WorldWideScience

Sample records for surface temperature assimilation

  1. Assimilation of SMOS brightness temperatures or soil moisture retrievals into a land surface model

    Science.gov (United States)

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

    2016-12-01

    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° 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

  2. Assimilation of lake water surface temperature observations using an extended Kalman filter

    Directory of Open Access Journals (Sweden)

    Ekaterina Kourzeneva

    2014-10-01

    Full Text Available A new extended Kalman filter (EKF-based algorithm to assimilate lake water surface temperature (LWST observations into the lake model/parameterisation scheme Freshwater Lake (FLake has been developed. The data assimilation algorithm has been implemented into the stand-alone offline version of FLake. The mixed and non-mixed regimes in lakes are treated separately by the EKF algorithm. The timing of the ice period is indicated implicitly: no ice if water surface temperature is measured. Numerical experiments are performed using operational in-situ observations for 27 lakes and merged observations (in-situ plus satellite for 4 lakes in Finland. Experiments are analysed, potential problems are discussed, and the role of early spring observations is studied. In general, results of experiments are promising: (1 the impact of observations (calculated as the normalised reduction of the LWST root mean square error comparing to the free model run is more than 90% and (2 in cross-validation (when observations are partly assimilated, partly used for validation the normalised reduction of the LWST error standard deviation is more than 65%. The new data assimilation algorithm will allow prognostic variables in the lake parameterisation scheme to be initialised in operational numerical weather prediction models and the effects of model errors to be corrected by using LWST observations.

  3. Diffusion Filters for Variational Data Assimilation of Sea Surface Temperature in an Intermediate Climate Model

    Directory of Open Access Journals (Sweden)

    Xuefeng Zhang

    2015-01-01

    Full Text Available Sequential, adaptive, and gradient diffusion filters are implemented into spatial multiscale three-dimensional variational data assimilation (3DVAR as alternative schemes to model background error covariance matrix for the commonly used correction scale method, recursive filter method, and sequential 3DVAR. The gradient diffusion filter (GDF is verified by a two-dimensional sea surface temperature (SST assimilation experiment. Compared to the existing DF, the new GDF scheme shows a superior performance in the assimilation experiment due to its success in extracting the spatial multiscale information. The GDF can retrieve successfully the longwave information over the whole analysis domain and the shortwave information over data-dense regions. After that, a perfect twin data assimilation experiment framework is designed to study the effect of the GDF on the state estimation based on an intermediate coupled model. In this framework, the assimilation model is subject to “biased” initial fields from the “truth” model. While the GDF reduces the model bias in general, it can enhance the accuracy of the state estimation in the region that the observations are removed, especially in the South Ocean. In addition, the higher forecast skill can be obtained through the better initial state fields produced by the GDF.

  4. Development of a variational data assimilation system for the diurnal cycle of sea surface temperature

    Science.gov (United States)

    While, J.; Martin, M.

    2013-06-01

    A variational data assimilation system based on an incremental 4D-Var approach is proposed for use with a zero-dimensional model of the diurnal cycle of sea surface temperature (SST). Traditional 4D-Var, which seeks to find the initial state of a system, is not appropriate for diurnal SST which is a wind and heat flux driven system that has only a limited memory of its prior state. Instead the proposed assimilation system corrects both the initial SST and the heat and wind fluxes applied throughout the day. The assimilation system is tested using ensembles in a set of idealized twin experiments. In these tests controlling parameters are varied around reasonable "default" values with the quality of the analyses assessed against a known "truth". Within our tests data assimilation is shown to improve diurnal SST under most circumstances. Analyzed heat fluxes are also sometimes improved, although the improvement is much less than that observed for diurnal SST. The system was not found to improve the wind stress. The only circumstances where diurnal SST was not found to be improved by the assimilation were where either observational errors were large (greater than 0.5 K in our tests), or biases in the observations were too big (less than -0.3 K or greater than 0.2 K). The non-Gaussian behavior of the wind stress was found to have an impact on the assimilation in low-wind conditions and under these conditions the best analyses were obtained by artificially inflating the observation error.

  5. Variational assimilation of land surface temperature observations for enhanced river flow predictions

    Science.gov (United States)

    Ercolani, Giulia; Castelli, Fabio

    2016-04-01

    Data assimilation (DA) has the potential of improving hydrologic forecasts. However, many issues arise in case it is employed for spatially distributed hydrologic models that describes processes in various compartments: large dimensionality of the inverse problem, layers governed by different equations, non-linear and discontinuous model structure, complex topology of domains such as surface drainage and river network.On the other hand, integrated models offer the possibility of improving prediction of specific states by exploiting observations of quantities belonging to other compartments. In terms of forecasting river discharges, and hence for their enhancement, soil moisture is a key variable, since it determines the partitioning of rainfall into infiltration and surface runoff. However, soil moisture measurements are affected by issues that could prevent a successful DA and an actual improvement of discharge predictions.In-situ measurements suffer a dramatic spatial scarcity, while observations from satellite are barely accurate and provide spatial information only at a very coarse scale (around 40 km).Hydrologic models that explicitly represent land surface processes of coupled water and energy balance provide a valid alternative to direct DA of soil moisture.They gives the possibility of inferring soil moisture states through DA of remotely sensed Land Surface Temperature (LST), whose measurements are more accurate and with a higher spatial resolution in respect to those of soil moisture. In this work we present the assimilation of LST data in a hydrologic model (Mobidic) that is part of the operational forecasting chain for the Arno river, central Italy, with the aim of improving flood predictions. Mobidic is a raster based, continuous in time and distributed in space hydrologic model, with coupled mass and energy balance at the surface and coupled groundwater and surface hydrology. The variational approach is adopted for DA, since it requires less

  6. Variational assimilation of land surface temperature within the ORCHIDEE Land Surface Model Version 1.2.6

    Science.gov (United States)

    Benavides Pinjosovsky, Hector Simon; Thiria, Sylvie; Ottlé, Catherine; Brajard, Julien; Badran, Fouad; Maugis, Pascal

    2017-01-01

    The SECHIBA module of the ORCHIDEE land surface model describes the exchanges of water and energy between the surface and the atmosphere. In the present paper, the adjoint semi-generator software called YAO was used as a framework to implement a 4D-VAR assimilation scheme of observations in SECHIBA. The objective was to deliver the adjoint model of SECHIBA (SECHIBA-YAO) obtained with YAO to provide an opportunity for scientists and end users to perform their own assimilation. SECHIBA-YAO allows the control of the 11 most influential internal parameters of the soil water content, by observing the land surface temperature or remote sensing data such as the brightness temperature. The paper presents the fundamental principles of the 4D-VAR assimilation, the semi-generator software YAO and a large number of experiments showing the accuracy of the adjoint code in different conditions (sites, PFTs, seasons). In addition, a distributed version is available in the case for which only the land surface temperature is observed.

  7. Numerical solution to the problem of variational assimilation of operational observational data on the ocean surface temperature

    Science.gov (United States)

    Agoshkov, V. I.; Lebedev, S. A.; Parmuzin, E. I.

    2009-02-01

    The problem of variational assimilation of satellite observational data on the ocean surface temperature is formulated and numerically investigated in order to reconstruct surface heat fluxes with the use of the global three-dimensional model of ocean hydrothermodynamics developed at the Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), and observational data close to the data actually observed in specified time intervals. The algorithms of the numerical solution to the problem are elaborated and substantiated, and the data assimilation block is developed and incorporated into the global three-dimensional model. Numerical experiments are carried out with the use of the Indian Ocean water area as an example. The data on the ocean surface temperature over the year 2000 are used as observational data. Numerical experiments confirm the theoretical conclusions obtained and demonstrate the expediency of combining the model with a block of assimilating operational observational data on the surface temperature.

  8. A Study on the Relationships among Surface Variables to Adjust the Height of Surface Temperature for Data Assimilation.

    Science.gov (United States)

    Kang, J. H.; Song, H. J.; Han, H. J.; Ha, J. H.

    2016-12-01

    The observation processing system, KPOP (KIAPS - Korea Institute of Atmospheric Prediction Systems - Package for Observation Processing) have developed to provide optimal observations to the data assimilation system for the KIAPS Integrated Model (KIM). Currently, the KPOP has capable of processing almost all of observations for the KMA (Korea Meteorological Administration) operational global data assimilation system. The height adjustment of SURFACE observations are essential for the quality control due to the difference in height between observation station and model topography. For the SURFACE observation, it is usual to adjust the height using lapse rate or hypsometric equation, which decides values mainly depending on the difference of height. We have a question of whether the height can be properly adjusted following to the linear or exponential relationship solely with regard to the difference of height, with disregard the atmospheric conditions. In this study, firstly we analyse the change of surface variables such as temperature (T2m), pressure (Psfc), humidity (RH2m and Q2m), and wind components (U and V) according to the height difference. Additionally, we look further into the relationships among surface variables . The difference of pressure shows a strong linear relationship with difference of height. But the difference of temperature according to the height shows a significant correlation with difference of relative humidity than with the height difference. A development of reliable model for the height-adjustment of surface temperature is being undertaken based on the preliminary results.

