DSN seven day/twelve week schedule program

Deep Space Network scheduling program allocates resources based on the users requirements. The system reviews and allocates the requests for equipment and resources. Depending upon the program input either the seven day or the twelve week schedule is generated

Evaluation of two models using CERES data for reference evapotranspiration estimation

[EN] Evapotranspiration is the most important variable in the Pampas plain. Information provided by sensors onboard satellite missions allows represent the spatial and temporal variability of evapotranspiration, which cannot be achieved using only measurements of weather stations. In this work, the Priestley and Taylor (PT) and FAO Penman Monteith (FAO PM) equations were adapted to estimate the reference evapotranspiration, ET0 , using only CERES satellite products (SYN1 and CldTypHist). In order to evaluate the reference evapotranspiration from CERES, a comparison with in situ measurements was conducted. We used ET data provided by the Oficina de Riesgo Agropecuario, corresponding to 24 stations placed in the Pampean Region of Argentina (2001-2016). Results showed very good agreement between the estimates with CERES products and in situ values, with errors between ±0.8 and ±1.1 mm d–1 and r2 greater than 0.75 at daily scale, and errors between ±14 and ±19 mm month–1 and r2 greater than 0.9, at monthly scale better results were obtained with adapted model FAO PM than PT. Finally, ET0 monthly maps for the Pampean Region of Argentina were elaborated, which allowed knowing the temporal-spatial variation in the validation area. In conclusion, the methods presented here are a suitable alternative to estimate the reference evapotranspiration without requiring ground measurements.[ES] La evapotranspiración es la variable hidrológica de mayor relevancia en la llanura pampeana. La información provista por sensores a bordo de satélites permite representar la variabilidad espacio-temporal de la evapotranspiración, lo cual no es posible lograr utilizando únicamente datos de sitios puntuales de medida. En este trabajo se adaptaron las ecuaciones de Priestley y Taylor (PT) y FAO Penman-Monteith (FAO PM) para obtener la evapotranspiración del cultivo de referencia, ET0 , utilizando únicamente datos de los productos de satélite CERES (SYN1 y CldTypHist). Los resultados obtenidos con los datos CERES se compararon con valores de ET0 provistos por la Oficina de Riesgo Agropecuario de Argentina, a partir de información de 24 estaciones agro-meteorológicas distribuidas en la Región Pampeana de Argentina (2001-2016). Los resultados mostraron muy buena concordancia entre los valores generados con los métodos propuestos y aquellos obtenidos in situ, con errores de entre ±0,8 y ±1,1 mm d–1 y r2 superiores a 0,75 a escala diaria, y errores de entre ±14 y ±19 mm mes–1 y r2 superiores a 0,9, a escala mensual, siendo en general mejores los resultados con el método adaptado de FAO PM respecto al de PT. Finalmente, se elaboraron los mapas promedio mensual de la ET0 para la Región Pampeana de Argentina, los cuales permitieron conocer la variación espacio temporal en el área de validación. En conclusión, los métodos que aquí se presentan constituyen una buena alternativa para el cálculo de la evapotranspiración de referencia, sin necesidad de contar con medidas de terreno.El trabajo se realizó gracias a fondos otorga-dos por la Agencia Nacional de Promoción Científica y Tecnológica de Argentina, PICT 2016-1486- Estudio de la evapotranspiración en la llanura pampeana argentina a partir de datos de satélite (EVAPAMPAS), y el Consejo Nacional de Investigaciones Científicas y Técnicas. Los autores además desean agradecer a la Comisión de Investigaciones Científicas de Buenos Aires, la Universidad Nacional del Centro de la provincia de Buenos Aires, a la Oficina de Riesgo Agropecuario de Argentina, y al Atmospheric Science Data Center de la NASA Langley Research Center por proveer los datos CERES. Además, se agradece a los revisores anónimos que contribuyeron para mejorar el documento.Carmona, F.; Holzman, M.; Rivas, R.; Degano, M.; Kruse, E.; Bayala, M. (2018). Evaluación de dos modelos para la estimación de la evapotranspiración de referencia con datos CERES. Revista de Teledetección. (51):87-98. https://doi.org/10.4995/raet.2018.9259SWORD879851Aliaga, V.S., Ferrelli, F., Piccolo, M.C. 2017. Regionalization of climate over the Argentine Pampas. International Journal of Climatology, 37, 1237-1247. https://doi.org/10.1002/joc.5079Allen R.G., Tasumi M., Trezza R. 2007. