Polarimetric High-contrast Exoplanet Research/Very Large Telescope. This new (second) moonlet of Elektra is about 2 km across, on an eccentric orbit, and about 500 km away from the primary. For a comparative study, we also observed another triple asteroid system, (93) Minerva. For both systems, component-resolved reflectance spectra of the satellites and primary were obtained simultaneously. No significant spectral difference was observed between the satellites and the primary for either triple system. Wemore » find that the moonlets in both systems are more likely to have been created by sub-disruptive impacts as opposed to having been captured.« less

Observational studies of the clearing phase in proto-planetary disk systems

NASA Technical Reports Server (NTRS)

Grady, Carol A.

1994-01-01

A summary of the work completed during the first year of a 5 year program to observationally study the clearing phase of proto-planetary disks is presented. Analysis of archival and current IUE data, together with supporting optical observations has resulted in the identification of 6 new proto-planetary disk systems associated with Herbig Ae/Be stars, the evolutionary precursors of the beta Pictoris system. These systems exhibit large amplitude light and optical color variations which enable us to identify additional systems which are viewed through their circumstellar disks including a number of classical T Tauri stars. On-going IUE observations of Herbig Ae/Be and T Tauri stars with this orientation have enabled us to detect bipolar emission plausibly associated with disk winds. Preliminary circumstellar extinction studies were completed for one star, UX Ori. Intercomparison of the available sample of edge-on systems, with stars ranging from 1-6 solar masses, suggests that the signatures of accreting gas, disk winds, and bipolar flows and the prominence of a dust-scattered light contribution to the integrated light of the system decreases with decreasing IR excess.

Global Earth Observation System of Systems (GEOSS): Initial Actions to Enhance Data Sharing to Meet Societal Needs

NASA Astrophysics Data System (ADS)

Adang, T.

2006-05-01

Over 60 nations and 50 participating organizations are working to make the Global Earth Observation System of Systems (GEOSS) a reality. The U.S. contribution to GEOSS is the Integrated Earth Observation System (IEOS), with a vision of enabling a healthy public, economy and planet through an integrated, comprehensive, and sustained Earth observation system. The international Group on Earth Observations (GEO) and the U.S. Group on Earth Observations have developed strategic plans for both GEOSS and IEOS, respectively, and are now working the first phases of implementation. Many of these initial actions are data architecture related and are being addressed by architecture and data working groups from both organizations - the GEO Architecture and Data Committee and the USGEO Architecture and Data Management Working Group. NOAA has actively participated in both architecture groups and has taken internal action to better support GEOSS and IEOS implementation by establishing the Global Earth Observation Integrated Data Environment (GEO IDE). GEO IDE provides a "system of systems" framework for effective and efficient integration of NOAA's many quasi-independent systems, which individually address diverse mandates in such areas resource management, weather forecasting, safe navigation, disaster response, and coastal mapping among others. GEO IDE will have a services oriented architecture, allowing NOAA Line Offices to retain a high level of independence in many of their data management decisions, and encouraging innovation in pursuit of their missions. Through GEO IDE, NOAA partners (both internal and external) will participate in a well-ordered, standards-based data and information infrastructure that will allow users to easily locate, acquire, integrate and utilize NOAA data and information. This paper describes the initial progress being made by GEO and USGEO architecture and data working groups, a status report on GEO IDE development within NOAA, and an assessment of

Ionospheric Simulation System for Satellite Observations and Global Assimilative Modeling Experiments (ISOGAME)

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Mannucci, Anthony J.; Verkhoglyadova, Olga P.; Stephens, Philip; Wilson, Brian D.; Akopian, Vardan; Komjathy, Attila; Lijima, Byron A.

2013-01-01

ISOGAME is designed and developed to assess quantitatively the impact of new observation systems on the capability of imaging and modeling the ionosphere. With ISOGAME, one can perform observation system simulation experiments (OSSEs). A typical OSSE using ISOGAME would involve: (1) simulating various ionospheric conditions on global scales; (2) simulating ionospheric measurements made from a constellation of low-Earth-orbiters (LEOs), particularly Global Navigation Satellite System (GNSS) radio occultation data, and from ground-based global GNSS networks; (3) conducting ionospheric data assimilation experiments with the Global Assimilative Ionospheric Model (GAIM); and (4) analyzing modeling results with visualization tools. ISOGAME can provide quantitative assessment of the accuracy of assimilative modeling with the interested observation system. Other observation systems besides those based on GNSS are also possible to analyze. The system is composed of a suite of software that combines the GAIM, including a 4D first-principles ionospheric model and data assimilation modules, an Internal Reference Ionosphere (IRI) model that has been developed by international ionospheric research communities, observation simulator, visualization software, and orbit design, simulation, and optimization software. The core GAIM model used in ISOGAME is based on the GAIM++ code (written in C++) that includes a new high-fidelity geomagnetic field representation (multi-dipole). New visualization tools and analysis algorithms for the OSSEs are now part of ISOGAME.