  9. Prediction of Turbulent Heat Fluxes by Assimilation of Remotely Sensed Land Surface Temperature and Soil Moisture Data into an Ensemble-Based Data Assimilation Framework

    Science.gov (United States)

    Xu, T.; Bateni, S. M.; Liu, S.

    2015-12-01

    Accurate estimation of turbulent heat fluxes is important for water resources planning and management, irrigation scheduling, and weather forecast. Land surface models (LSMs) can be used to simulate turbulent heat fluxes over large-scale domains. However, the application of LSMs is hindered due to the high uncertainty in model parameters and state variables. In this study, a dual-pass ensemble-based data assimilation (DA) approach is developed to estimate turbulent heat fluxes. Initially, the common land model (CoLM) is used as the LSM (open-loop), and thereafter the ensemble Kalman filter is employed to optimize the CoLM parameters and variables. The first pass of the DA scheme optimizes vegetation parameters of CoLM (which are related to the leaf stomatal conductance) on a weekly-basis by assimilating the MODIS land surface temperature (LST) data. The second pass optimizes the soil moisture state of CoLM on a daily-basis by assimilating soil moisture observations from Cosmic-ray instrument. The ultimate goal is to improve turbulent heat fluxes estimates from CoLM by optimizing its vegetation parameters and soil moisture state via assimilation of LST and soil moisture data into the proposed DA system. The DA approach is tested over a wet and densely vegetated site, called Daman in northwest of China. Results indicate that the CoLM (open-loop) model typically underestimates latent heat flux and overestimates sensible heat flux. By assimilation of LST in the first pass, the turbulent heat fluxes are improved compared to those of the open-loop. These fluxes become even more accurate by assimilation of soil moisture in the second pass of the DA approach. These findings illustrate that the introduced DA approach can successfully extract information in LST and soil moisture data to optimize the CoLM parameters and states and improve the turbulent heat fluxes estimates.

  10. An Indirect Data Assimilation Scheme for Deep Soil Temperature in the Pleim-Xiu Land Surface Model

    Science.gov (United States)

    The Pleim-Xiu land surface model (PX LSM) has been improved by the addition of a 2nd indirect data assimilation scheme. The first, which was described previously, is a technique where soil moisture in nudged according to the biases in 2-m air temperature and relative humidity be...

  11. A Dynamic Approach to Addressing Observation-Minus-Forecast Mean Differences in a Land Surface Skin Temperature Data Assimilation System

    Science.gov (United States)

    Draper, Clara; Reichle, Rolf; De Lannoy, Gabrielle; Scarino, Benjamin

    2015-01-01

    In land data assimilation, bias in the observation-minus-forecast (O-F) residuals is typically removed from the observations prior to assimilation by rescaling the observations to have the same long-term mean (and higher-order moments) as the corresponding model forecasts. Such observation rescaling approaches require a long record of observed and forecast estimates, and an assumption that the O-F mean differences are stationary. A two-stage observation bias and state estimation filter is presented, as an alternative to observation rescaling that does not require a long data record or assume stationary O-F mean differences. The two-stage filter removes dynamic (nonstationary) estimates of the seasonal scale O-F mean difference from the assimilated observations, allowing the assimilation to correct the model for synoptic-scale errors without adverse effects from observation biases. The two-stage filter is demonstrated by assimilating geostationary skin temperature (Tsk) observations into the Catchment land surface model. Global maps of the O-F mean differences are presented, and the two-stage filter is evaluated for one year over the Americas. The two-stage filter effectively removed the Tsk O-F mean differences, for example the GOES-West O-F mean difference at 21:00 UTC was reduced from 5.1 K for a bias-blind assimilation to 0.3 K. Compared to independent in situ and remotely sensed Tsk observations, the two-stage assimilation reduced the unbiased Root Mean Square Difference (ubRMSD) of the modeled Tsk by 10 of the open-loop values.

  12. Improving the spatial estimation of evapotranspiration by assimilating land surface temperature data

    Science.gov (United States)

    Zink, Matthias; Samaniego, Luis; Cuntz, Matthias

    2013-04-01

    A combined investigation of the water and energy balance in hydrologic models might lead to a more accurate estimation of hydrological fluxes and state variables, such as evapotranspiration ET and soil moisture. Hydrologic models are usually calibrated against discharge measurements, and thus are only trained on the integrated signal at few points within a catchment. This procedure does not take into account any spatial variability of fluxes or state variables. Satellite data are a useful source of information to incorporate spatial information into hydrologic models. The objective of this study is to improve the estimation of evapotranspiration in the spatial domain by using satellite derived land surface temperature Ts for the calibration of the distributed hydrological model mHM. The satellite products are based on data of Meteosat Second Generation (MSG) and are provided by the Land Surface Analysis - Satellite Application Facility (LSA-SAF). mHM simulations of Ts are obtained by solving the energy balance wherein evapotranspiration is determined by closing the water balance. Net radiation is calculated by using incoming short- and longwave radiation, albedo and emissivity data provided by LSA-SAF. The Multiscale Parameter Regionalization technique (MPR, Samaniego et al. 2010) is applied to determine the aerodynamic resistance among other parameters. The optimization is performed for the year 2009 using three objective functions that consider (1) only discharge, (2) only Ts, and (3) both discharge and Ts. For the spatial comparison of satellite derived and estimated Ts fields, a new measure accounting for local spatial variabilities is introduced. The proposed method is applied to seven major German river basins, i.e. Danube, Ems, Main, Mulde, Neckar, Saale, and Weser. The results of the Ts simulations show a bias of 4.1 K compared to the satellite data. We hypothesize that this bias is inherent to the satellite data rather than to the model simulations. This

  13. Assimilation of Sea Surface Temperature in a doubly, two-way nested primitive equation model of the Ligurian Sea

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    Barth, A.; Alvera-Azcarate, A.; Rixen, M.; Beckers, J.-M.; Testut, C.-E.; Brankart, J.-M.; Brasseur, P.

    2003-04-01

    The GHER 3D primitive equation model is implemented with three different resolutions: a low resolution model (1/4^o) covering the whole Mediterranean Sea, an intermediate resolution model (1/20^o) of the Liguro-Provençal basin and a high resolution model (1/60^o) simulating the fine mesoscale structures in the Ligurian Sea. Boundary conditions and the averaged fields (feedback) are exchanged between two successive nesting levels. The model of the Ligurian Sea is also coupled with the assimilation package SESAM. It allows to assimilate satellite data and in situ observations using the local adaptative SEEK (Singular Evolutive Extended Kalman) filter. Instead of evolving the error space by the numerically expensive Lyapunov equation, a simplified algebraic equation depending on the misfit between observation and model forecast is used. Starting from the 1st January 1998 the low and intermediate resolution models are spun up for 18 months. The initial conditions for the Ligurian Sea are interpolated from the intermediate resolution model. The three models are then integrated until August 1999. During this period AVHRR Sea Surface Temperature of the Ligurian Sea is assimilated. The results are validated by using CTD and XBT profiles of the SIRENA cruise from the SACLANT Center. The overall objective of this study is pre-operational. It should help to identify limitations and weaknesses of forecasting methods and to suggest improvements of existing operational models.