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) - model. J. Irrig. Drain. Eng. ASCE, 133, 380-394. https://doi. org/10.1061/(ASCE)0733-9437(2007)133:4(380)Allen, R.G., Pereira, L.S., Raes, D., Smith, M. 1998. FAO Irrigation and Drainage Paper No. 56: Crop Evapotranspiration. (F.W. Resources, Ed.), Irrigation and Drainage. Fao. Retrieved from http://www.kimberly.uidaho.edu/water/fao56/ fao56.pdfAnderson M.C., Norman J.M., Diak G.R., Kustas W.P., Mecikalski J.R. 1997. A twosource time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens Environ, 60, 195-216. https://doi.org/10.1016/S0034-4257(96)00215-5ASCE - EWRI. 2005. The ASCE standardized reference evapotranspiration equation. ASCE-EWRI Standardization of Reference Evapotranspiration Task Comm. Report, January, 2005. http:// www.kimberly.uidaho.edu/water/asceewri/ ascestzdetmain2005.pdf.Bastiaanssen W.G.M., Menenti M., Feddes R.A., Holtslag A.A.M. 1998. A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation. J. Hydrol, 212-213, 198-212. https://doi.org/10.1016/S0022-1694(98)00253-4Carmona, F., Rivas, R., Ocampo, D., Schirmbeck, J., Holzman, M. 2011. Sensores para la medición y validación de variables hidrológicas a escalas local y regional a partir del balance de energía. Aqua-LAC, Revista del programa hidrológico internacional para América Latina y el Caribe, 3, 26-36.Carmona, F., Rivas, R., Caselles, V. 2013. Estimate of the alpha parameter in an oat crop under rain-fed conditions. Hydrological Processes, 27(19), 2834- 2839. https://doi.org/10.1002/hyp.9415Carmona, F., Rivas, R., Kruse, E. 2017. Estimating daily net radiation in the FAO Penman-Monteith method. Theoretical and Applied Climatology, 129(1-2), 89- 95. https://doi.org/10.1007/s00704-016-1761-6Carmona, F., Orte, P.F., Rivas, R., Wolfram, E., Kruse, E. 2017. Development and Analysis of a New Solar Radiation Atlas for Argentina from Ground-Based Measurements and CERES_SYN1deg data. Egyptian Journal of Remote Sensing and Space Science. (In press). https://doi.org/10.1016/j.ejrs.2017.11.003Degano, M.F. 2017. Evaluación del producto de evapotranspiración global MOD16 con medidas in situ en la región de la Pampa Húmeda, Argentina. Tesis de Maestría. Repositorio DigitalCIC. Facultad de Física, Universidad de Valencia. Disponible en https://digital.cic.gba.gob.ar/ handle/11746/7085Degano F., Rivas R., Sánchez Tomás J.M., Carmona F., Niclós R. 2018. Assessment of the Potential Evapotranspiration MODIS Product Using Ground Measurements in the Pampas. Proceedings of the 2018 IEEE ARGENCON conference.Fisher J.B., Tu K.P., Baldocchi D.D. 2008. Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUX- NET sites. Remote Sens. Environ., 112, 901-919. https://doi.org/10.1016/j.rse.2007.06.025Hashimoto, H., Dungan, J.L., White, M.A., Yang, F., Michaelis, A.R., Running, S.W., Nemani, R.R. 2008. Satellite-based estimation of surface vapor pressure deficits using MODIS land surface temperature data. Remote Sensing of Environment, 112(1), 142-155. https://doi.org/10.1016/j.rse.2007.04.016Jensen, M., Burman, R., Allen, R. 1990. Evapotranspiration and irrigation water requirements. Am Soc Civ Eng (ASCE) Manual 70, 332.Jiang L., Islam S. 2001. Estimation of surface evaporation map over southern Great Plains using remote sensing data. Water Resour. Res., 37, 329-340. https://doi.org/10.1029/2000WR900255Jiang, B., Liang, S., Ma, H., Zhang, X., Xiao, Z., Zhao, X., Jia, K., Yao, Y., Jia, A. 2016. GLASS daytime allwave net radiation product: Algorithm development and preliminary validation. Remote Sensing, 8(3), 222. https://doi.org/10.3390/rs8030222Kitoh, A., Kusunoki, S., Nakaegawa, T. 2011. Climate change projections over South America in the late 21st century with the 20 and 60 km mesh Meteorological Research Institute atmospheric general circulation model (MRI-AGCM). Journal of Geophysical Research Atmospheres, 116(6), 1-21. https://doi.org/10.1029/2010JD014920Long D., Longuevergne L., Scanlon B.R. 2014. Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites. Water Resour. Res., 50, 1131-1151. https://doi.org/10.1002/2013WR014581Martínez, G., Gutiérrez, M.A., Messineo, P.G., Kaufmann, C.A., Rafuse, D.J. 2016. Subsistence strategies in Argentina during the late Pleistocene and early Holocene. Quaternary Science Reviews, 144, 51-65. https://doi.org/10.1016/j.quascirev.2016.05.014Miralles D.G., Holmes T.R.H., De Jeu R.A.M., Gash J.H., Meesters A.G.C.A., Dolman A.J. 2011. Global land-surface evaporation estimated from satellitebased observations. Hydrol. Earth Syst Sci., 15, 453-469. https://doi.org/10.5194/hess-15-453-2011Mu Q., Heinsch F.A., Zhao M., Running S.W. 2007. Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. Remote. Sens. Environ., 111, 519-536. https://doi.org/10.1016/j.rse.2007.04.015Mu Q.Z., Zhao M.S., Running S.W. 2011. Improvements to a MODIS global terrestrial evapotranspiration algorithm. Remote Sens Environ, 115, 1781-1800. https://doi.org/10.1016/j.rse.2011.02.019Nishida K., Nemani R.R., Glassy JM, Running S.W. 2003. Development of an evapotranspiration index from aqua/MODIS for monitoring surface moisture status. IEEE Trans Geosci. Remote Sens., 41, 493- 501. https://doi.org/10.1109/TGRS.2003.811744Ocampo, D., Rivas, R. 2013. Estimación de la radiación neta diaria a partir de Modelos de Regresión Lineal Múltiple. Revista Chapingo, Serie Ciencias Forestales y del Ambiente, 19(2), 263-271. https://doi.org/10.5154/r.rchscfa.2012.04.031Penman, H.L. 1948. Natural Evaporation from Open Water, Bare Soil and Grass. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 193(1032), 120-145. https://doi.org/10.1098/rspa.1948.0037Pereyra, F. 2003. Ecorregiones de la Argentina. SEGEMAR. ISSN 0328-2325.Priestley, C.H.B., Taylor, R.J. 1972. On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters. Monthly Weather Review, 100(2), 81-92. https://doi.org/10.1175/1520- 0493(1972)100%3C0081:OTAOSH%3E2.3.CO;2Rivas, R.E., Carmona, F. 2013. Evapotranspiration in the Pampean Region using field measurements and satellite data. Physics and Chemistry of the Earth, Parts A/B/C, 55-57, 27-34. https://doi.org/10.1016/j.pce.2010.12.002Rivas, R., Caselles, V. 2004. A simplified equation to estimate spatial reference evaporation from remote sensing-based surface temperature and local meteorological data. Remote Sensing of Environment, 93, 68-76. https://doi.org/10.1016/j.rse.2004.06.021Sánchez, J.M., Scavone, G., Caselles, V., Valor, E., Copertino, V.A., Telesca, V. 2008. Monitoring daily evapotranspiration at a regional scale from LandsatTM and ETM+ data: Application to the Basilicata region. Journal of Hydrology, 351(1-2), 58-70. https://doi.org/10.1016/j.jhydrol.2007.11.041Scian, B., Labraga, J.C., Reimers, W., Frumento, O. 2006. Characteristics of large-scale atmospheric circulation related to extreme monthly rainfall anomalies in the Pampa region, Argentina, under non-ENSO conditions. Theoretical and Applied Climatology, 85(1-2), 89-106. https://doi.org/10.1007/s00704-005-0182-8Smith, G.L., Priestley, K.J., Loeb, N.G., Wielicki, B.A., Charlock, T.P., Minnis, P., Doelling, D.R., Rutan, D.A. 2011. Clouds and Earth Radiant Energy System (CERES), a review: Past, present and future. Advances in Space Research, 48(2), 254-263. https://doi.org/10.1016/j.asr.2011.03.009Soegaard, H., Boegh, E. 1995. Estimation of evapotranspiration from a millet crop in the Sahel combining sap flow, leaf area index and eddy correlation technique. Journal of Hydrology, 166(3-4), 265-282. https://doi.org/10.1016/0022-1694(94)05094-ETang Q.H., Peterson S., Cuenca R.H., Hagimoto Y., Lettenmaier D.P. 2009. Satellite-based nearreal-time estimation of irrigated crop water consumption. J. Geophys. Res. Atmos., 114, D05114. https://doi.org/10.1029/2008JD010854Wan Z., Zhang K., Xue X.W., Hong Z., Hong Y., Gourley J.J. 2015. Water balance based actual evapotranspi- ration reconstruction from ground and satellite obser- vations over the Conterminous United States. Water Resour. Res., 51, 6485-6499. https://doi.org/10.1002/2015WR017311Wang K.C., Wang P., Li Z.Q., Cribb M., Sparrow M. 2007. A simple method to estimate actual evapotranspiration from a combination of net radiation, vegetation index, and temperature. J. Geophys. Res. Atmos., 112, D15107. https://doi.org/10.1029/2006JD008351Zeng Z.Z., Piao S.L., Lin X., Yin G.D., Peng S.S., Ciais P., Myneni R.B. 2012. Global evapotranspiration over the past three decades: estimation based on the water balance equation combined with empirical models. Environ. Res. Lett., 7, 014026, https://doi.org/10.1088/1748-9326/7/1/014026.Zhang K., Kimball J.S., Mu Q., Jones L.A., Goetz S.J., Running S.W. 2009. Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005. J. Hydrol., 379, 92-110. https://doi.org/10.1016/j.jhydrol.2009.09.047Zhang, K., Kimball, J.S., Running, S.W. 2016. A review of remote sensing based actual evapotranspiration estimation. WIREs Water, 3, 834-853. https://doi.org/10.1002/wat2.116