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

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    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

  15. Improving Soil Moisture and Temperature Profile and Surface Turbulent Fluxes Estimations in Irrigated Field by Assimilating Multi-source Data into Land Surface Model

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    Chen, Weijing; Huang, Chunlin; Shen, Huanfeng; Wang, Weizhen

    2016-04-01

    The optimal estimation of hydrothermal conditions in irrigation field is restricted by the deficiency of accurate irrigation information (when and how much to irrigate). However, the accurate estimation of soil moisture and temperature profile and surface turbulent fluxes are crucial to agriculture and water management in irrigated field. In the framework of land surface model, soil temperature is a function of soil moisture - subsurface moisture influences the heat conductivity at the interface of layers and the heat storage in different layers. In addition, soil temperature determines the phase of soil water content with the transformation between frozen and unfrozen. Furthermore, surface temperature affects the partitioning of incoming radiant energy into ground (sensible and latent heat flux), as a consequence changes the delivery of soil moisture and temperature. Given the internal positive interaction lying in these variables, we attempt to retrieve the accurate estimation of soil moisture and temperature profile via assimilating the observations from the surface under unknown irrigation. To resolve the input uncertainty of imprecise irrigation quantity, original EnKS is implemented with inflation and localization (referred to as ESIL) aiming at solving the underestimation of the background error matrix and the extension of observation information from the top soil to the bottom. EnKS applied in this study includes the states in different time points which tightly connect with adjacent ones. However, this kind of relationship gradually vanishes along with the increase of time interval. Thus, the localization is also employed to readjust temporal scale impact between states and filter out redundant or invalid correlation. Considering the parameter uncertainty which easily causes the systematic deviation of model states, two parallel filters are designed to recursively estimate both states and parameters. The study area consists of irrigated farmland and is

  16. Characterizing Greenland ice sheet surface mass balance via assimilation of spaceborne surface temperature, albedo, and passive microwave data into a physically-based model

    Science.gov (United States)

    Navari, M.; Bateni, S.; Margulis, S. A.; Alexander, P. M.; Tedesco, M.

    2012-12-01

    The Greenland ice sheet (GrIS) has been the focus of climate studies due to its significant impact on sea level rise and Arctic climate. Accurate estimates of space-time maps of surface mass balance (SMB) components including precipitation, runoff, and evaporation over the GrIS would contribute to understanding the cause of its recent unprecedented changes (e.g., increase in melt amount and duration, thickening of ice sheet interior, and thinning at the margins) and forecasting its changes in the future. In situ measurement of the SMB components across the GrIS is difficult and costly, and thus there are only a limited number of sparse measurements. Remote sensing retrievals are capable of providing some estimates of SMB terms and/or SMB indicators (i.e. melt onset), but generally provide an incomplete picture of the SMB. Additional efforts have focused on the use of regional climate models coupled to surface models in an effort to obtain spatially and temporally continuous estimates of the SMB. However, these estimates are prone to model errors and are generally unconstrained by the remote sensing record. To overcome these uncertainties and consequently improve estimates of the GrIS SMB, an ensemble data assimilation approach is developed for characterizing the SMB and its uncertainty. The EnBS consists of two steps: forecast and update. In the forecast step, an unconditional estimate of SMB using the MAR regional climate model and an ensemble implementation of the CROCUS snow is obtained that includes appropriate uncertainty in key SMB forcings. In the update step, the estimate is conditioned on remotely sensed land surface temperature (LST), albedo, and passive microwave (1.4, 6.9, 18.7, 36.5, and 89 GHz) measurements to provide a posterior estimate of the GrIS SMB components. The end result is an estimate that benefits from the regional atmospheric and snow models, but is also constrained by remote sensing data streams. The assimilation approach is tested for

  17. Assimilation of land surface temperature data from ATSR in an NWP environment - a case study

    NARCIS (Netherlands)

    Hurk, van den B.J.J.M.; Jia, L.; Jacobs, C.; Menenti, M.; Li, Z.L.

    2002-01-01

    Directional thermal observations from the ATSR-2 satellite sensor were used to estimate separate vegetation and soil temperatures for a number of cloud free scenes covering south-east Spain over five days in 1999. Underlying methodology for this is a simplified radiative transfer scheme and a concur

  18. Diffusion Filters for Variational Data Assimilation of Sea Surface Temperature in an Intermediate Climate Model

    Science.gov (United States)

    2015-01-01

    western boundary currents, gyre systems and the Antarctic Circumpolar Current (ACC). For and , reasonable temperature gradients are also... Specially , if , is a constant, which is equivalent to an isotropic filter, we know that = , ∈ [1, − 2] , = , ∈ [1, − 2

  19. Data Assimilation of the High-Resolution Sea Surface Temperature Obtained from the Aqua-Terra Satellites (MODIS-SST Using an Ensemble Kalman Filter

    Directory of Open Access Journals (Sweden)

    Takuji Waseda

    2013-06-01

    Full Text Available We develop an assimilation method of high horizontal resolution sea surface temperature data, provided from the Moderate Resolution Imaging Spectroradiometer (MODIS-SST sensors boarded on the Aqua and Terra satellites operated by National Aeronautics and Space Administration (NASA, focusing on the reproducibility of the Kuroshio front variations south of Japan in February 2010. Major concerns associated with the development are (1 negative temperature bias due to the cloud effects, and (2 the representation of error covariance for detection of highly variable phenomena. We treat them by utilizing an advanced data assimilation method allowing use of spatiotemporally varying error covariance: the Local Ensemble Transformation Kalman Filter (LETKF. It is found that the quality control, by comparing the model forecast variable with the MODIS-SST data, is useful to remove the negative temperature bias and results in the mean negative bias within −0.4 °C. The additional assimilation of MODIS-SST enhances spatial variability of analysis SST over 50 km to 25 km scales. The ensemble spread variance is effectively utilized for excluding the erroneous temperature data from the assimilation process.

  20. Assimilation of high-resolution sea surface temperature data into an operational nowcast/forecast system around Japan using a multi-scale three-dimensional variational scheme

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    Miyazawa, Yasumasa; Varlamov, Sergey M.; Miyama, Toru; Guo, Xinyu; Hihara, Tsutomu; Kiyomatsu, Keiji; Kachi, Misako; Kurihara, Yukio; Murakami, Hiroshi

    2017-06-01

    A multi-scale three-dimensional variational (MS-3DVAR) scheme is developed to assimilate high-resolution Himawari-8 sea surface temperature (SST) data for the first time into an operational ocean nowcast/forecast system targeting the North Western Pacific, JCOPE2. MS-3DVAR improves representation of the Kuroshio path south of Japan, its associated sea level variations, and temperature/salinity profiles south of Japan, the Kuroshio/Oyashio mixed water region, and the Japan Sea as compared to those of the products by the traditional single-scale 3DVAR. Validation results demonstrate that MS-3DVAR well assimilates the sparsely distributed in situ temperature and salinity profiles data by spreading the information over the large scale and by representing the detailed information near the measurement points. MS-3DVAR succeeds to assimilate the Himawari-8 SST product without noisy features caused by the cloud effects. We also find that MS-3DVAR is more effective for estimating oceanic conditions in regions with smaller mesoscale variability including the mixed water region and Japan Sea than in south of Japan.

  1. Monitoring of the ground surface temperature and the active layer in NorthEastern Canadian permafrost areas using remote sensing data assimilated in a climate land surface scheme.

    Science.gov (United States)

    Marchand, N.; Royer, A.; Krinner, G.; Roy, A.

    2014-12-01

    Projected future warming is particularly strong in the Northern high latitudes where increases of temperatures are up to 2 to 6 °C. Permafrost is present on 25 % of the northern hemisphere lands and contain high quantities of « frozen » carbon, estimated at 1400 Gt (40 % of the global terrestrial carbon). The aim of this study is to improve our understanding of the climate evolution in arctic areas, and more specifically of land areas covered by snow. The objective is to describe the ground temperature year round including under snow cover, and to analyse the active layer thickness evolution in relation to the climate variability. We use satellite data (fusion of MODIS land surface temperature « LST » and microwave AMSR-E brightness temperature « Tb ») assimilated in the Canadian Land Surface Scheme (CLASS) of the Canadian climate model coupled with a simple radiative transfer model (HUT). This approach benefits from the advantages of each of the data type in order to complete two objectives : 1- build a solid methodology for retrieving the ground temperature, with and without snow cover, in taïga and tundra areas ; 2 - from those retrieved ground temperatures, derive the summer melt duration and the active layer depth. We describe the coupling of the models and the methodology that adjusts the meteorological input parameters of the CLASS model (mainly air temperature and precipitations derived from the NARR database) in order to minimise the simulated LST and Tb ouputs in comparison with satellite measurements. Using ground-based meteorological data as validation references in NorthEastern Canadian tundra, the results show that the proposed approach improves the soil temperatures estimates when using the MODIS LST and Tb at 10 and 19 GHz to constrain the model in comparison with the model outputs without satellite data. Error analysis is discussed for the summer period (2.5 - 4 K) and for the snow covered winter period (2 - 3.5 K). Further steps are

  2. Assimilating surface observations in a four-dimensional variational Doppler radar data assimilation system to improve the analysis and forecast of a squall line case

    Science.gov (United States)

    Chen, Xingchao; Zhao, Kun; Sun, Juanzhen; Zhou, Bowen; Lee, Wen-Chau

    2016-10-01

    This paper examines how assimilating surface observations can improve the analysis and forecast ability of a fourdimensional Variational Doppler Radar Analysis System (VDRAS). Observed surface temperature and winds are assimilated together with radar radial velocity and reflectivity into a convection-permitting model using the VDRAS four-dimensional variational (4DVAR) data assimilation system. A squall-line case observed during a field campaign is selected to investigate the performance of the technique. A single observation experiment shows that assimilating surface observations can influence the analyzed fields in both the horizontal and vertical directions. The surface-based cold pool, divergence and gust front of the squall line are all strengthened through the assimilation of the single surface observation. Three experiments—assimilating radar data only, assimilating radar data with surface data blended in a mesoscale background, and assimilating both radar and surface observations with a 4DVAR cost function—are conducted to examine the impact of the surface data assimilation. Independent surface and wind profiler observations are used for verification. The result shows that the analysis and forecast are improved when surface observations are assimilated in addition to radar observations. It is also shown that the additional surface data can help improve the analysis and forecast at low levels. Surface and low-level features of the squall line—including the surface warm inflow, cold pool, gust front, and low-level wind—are much closer to the observations after assimilating the surface data in VDRAS.

  3. Improving Forecast Skill by Assimilation of AIRS Temperature Soundings

    Science.gov (United States)

    Susskind, Joel; Reale, Oreste

    2010-01-01

    AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The AIRS Version 5 retrieval algorithm, is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates delta T(p) for retrieved quantities and the use of these error estimates for Quality Control. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 deg. latitude X 0.67 deg longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates delta (p) were used as the uncertainty for each measurement in the data assimilation process. We compared forecasts analyses generated from the analyses done by assimilation of AIRS temperature profiles with three different sets of thresholds; Standard, Medium, and Tight. Assimilation of Quality Controlled AIRS temperature profiles significantly improve 5-7 day forecast skill compared to that obtained without the benefit of AIRS data in all of the cases studied. In addition, assimilation of Quality Controlled AIRS temperature soundings performs better than assimilation of AIRS observed radiances. Based on the experiments shown, Tight Quality Control of AIRS temperature profile performs best

  4. A sea temperature data assimilation system for the China Seas and adjacent areas

    Institute of Scientific and Technical Information of China (English)

    YOU Xiaobao; ZHOU Guangqing; ZHU Jiang; LI Rongfeng

    2003-01-01

    A sea temperature data assimilation system for the China Seas and adjacent areas is developed based on a nested regional ocean circulation model and variational optimal interpolation assimilation method. A 12-year assimilation experiment is performed by using the observational temperature profiles from World Ocean Database 1998 (WOD98) and ECMWF reanalysis surface wind stress. Experimental results indicate that the variational scheme shows good skill in assimilating the observed sea temperature into a regional ocean circulation model. Compared with simulation alone, the sea temperature data assimilation significantly improves the performance of a regional ocean model and obtains comprehensive description of the circulations in the China Seas and adjacent areas. Assimilation results, such as the strength and flowing axis of the Kuroshio, Yellow Sea Cold Water Mass and its corresponding horizontal circulation in summer and dipole eddies in the South China Sea in the late summer/early autumn and the eastward jet between them, are well consistent with the observed evidences.

  5. Coupled atmosphere and land-surface assimilation of surface observations with a single column model and ensemble data assimilation

    Science.gov (United States)

    Rostkier-Edelstein, Dorita; Hacker, Joshua P.; Snyder, Chris

    2014-05-01

    Numerical weather prediction and data assimilation models are composed of coupled atmosphere and land-surface (LS) components. If possible, the assimilation procedure should be coupled so that observed information in one module is used to correct fields in the coupled module. There have been some attempts in this direction using optimal interpolation, nudging and 2/3DVAR data assimilation techniques. Aside from satellite remote sensed observations, reference height in-situ observations of temperature and moisture have been used in these studies. Among other problems, difficulties in coupled atmosphere and LS assimilation arise as a result of the different time scales characteristic of each component and the unsteady correlation between these components under varying flow conditions. Ensemble data-assimilation techniques rely on flow dependent observations-model covariances. Provided that correlations and covariances between land and atmosphere can be adequately simulated and sampled, ensemble data assimilation should enable appropriate assimilation of observations simultaneously into the atmospheric and LS states. Our aim is to explore assimilation of reference height in-situ temperature and moisture observations into the coupled atmosphere-LS modules(simultaneously) in NCAR's WRF-ARW model using the NCAR's DART ensemble data-assimilation system. Observing system simulation experiments (OSSEs) are performed using the single column model (SCM) version of WRF. Numerical experiments during a warm season are centered on an atmospheric and soil column in the South Great Plains. Synthetic observations are derived from "truth" WRF-SCM runs for a given date,initialized and forced using North American Regional Reanalyses (NARR). WRF-SCM atmospheric and LS ensembles are created by mixing the atmospheric and soil NARR profile centered on a given date with that from another day (randomly chosen from the same season) with weights drawn from a logit-normal distribution. Three

  6. Assimilation of neural network soil moisture in land surface models

    Science.gov (United States)

    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

  7. Hydrologic Remote Sensing and Land Surface Data Assimilation.

    Science.gov (United States)

    Moradkhani, Hamid

    2008-05-06

    Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear

  8. Hydrologic Remote Sensing and Land Surface Data Assimilation

    Directory of Open Access Journals (Sweden)

    Hamid Moradkhani

    2008-05-01

    Full Text Available Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface–atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF and Particle filter (PF, for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law and could be a strong alternative to EnKF which is subject to some

  9. The Impact of the Assimilation of Aquarius Sea Surface Salinity Data in the GEOS Ocean Data Assimilation System

    Science.gov (United States)

    Vernieres, Guillaume Rene Jean; Kovach, Robin M.; Keppenne, Christian L.; Akella, Santharam; Brucker, Ludovic; Dinnat, Emmanuel Phillippe

    2014-01-01

    Ocean salinity and temperature differences drive thermohaline circulations. These properties also play a key role in the ocean-atmosphere coupling. With the availability of L-band space-borne observations, it becomes possible to provide global scale sea surface salinity (SSS) distribution. This study analyzes globally the along-track (Level 2) Aquarius SSS retrievals obtained using both passive and active L-band observations. Aquarius alongtrack retrieved SSS are assimilated into the ocean data assimilation component of Version 5 of the Goddard Earth Observing System (GEOS-5) assimilation and forecast model. We present a methodology to correct the large biases and errors apparent in Version 2.0 of the Aquarius SSS retrieval algorithm and map the observed Aquarius SSS retrieval into the ocean models bulk salinity in the topmost layer. The impact of the assimilation of the corrected SSS on the salinity analysis is evaluated by comparisons with insitu salinity observations from Argo. The results show a significant reduction of the global biases and RMS of observations-minus-forecast differences at in-situ locations. The most striking results are found in the tropics and southern latitudes. Our results highlight the complementary role and problems that arise during the assimilation of salinity information from in-situ (Argo) and space-borne surface (SSS) observations

  10. A soil moisture assimilation scheme based on the ensemble Kalman filter using microwave brightness temperature

    Institute of Scientific and Technical Information of China (English)

    JIA BingHao; XIE ZhengHui; TIAN XiangJun; SHI ChunXiang

    2009-01-01

    This study presents a soil moisture assimilation scheme,which could assimilate microwave brightness temperature directly,based on the ensemble Kalman filter and the shuffled complex evolution method (SCE-UA).It uses the soil water model of the land surface model CLM3.0 as the forecast operator,and a radiative transfer model (RTM) as the observation operator in the assimilation system.The assimilation scheme is implemented in two phases:the parameter calibration phase and the pure soil moisture assimilation phase.The vegetation optical thickness and surface roughness parameters in the RTM are calibrated by SCE-UA method and the optimal parameters are used as the final model parameters of the observation operator in the assimilation phase.The ideal experiments with synthetic data indicate that this scheme could significantly improve the simulation of soil moisture at the surface layer.Furthermore,the estimation of soil moisture in the deeper layers could also be improved to a certain extent.The real assimilation experiments with AMSR-E brightness temperature at 10.65 GHz (vertical polarization) show that the root mean square error (RMSE) of soil moisture in the top layer (0-10 cm) by asms.msimilation is 0.03355 m~3·m~(-3),which is reduced by 33.6% compared with that by simulation (0.05052m~3·m~(-3)).The mean RMSE by assimilation for the deeper layers (10-50 cm) is also reduced by 20.9%.All these experiments demonstrate the reasonability of the assimilation scheme developed in this study.