SMOS soil moisture product validation in croplands

A validation campaign has been carried out to evaluate the Level 2 Soil Moisture (SM) product (version 5.51) given by the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite in the Pampean Region of Argentina. The study region was selected because it is a plain, avoiding topography problems, with an SMOS nominal land use class (low vegetation crops, 1-2m height). Transects of ground SM measurements were collected at 5-cm and 6-cm depth using Delta-T ThetaProbe ML2x and Stevens Hydra Probe II SM sensors, respectively. The volumetric measurements were calibrated using gravimetric and bulk density data collected at the same time as the SM sensor measurements. The SM transects covered ISEA-grid SMOS nodes over four extensive agricultural areas with prevalence of soy crops (site 1: -32.982N, -62.505E; site 2: -32.510N, -62.788E; site 3: -32.024N, -63.692E; and site 4: -37.315N, -58.868E, WGS84). 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). Therefore, additionally to validate the SMOS SM product with the ground data collected during the experimental campaign, the measurements are useful to evaluate the station SM data reliability at the SMOS spatial resolution with the aim of using station data series as reference to test different versions of the SMOS SM product. Previously to the campaign, SMOS SM data variability, ESA Globcover land use classification, soil edaphic properties, water bodies and topography were analyzed around the station locations to select the best sites and the experimental methodology. Temperature vegetation dryness index (TVDI) temporal and spatial variability was also studied at the sites. Additionally, transects of land surface temperature were carried out with Cimel Electronique CE312 6-band radiometers concurrently with thermal-infrared (TIR) satellite overpasses. In previous works, we studied the dependence of land surface emissivities on SM. The analysis of concurrent TIR and SM data make possible to evaluate the utility of the SMOS SM product to improve land surface emissivities and temperature determinations from satellite, giving an added value to the research

System size and centrality dependence of charged hadron transverse momentum spectra in Au+Au and Cu+Cu collisions at sqrt(s) = 62.4 and 200 GeV

We present transverse momentum distributions of charged hadrons produced in Cu+Cu collisions at sqrt(s) = 62.4 and 200 GeV. The spectra are measured for transverse momenta of 0.25 < p_T < 5.0 GeV/c at sqrt(s) = 62.4 GeV and 0.25 < p_T < 7.0 GeV/c at sqrt(s) = 200 GeV, in a pseudo-rapidity range of 0.2 < eta < 1.4. The nuclear modification factor R_AA is calculated relative to p+p data at both collision energies as a function of collision centrality. At a given collision energy and fractional cross-section, R_AA is observed to be systematically larger in Cu+Cu collisions compared to Au+Au. However, for the same number of participating nucleons, R_AA is essentially the same in both systems over the measured range of p_T, in spite of the significantly different geometries of the Cu+Cu and Au+Au systems.Comment: 4 pages, 5 figures, submitted to Phys. Rev. Let