  11. A soil moisture assimilation scheme based on the ensemble Kalman filter using microwave brightness temperature

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    This study presents a soil moisture assimilation scheme, which could assimilate microwave brightness temperature directly, based on the ensemble Kalman filter and the shuffled complex evolution method (SCE-UA). It uses the soil water model of the land surface model CLM3.0 as the forecast operator, and a radiative transfer model (RTM) as the observation operator in the assimilation system. The assimilation scheme is implemented in two phases: the parameter calibration phase and the pure soil moisture assimilation phase. The vegetation optical thickness and surface roughness parameters in the RTM are calibrated by SCE-UA method and the optimal parameters are used as the final model parameters of the observation operator in the assimilation phase. The ideal experiments with synthetic data indicate that this scheme could significantly improve the simulation of soil moisture at the surface layer. Further- more, the estimation of soil moisture in the deeper layers could also be improved to a certain extent. The real assimilation experiments with AMSR-E brightness temperature at 10.65 GHz (vertical polariza- tion) show that the root mean square error (RMSE) of soil moisture in the top layer (0―10 cm) by as- similation is 0.03355 m3·m-3, which is reduced by 33.6% compared with that by simulation (0.05052 m3·m-3). The mean RMSE by assimilation for the deeper layers (10―50 cm) is also reduced by 20.9%. All these experiments demonstrate the reasonability of the assimilation scheme developed in this study.

  12. Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

    Science.gov (United States)

    Farhadi, Leila; Reichle, Rolf H.; DeLannoy, Gabrielle J. M.; Kimball, John S.

    2014-01-01

    The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission.

  13. Soil moisture estimation by assimilating L-band microwave brightness temperature with geostatistics and observation localization.

    Science.gov (United States)

    Han, Xujun; Li, Xin; Rigon, Riccardo; Jin, Rui; Endrizzi, Stefano

    2015-01-01

    The observation could be used to reduce the model uncertainties with data assimilation. If the observation cannot cover the whole model area due to spatial availability or instrument ability, how to do data assimilation at locations not covered by observation? Two commonly used strategies were firstly described: One is covariance localization (CL); the other is observation localization (OL). Compared with CL, OL is easy to parallelize and more efficient for large-scale analysis. This paper evaluated OL in soil moisture profile characterizations, in which the geostatistical semivariogram was used to fit the spatial correlated characteristics of synthetic L-Band microwave brightness temperature measurement. The fitted semivariogram model and the local ensemble transform Kalman filter algorithm are combined together to weight and assimilate the observations within a local region surrounding the grid cell of land surface model to be analyzed. Six scenarios were compared: 1_Obs with one nearest observation assimilated, 5_Obs with no more than five nearest local observations assimilated, and 9_Obs with no more than nine nearest local observations assimilated. The scenarios with no more than 16, 25, and 36 local observations were also compared. From the results we can conclude that more local observations involved in assimilation will improve estimations with an upper bound of 9 observations in this case. This study demonstrates the potentials of geostatistical correlation representation in OL to improve data assimilation of catchment scale soil moisture using synthetic L-band microwave brightness temperature, which cannot cover the study area fully in space due to vegetation effects.

  14. Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

    Science.gov (United States)

    Zaitchik, Benjamin F.; Rodell, Matthew

    2008-01-01

    Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  17. Synthetic tests of passive microwave brightness temperature assimilation over snow covered land using machine learning algorithms

    Science.gov (United States)

    Forman, B. A.

    2015-12-01

    A novel data assimilation framework is evaluated that assimilates passive microwave (PMW) brightness temperature (Tb) observations into an advanced land surface model for the purpose of improving snow depth and snow water equivalent (SWE) estimates across regional- and continental-scales. The multifrequency, multipolarization framework employs machine learning algorithms to predict PMW Tb as a function of land surface model state information and subsequently merges the predicted PMW Tb with observed PMW Tb from the Advanced Microwave Scanning Radiometer (AMSR-E). The merging procedure is predicated on conditional probabilities computed within a Bayesian statistical framework using either an Ensemble Kalman Filter (EnKF) or an Ensemble Kalman Smoother (EnKS). The data assimilation routine produces a conditioned (updated) estimate of modeled SWE that is more accurate and contains less uncertainty than the model without assimilation. A synthetic case study is presented for select locations in North America that compares model results with and without assimilation against synthetic observations of snow depth and SWE. It is shown that the data assimilation framework improves modeled estimates of snow depth and SWE during both the accumulation and ablation phases of the snow season. Further, it is demonstrated that the EnKS outperforms the EnKF implementation due to its ability to better modulate high frequency noise into the conditioned estimates. The overarching findings from this study demonstrate the feasibility of machine learning algorithms for use as an observation model operator within a data assimilation framework in order to improve model estimates of snow depth and SWE across regional- and continental-scales.

  18. Operational assimilation of ASCAT surface soil wetness at the Met Office

    Directory of Open Access Journals (Sweden)

    I. Dharssi

    2011-04-01

    Full Text Available Currently, no extensive global soil moisture observation network exists. Therefore, the Met Office global soil moisture analysis scheme has instead used observations of screen temperature and humidity. A number of new space-borne remote sensing systems, operating at microwave frequencies, have been developed that provide a more direct retrieval of surface soil moisture. These systems are attractive since they provide global data coverage and the horizontal resolution is similar to weather forecasting models. Several studies show that measurements of normalised backscatter (surface soil wetness from the Advanced Scatterometer (ASCAT on the meteorological operational (MetOp satellite contain good quality information about surface soil moisture. This note describes methods to convert ASCAT surface soil wetness measurements to volumetric surface soil moisture together with bias correction and quality control. A computationally efficient nudging scheme is used to assimilate the ASCAT volumetric surface soil moisture data into the Met Office global soil moisture analysis. This ASCAT nudging scheme works alongside a soil moisture nudging scheme that uses observations of screen temperature and humidity. Trials, using the Met Office global Unified Model, of the ASCAT nudging scheme show a positive impact on forecasts of screen temperature and humidity for the tropics, North America and Australia. A comparison with in-situ soil moisture measurements from the US also indicates that assimilation of ASCAT surface soil wetness improves the soil moisture analysis. Assimilation of ASCAT surface soil wetness measurements became operational during July 2010.

  19. Advanced microwave forward model for the land surface data assimilation

    Science.gov (United States)

    Park, Chang-Hwan; Pause, Marion; Gayler, Sebastian; Wollschlaeger, Ute; Jackson, Thomas J.; LeDrew, Ellsworth; Behrendt, Andreas; Wulfmeyer, Volker

    2015-04-01

    , a significant improvement by new approach would be expected in monitoring surface runoff and infiltration, managing and improving irrigation system, and mapping and predicting flood events. Finally, the novel dielectric-mixing model is able to successfully integrate the land surface model and the dielectric constant of microwave. Radiative transfer is calculated for the bare soil and the vegetated components of the grid box using a two-stream radiative transfer model. These model characteristics provide all relevant information needed for a simulation of the microwave emission from the land surface with unprecedented realism. Noah-MP is coupled with the Weather Research and Forecasting (WRF) model system. Also, the novel dielectric-mixing model physically links the Noah-MP land surface properties and the microwave effective dielectric constant. Finally, with the existing radiative transfer model the advanced forward model can assimilate microwave brightness temperature into a consistent land-surface-atmosphere system. A case study will be provided to investigate how well the simulation of the forward model matches to the real world. L-band microwave remote-sensing measurements over the Schäfertal region in Germany have been used for this case study.

  20. The Effect of Errors in Snow Assimilation on Land Surface Modeling

    Science.gov (United States)

    Cosgrove, Brian A.; Houser, Paul R.; Atlas, Robert (Technical Monitor)

    2001-01-01

    The accurate portrayal of the hydrological cycle is extremely important in land surface modeling. Central to this effort is the treatment of snow, as errors in the representation of this quantity can impact practically all other modeled quantities through alterations in the water and energy balances. Although land surface model (LSM) simulations can benefit from the assimilation of snow cover and snow depth observations, they can be negatively impacted if such observations contain errors or if a model bias exists in the simulation of surface or soil temperatures. Both cases may lead to excessive melting or growth of snow packs, and to large alterations in both the energy and water balances. Such problems in the snow assimilation process, made evident by the repeated melting and replenishing of snow pack over significant areas of the United States, exists in the Eta Data Assimilation System and is a product of the EDAS system's direct insertion assimilation of snow data. Occurring on a 24 hour cycle, the repeated melting infuses the soil column with a large quantity of water that upsets the hydrological cycle. In an effort to quantify the impacts of such errors in snow assimilation on water and energy budgets, a series of Mosaic LSM simulations were performed over the 12 month period covering October 1998 to October 1999.

  1. Land-atmosphere interactions in an high resolution atmospheric simulation coupled with a surface data assimilation scheme

    Directory of Open Access Journals (Sweden)

    L. Campo

    2009-09-01

    Full Text Available A valid tool for the retrieving of the turbulent fluxes that characterize the surface energy budget is constituted by the remote sensing of land surface states. In this study sequences of satellite-derived observations (from SEVIRI sensors aboard the Meteosat Second Generation of Land Surface Temperature have been used as input in a data assimilation scheme in order to retrieve parameters that describe energy balance at the ground surface in the Tuscany region, in central Italy, during summer 2005. A parsimonious 1-D multiscale variational assimilation procedure has been followed, that requires also near surface meteorological observations. A simplified model of the surface energy balance that includes such assimilation scheme has been coupled with the limited area atmospheric model RAMS, in order to improve in the latter the accuracy of the energy budget at the surface. The coupling has been realized replacing the assimilation scheme products, in terms of surface turbulent fluxes and temperature and humidity states during the meteorological simulation. Comparisons between meteorological model results with and without coupling with the assimilation scheme are discussed, both in terms of reconstruction of surface variables and of vertical characterization of the lower atmosphere. In particular, the effects of the coupling on the moisture feedback between surface and atmosphere are considered and estimates of the precipitation recycling ratio are provided. The results of the coupling experiment showed improvements in the reconstruction of the surface states by the atmospheric model and considerable influence on the atmospheric dynamics.

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

    Science.gov (United States)

    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

  3. Temperature data assimilation for hyporheic exchange: numerical studies and sandbox experiments

    Science.gov (United States)

    Ju, L.; Zeng, L.; Wu, L.

    2015-12-01

    Due to the temperature difference between groundwater and surface water (GW-SW), heat can be used as an ideal tracer in hyporheic zone. To quantify GW-SW interactions, existing methods are mainly based on the analytical solution of one-dimensional heat transport equation. However, the assumptions therein are usually violated in practical applications. Furthermore, there are relatively limited experimental sandbox studies regarding heat tracer for complicated GW-SW interactions. In this study, we developed a data assimilation method to quantify the GW-SW interaction in the presence of heterogeneous river bed. A numerical simulator was used to solve the groundwater and heat transport equation. Then the ensemble Kalman filter (EnKF) was employed to assimilate the temperature data to quantify the unknown interactions (velocity field) between GW-SW and heterogeneous hydraulic conductivity field. The validity of this method was verified by both numerical simulation and sandbox experiment for different scenarios.

  4. Assimilation of freeze-thaw observations into the NASA Catchment land surface model

    Science.gov (United States)

    Farhadi, L.; Reichle, R. H.; Delannoy, G.

    2012-12-01

    The land surface freeze-thaw (F/T) state controls hydrological and carbon cycling and thus affects water and energy exchanges at land surface. In this research an Observing System Simulation Experiment experiment is conducted using synthetically generated measurements of the F/T state for a region in North America (90-110oW longitude, 45-55oN latitude). The synthetic "truth" is generated using the NASA Catchment land surface model forced with surface meteorological fields from the Modern-Era Retrospective Reanalysis for Research and Applications (MERRA). To generate synthetic measurements, the true categorical F/T state is corrupted with a prescribed amount of F/T classification error. The assimilation experiment employs the same Catchment model except that forcing errors (relative to truth) are introduced via the application of meteorological forcing fields from the Global Land Data Assimilation System (GLDAS). A rule-based approach that incorporates model and observational errors is developed and used for assimilating the categorical F/T measurements into the land surface model (F/T analysis). The effect of the F/T analysis on land surface temperature, soil temperature and soil moisture is examined. In a real-world experiment, the synthetic F/T observations are replaced with F/T observations from the Advanced Microwave Scanning Radiometer Enhanced (AMSR-E). The ultimate goal of this project is to provide a framework for the assimilation of SMAP (Soil Moisture Active Passive) F/T observations into the NASA Catchment land surface model.

  5. Ensemble Kalman filter data assimilation of Thermal Emission Spectrometer temperature retrievals into a Mars GCM

    Science.gov (United States)

    Greybush, Steven J.; Wilson, R. John; Hoffman, Ross N.; Hoffman, Matthew J.; Miyoshi, Takemasa; Ide, Kayo; McConnochie, Timothy; Kalnay, Eugenia

    2012-11-01

    Thermal Emission Spectrometer (TES) retrieved temperature profiles are assimilated into the GFDL Mars Global Climate Model (MGCM) using the Local Ensemble Transform Kalman Filter (LETKF) to produce synoptic maps of temperature, winds, and surface pressure and their uncertainties over the course of a Martian year. Short-term (0.25 sol) forecasts compared to independent observations show reduced root mean square error (to 3-4 K global RMSE for a 30-sol evaluation period during the northern hemisphere autumn) and bias compared to a free running model. Several enhanced techniques result in further performance gains. A 4D-LETKF considers observations at their correct hour of occurrence rather than every 6 h. Spatially varying adaptive inflation and varying the dust distribution among ensemble members refine estimates of analysis uncertainty through the ensemble spread. Enhancing dust and water ice aerosol schemes and the application of empirical bias correction using time mean analysis increments help account for model biases. Full-year experiments using prescribed dust opacities and observed TES dust opacities show that while realistic dust distributions are essential to match observed temperatures with a free run simulation, analyses from data assimilation are more robust with respect to imperfections in aerosol distribution. The data assimilation system described here is being used to generate a new reanalysis of Mars weather and climate, which will have many scientific and engineering applications.

  6. Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

    Directory of Open Access Journals (Sweden)

    Tao Wang

    Full Text Available Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique improve the simulation accuracy of mean seasonal (October throughout May snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the

  7. Impacts of Satellite-Based Snow Albedo Assimilation on Offline and Coupled Land Surface Model Simulations.

    Science.gov (United States)

    Wang, Tao; Peng, Shushi; Krinner, Gerhard; Ryder, James; Li, Yue; Dantec-Nédélec, Sarah; Ottlé, Catherine

    2015-01-01

    Seasonal snow cover in the Northern Hemisphere is the largest component of the terrestrial cryosphere and plays a major role in the climate system through strong positive feedbacks related to albedo. The snow-albedo feedback is invoked as an important cause for the polar amplification of ongoing and projected climate change, and its parameterization across models is an important source of uncertainty in climate simulations. Here, instead of developing a physical snow albedo scheme, we use a direct insertion approach to assimilate satellite-based surface albedo during the snow season (hereafter as snow albedo assimilation) into the land surface model ORCHIDEE (ORganizing Carbon and Hydrology In Dynamic EcosystEms) and assess the influences of such assimilation on offline and coupled simulations. Our results have shown that snow albedo assimilation in both ORCHIDEE and ORCHIDEE-LMDZ (a general circulation model of Laboratoire de Météorologie Dynamique) improve the simulation accuracy of mean seasonal (October throughout May) snow water equivalent over the region north of 40 degrees. The sensitivity of snow water equivalent to snow albedo assimilation is more pronounced in the coupled simulation than the offline simulation since the feedback of albedo on air temperature is allowed in ORCHIDEE-LMDZ. We have also shown that simulations of air temperature at 2 meters in ORCHIDEE-LMDZ due to snow albedo assimilation are significantly improved during the spring in particular over the eastern Siberia region. This is a result of the fact that high amounts of shortwave radiation during the spring can maximize its snow albedo feedback, which is also supported by the finding that the spatial sensitivity of temperature change to albedo change is much larger during the spring than during the autumn and winter. In addition, the radiative forcing at the top of the atmosphere induced by snow albedo assimilation during the spring is estimated to be -2.50 W m-2, the magnitude of

  8. Assimilation of Quality Controlled AIRS Temperature Profiles using the NCEP GFS

    Science.gov (United States)

    Susskind, Joel; Reale, Oreste; Iredell, Lena; Rosenberg, Robert

    2013-01-01

    We have previously conducted a number of data assimilation experiments using AIRS Version-5 quality controlled temperature profiles as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The data assimilation and forecast system we used was the Goddard Earth Observing System Model , Version-5 (GEOS-5) Data Assimilation System (DAS), which represents a combination of the NASA GEOS-5 forecast model with the National Centers for Environmental Prediction (NCEP) operational Grid Point Statistical Interpolation (GSI) global analysis scheme. All analyses and forecasts were run at a 0.5deg x 0.625deg spatial resolution. Data assimilation experiments were conducted in four different seasons, each in a different year. Three different sets of data assimilation experiments were run during each time period: Control; AIRS T(p); and AIRS Radiance. In the "Control" analysis, all the data used operationally by NCEP was assimilated, but no AIRS data was assimilated. Radiances from the Aqua AMSU-A instrument were also assimilated operationally by NCEP and are included in the "Control". The AIRS Radiance assimilation adds AIRS observed radiance observations for a select set of channels to the data set being assimilated, as done operationally by NCEP. In the AIRS T(p) assimilation, all information used in the Control was assimilated as well as Quality Controlled AIRS Version-5 temperature profiles, i.e., AIRS T(p) information was substituted for AIRS radiance information. The AIRS Version-5 temperature profiles were presented to the GSI analysis as rawinsonde profiles, assimilated down to a case-by-case appropriate pressure level p(sub best) determined using the Quality Control procedure. Version-5 also determines case-by-case, level-by-level error estimates of the temperature profiles, which were used as the uncertainty of each temperature measurement. These experiments using GEOS-5 have shown that forecasts