System Size, Energy and Centrality Dependence of Pseudorapidity Distributions of Charged Particles in Relativistic Heavy Ion Collisions

We present the first measurements of the pseudorapidity distribution of primary charged particles in Cu+Cu collisions as a function of collision centrality and energy, \sqrtsnn = 22.4, 62.4 and 200 GeV, over a wide range of pseudorapidity, using the PHOBOS detector. Making a global comparison of Cu+Cu and Au+Au results, we find that the total number of produced charged particles and the rough shape (height and width) of the pseudorapidity distributions are determined by the number of nucleon participants. More detailed studies reveal that a more precise matching of the shape of the Cu+Cu and Au+Au pseudorapidity distributions over the full range of pseudorapidity occurs for the same Npart/2A value rather than the same Npart value. In other words, it is the collision geometry rather than just the number of nucleon participants that drives the detailed shape of the pseudorapidity distribution and its centrality dependence at RHIC energies.Comment: Submitted to Physical Review Letter

LNCS

In resource allocation games, selfish players share resources that are needed in order to fulfill their objectives. The cost of using a resource depends on the load on it. In the traditional setting, the players make their choices concurrently and in one-shot. That is, a strategy for a player is a subset of the resources. We introduce and study dynamic resource allocation games. In this setting, the game proceeds in phases. In each phase each player chooses one resource. A scheduler dictates the order in which the players proceed in a phase, possibly scheduling several players to proceed concurrently. The game ends when each player has collected a set of resources that fulfills his objective. The cost for each player then depends on this set as well as on the load on the resources in it – we consider both congestion and cost-sharing games. We argue that the dynamic setting is the suitable setting for many applications in practice. We study the stability of dynamic resource allocation games, where the appropriate notion of stability is that of subgame perfect equilibrium, study the inefficiency incurred due to selfish behavior, and also study problems that are particular to the dynamic setting, like constraints on the order in which resources can be chosen or the problem of finding a scheduler that achieves stability

Identified charged antiparticle to particle ratios near midrapidity in Cu+Cu collisions at sqrt(s) = 62.4 and 200 GeV

Antiparticle to particle ratios for identified protons, kaons and pions at sqrt(s) = 62.4 and 200 GeV in Cu+Cu collisions are presented as a function of centrality for the midrapidity region of 0.2 < eta < 1.4. No strong dependence on centrality is observed. For the / ratio at ~ 0.51 GeV/c, we observe an average value of 0.50 +/- 0.003_(stat) +/- 0.04_(syst) and 0.77 +/- 0.008_(stat) +/- 0.05_(syst) for the 10% most central collisions of 62.4 and 200 GeV Cu+Cu, respectively. The values for all three particle species measured at sqrt(s) = 200 GeV are in agreement within systematic uncertainties with that seen in both heavier and lighter systems measured at the same RHIC energy. This indicates that system size does not appear to play a strong role in determining the midrapidity chemical freeze-out properties affecting the antiparticle to particle ratios of the three most abundant particle species produced in these collisions.Comment: 5 Pages, 4 figures Made changes to the figures to include the panel numbers. Slight changes to the text. Updated data points from other experiment

Cluster properties from two-particle angular correlations in p+p collisions at s\sqrt{s} = 200 and 410 GeV

We present results on two-particle angular correlations in proton-proton collisions at center of mass energies of 200 and 410 GeV. The PHOBOS experiment at the Relativistic Heavy Ion Collider has a uniquely large coverage for charged particles, giving the opportunity to explore the correlations at both short- and long-range scales. At both energies, a complex two-dimensional correlation structure in $\Delta \eta$ and $\Delta \phi$ is observed. In the context of an independent cluster model of short-range correlations, the cluster size and its decay width are extracted from the two-particle pseudorapidity correlation function and compared with previous measurements in proton-proton and proton-antiproton collisions, as well as PYTHIA and HIJING predictions.Comment: 10 pages, 10 figures, submitted to Phys. Rev.