  9. Assimilation and High Resolution Forecasts of Surface and Near Surface Conditions for the 2010 Vancouver Winter Olympic and Paralympic Games

    Science.gov (United States)

    Bernier, Natacha B.; Bélair, Stéphane; Bilodeau, Bernard; Tong, Linying

    2014-01-01

    A dynamical model was experimentally implemented to provide high resolution forecasts at points of interests in the 2010 Vancouver Olympics and Paralympics Region. In a first experiment, GEM-Surf, the near surface and land surface modeling system, is driven by operational atmospheric forecasts and used to refine the surface forecasts according to local surface conditions such as elevation and vegetation type. In this simple form, temperature and snow depth forecasts are improved mainly as a result of the better representation of real elevation. In a second experiment, screen level observations and operational atmospheric forecasts are blended to drive a continuous cycle of near surface and land surface hindcasts. Hindcasts of the previous day conditions are then regarded as today's optimized initial conditions. Hence, in this experiment, given observations are available, observation driven hindcasts continuously ensure that daily forecasts are issued from improved initial conditions. GEM-Surf forecasts obtained from improved short-range hindcasts produced using these better conditions result in improved snow depth forecasts. In a third experiment, assimilation of snow depth data is applied to further optimize GEM-Surf's initial conditions, in addition to the use of blended observations and forecasts for forcing. Results show that snow depth and summer temperature forecasts are further improved by the addition of snow depth data assimilation.

  10. Initial results from Ensemble Data Assimilation of radiances and retrieved temperatures from TES and MCS in an Martian GCM

    Science.gov (United States)

    Lee, C.; Richardson, M. I.

    2010-12-01

    Direct observations of the Martian atmosphere are used to constrain the evolution of a Martian General Circulation Model (MarsWRF) using an ensemble Kalman filter data assimilation framework (DART). We use radiance observations from the Thermal Emission Spectrometer (TES) and temperature profiles from TES and the Mars Climate Sounder (MCS) to constrain the evolution of the simulated Martian atmosphere during similar seasons of each mission. We describe the observations being ingested into the model and the preprocessing necessary to ingest these observations efficiently and accurately into the assimilation system. We test the sensitivity of the assimilation system by including surface visual albedo and infra-red emissivity, and atmospheric total dust loading, in the state vector. We allow DART to modify these unobserved state vector components using only the temperature or radiance observations and information gained from the ensemble of simulated circulations. Finally, we identify and discuss the biases and model limitations revealed by the assimilation, and describe the modifications made to the GCM to improve its ensemble mean skill (accuracy) and ensemble variance to better assimilate the available observations.

  11. MODIS BRIGHTNESS TEMPERATURE DATA ASSIMILATION UNDER CLOUDY CONDITIONS: METHODS AND IDEAL TESTS

    Institute of Scientific and Technical Information of China (English)

    DING Wei-yu; WAN Qi-lin; ZHANG Chen-zhong; CHEN Zi-tong; HUANG Yan-yan

    2010-01-01

    Clouds have important effects on the infrared radiances transmission in that the inclusion of cloud effects in data assimilation can not only improve the quality of the assimilated atmospheric parameters greatly, but also minimize the initial error of cloud parameters by adjusting part of the infrared radiances data. On the basis of the Grapes-3D-var (Global and Regional Assimilation and Prediction Enhanced System), cloud liquid water, cloud ice water and cloud cover are added as the governing variables in the assimilation. Under the conditions of clear sky, partly cloudy cover and totally cloudy cover, the brightness temperature of 16 MODIS channels are assimilated respectively in ideal tests. Results show that when the simulated background brightness temperatures are lower than the observation, the analyzed field will increase the simulated brightness temperature by increasing its temperature and reducing its moisture, cloud liquid water, cloud ice water, and cloud cover. The simulated brightness temperature can be reduced if adjustment is made in the contrary direction. The adjustment of the temperature and specific humidity under the clear sky conditions conforms well to the design of MODIS channels, but it is weakened for levels under cloud layers. The ideal tests demonstrate that by simultaneously adding both cloud parameters and atmospheric parameters as governing variables during the assimilation of infrared radiances, both the cloud parameters and atmospheric parameters can be adjusted using the observed infrared radiances and conventional meteorological elements to make full use of the infrared observations.

  12. Utilization of Hydrologic Remote Sensing Data in Land Surface Modeling and Data Assimilation: Current Status and Challenges

    Science.gov (United States)

    Kumar, Sujay V.; Peters-Lidard, Christa; Reichl, Rolf; Harrison, Kenneth; Santanello, Joseph

    2010-01-01

    Recent advances in remote sensing technologies have enabled the monitoring and measurement of the Earth's land surface at an unprecedented scale and frequency. The myriad of these land surface observations must be integrated with the state-of-the-art land surface model forecasts using data assimilation to generate spatially and temporally coherent estimates of environmental conditions. These analyses are of critical importance to real-world applications such as agricultural production, water resources management and flood, drought, weather and climate prediction. This need motivated the development of NASA Land Information System (LIS), which is an expert system encapsulating a suite of modeling, computational and data assimilation tools required to address challenging hydrological problems. LIS integrates the use of several community land surface models, use of ground and satellite based observations, data assimilation and uncertainty estimation techniques and high performance computing and data management tools to enable the assessment and prediction of hydrologic conditions at various spatial and temporal scales of interest. This presentation will focus on describing the results, challenges and lessons learned from the use of remote sensing data for improving land surface modeling, within LIS. More specifically, studies related to the improved estimation of soil moisture, snow and land surface temperature conditions through data assimilation will be discussed. The presentation will also address the characterization of uncertainty in the modeling process through Bayesian remote sensing and computational methods.

  13. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; Velde, van der R.; Vekerdy, Z.; Su, Z.

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado

  14. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; van der Velde, R.; Vekerdy, Z.; Su, Zhongbo

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park

  15. Assimilation of satellite observed snow albedo in a land surface model

    NARCIS (Netherlands)

    Malik, M.J.; van der Velde, R.; Vekerdy, Z.; Su, Zhongbo

    2012-01-01

    This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado

  16. Evaluation of the Global Land Data Assimilation System (GLDAS) air temperature data products

    Science.gov (United States)

    Ji, Lei; Senay, Gabriel B.; Verdin, James P.

    2015-01-01

    There is a high demand for agrohydrologic models to use gridded near-surface air temperature data as the model input for estimating regional and global water budgets and cycles. The Global Land Data Assimilation System (GLDAS) developed by combining simulation models with observations provides a long-term gridded meteorological dataset at the global scale. However, the GLDAS air temperature products have not been comprehensively evaluated, although the accuracy of the products was assessed in limited areas. In this study, the daily 0.25° resolution GLDAS air temperature data are compared with two reference datasets: 1) 1-km-resolution gridded Daymet data (2002 and 2010) for the conterminous United States and 2) global meteorological observations (2000–11) archived from the Global Historical Climatology Network (GHCN). The comparison of the GLDAS datasets with the GHCN datasets, including 13 511 weather stations, indicates a fairly high accuracy of the GLDAS data for daily temperature. The quality of the GLDAS air temperature data, however, is not always consistent in different regions of the world; for example, some areas in Africa and South America show relatively low accuracy. Spatial and temporal analyses reveal a high agreement between GLDAS and Daymet daily air temperature datasets, although spatial details in high mountainous areas are not sufficiently estimated by the GLDAS data. The evaluation of the GLDAS data demonstrates that the air temperature estimates are generally accurate, but caution should be taken when the data are used in mountainous areas or places with sparse weather stations.

  17. Determining soil moisture by assimilating soil temperature measurements using the Ensemble Kalman Filter

    Science.gov (United States)

    Dong, Jianzhi; Steele-Dunne, Susan C.; Ochsner, Tyson E.; van de Giesen, Nick

    2015-12-01

    This study investigates the potential to estimate the vertical profile of soil moisture by assimilating temperature observations at a limited number of depths into a coupled heat and moisture transport model (Hydrus-1D). The method is developed with a view to assimilating temperature data from distributed temperature sensing (DTS) to estimate soil moisture at high resolution over large areas. The correlation between temperature and soil moisture in the shallow soil (top ∼ 50 cm) ensures that soil moisture can be estimated using just soil temperature observations. Synthetic tests across a range of soil textures show that with data assimilation both modeled temperature and the moisture profile are improved considerably compared to the ensemble open loop model simulations. In addition, employing data assimilation provides a means to quantitatively account for different sources of uncertainty. This is particularly relevant in the context of DTS given the influence of spatial variability in soil texture and its impact on estimation error. The data assimilation approach could also be used to determine, the number of temperature observations required and the depths at which they should be made. Results suggest that temperature observed at two depths is typically sufficient to estimate soil moisture using this approach. The root mean square error (RMSE) in soil moisture was reduced by up to 75% in the top 20 cm. Furthermore, this approach solves many of the challenges identified in the application of an inversion approach to estimate soil moisture from DTS.

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

    Science.gov (United States)

    Zhang, Sibo; Guan, Li

    2017-02-01

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

  19. A land surface soil moisture data assimilation framework in consideration of the model subgrid-scale heterogeneity and soil water thawing and freezing

    Institute of Scientific and Technical Information of China (English)

    TIAN XiangJun; XIE ZhengHui

    2008-01-01

    The Ensemble Kalman Filter (EnKF) is well known and widely used in land data assimilation for its high precision and simple operation. The land surface models used as the forecast operator in a land data assimilation system are usually designed to consider the model subgrid-heterogeneity and soil water thawing and freezing. To neglect their effects could lead to some errors in soil moisture assimilation.The dual EnKF method is employed in soil moisture data assimilation to build a soil moisture data assimilation framework based on the NCAR Community Land Model version 2.0 (CLM 2.0) in consideration of the effects of the model subgrid-heterogeneity and soil water thawing and freezing: Liquid volumetric soil moisture content in a given fraction is assimilated through the state filter process,while solid volumetric soil moisture content in the same fraction and solid/liquid volumetric soil moisture in the other fractions are optimized by the parameter filter. Preliminary experiments show that this dual EnKF-based assimilation framework can assimilate soil moisture more effectively and precisely than the usual EnKF-based assimilation framework without considering the model subgrid-scale heterogeneity and soil water thawing and freezing. With the improvement of soil moisture simulation,the soil temperature-simulated precision can be also improved to some extent.

  20. Assimilation of simulated satellite altimetric data and ARGO temperature data into a double-gyre NEMO ocean model

    Science.gov (United States)

    Yan, Yajing; Barth, Alexander; Laenen, François; Beckers, Jean-Marie

    2013-04-01

    In recent years, data assimilation, adressing the problem of producing useful analyses and forecasts given imperfect dynamical models and observations, has shown increasing interest in the atmosphere and ocean science community. The efficiency of data assimilation in improving the model prediction has been proven by numerous work. However, it is still a challenge to design operational data assimilation schemes which can be operated with realistic ocean models, with reasonable quality and at acceptable cost. In this work, several experiments, assimilating the simulated altimetry and temperature observations into a double-gyre NEMO ocean model, are performed with objective to investigate the impact of different assimilation setups, including changing the observation distribution, the ensemble size and the localisation scale, on the quality of the analysis. The double-gyre NEMO ocean model corresponds to an idealized configuration of the NEMO model: a square and 5000-meter deep flat bottom ocean at mid latitudes (the so called square-box or SQB configuration). The main physical parameters governing the dominant characteristics of the flow are the initial stratification, the wind stress, the bottom friction and the lateral mixing parameterization. The domain extends from 24N to 44N, over 30° in longitude (60W - 30W) with 11 vertical levels between 152 m and 4613 m in depth. The minimum horizontal resolution of the model is 1/4°. The observations are generated from the model simulations (the truth) by adding spatially uncorrelated gaussian noise with given standard deviation. Two types of observation are considered : sea surface height (SSH) and temperature. The observation grid of the SSH is simulated from the ENVISAT and Jason-1 satellite tracks, and that of the temperature is generated in order to mimic the ARGO float profile. The observation localisation is performed in order to avoid spurious correlation at large distance. For this, the observations are weighted

  1. Ensemble Kalman filter assimilation of temperature and altimeter data with bias correction and application to seasonal prediction

    Directory of Open Access Journals (Sweden)

    C. L. Keppenne

    2005-01-01

    Full Text Available To compensate for a poorly known geoid, satellite altimeter data is usually analyzed in terms of anomalies from the time mean record. When such anomalies are assimilated into an ocean model, the bias between the climatologies of the model and data is problematic. An ensemble Kalman filter (EnKF is modified to account for the presence of a forecast-model bias and applied to the assimilation of TOPEX/Poseidon (T/P altimeter data. The online bias correction (OBC algorithm uses the same ensemble of model state vectors to estimate biased-error and unbiased-error covariance matrices. Covariance localization is used but the bias covariances have different localization scales from the unbiased-error covariances, thereby accounting for the fact that the bias in a global ocean model could have much larger spatial scales than the random error.The method is applied to a 27-layer version of the Poseidon global ocean general circulation model with about 30-million state variables. Experiments in which T/P altimeter anomalies are assimilated show that the OBC reduces the RMS observation minus forecast difference for sea-surface height (SSH over a similar EnKF run in which OBC is not used. Independent in situ temperature observations show that the temperature field is also improved. When the T/P data and in situ temperature data are assimilated in the same run and the configuration of the ensemble at the end of the run is used to initialize the ocean component of the GMAO coupled forecast model, seasonal SSH hindcasts made with the coupled model are generally better than those initialized with optimal interpolation of temperature observations without altimeter data. The analysis of the corresponding sea-surface temperature hindcasts is not as conclusive.

  2. Assimilation of ASCAT near-surface soil moisture into the French SIM hydrological model

    Directory of Open Access Journals (Sweden)

    C. Draper

    2011-06-01

    Full Text Available The impact of assimilating near-surface soil moisture into the SAFRAN-ISBA-MODCOU (SIM hydrological model over France is examined. Specifically, the root-zone soil moisture in the ISBA land surface model is constrained over three and a half years, by assimilating the ASCAT-derived surface degree of saturation product, using a Simplified Extended Kalman Filter. In this experiment ISBA is forced with the near-real time SAFRAN analysis, which analyses the variables required to force ISBA from relevant observations available before the real time data cut-off. The assimilation results are tested against ISBA forecasts generated with a higher quality delayed cut-off SAFRAN analysis. Ideally, assimilating the ASCAT data will constrain the ISBA surface state to correct for errors in the near-real time SAFRAN forcing, the most significant of which was a substantial dry bias caused by a dry precipitation bias. The assimilation successfully reduced the mean root-zone soil moisture bias, relative to the delayed cut-off forecasts, by close to 50 % of the open-loop value. The improved soil moisture in the model then led to significant improvements in the forecast hydrological cycle, reducing the drainage, runoff, and evapotranspiration biases (by 17 %, 11 %, and 70 %, respectively. When coupled to the MODCOU hydrogeological model, the ASCAT assimilation also led to improved streamflow forecasts, increasing the mean discharge ratio, relative to the delayed cut off forecasts, from 0.68 to 0.76. These results demonstrate that assimilating near-surface soil moisture observations can effectively constrain the SIM model hydrology, while also confirming the accuracy of the ASCAT surface degree of saturation product. This latter point highlights how assimilation experiments can contribute towards the difficult issue of validating remotely sensed land surface observations over large spatial scales.

  3. Ensemble Optimal Interpolation Data Assimilation of Surface Currents by Utilizing Monte Carlo Simulation

    Science.gov (United States)

    Hartnett, Michael; Ren, Lei

    2013-04-01

    This paper describes the application of Ensemble Optimal Interpolation (EnOI) with Monte Carlo (MC) simulation for surface currents forecasting. Environment Fluid Dynamics Codes (EFDC) is run for 7 days with initial conditions and boundary conditions. For the assimilation process, Direct Insertion (DI), Optimal Interpolation (OI) and Ensemble Optimal Interpolation (EnOI) approaches are applied from t=5.0d, and wind forcing is switched off during updating process. For Optimal Interpolation, background error covariance is estimated from the first run combining empirical correlation function, while for Ensemble Optimal Interpolation, background error covariance is calculated from the ensemble of first run, optimal number of ensemble is acquired by comparing different assimilation. Different strategies have been proposed to obtain the measurement error covariance, optimal measurement error covariance gives the least forecast error. Different kinds of pseudo measurements are produced from Monte Carlo simulation by adding different type of perturbations, which obey certain distribution. A series of experiments with distinct perturbations are carried out to show the improvement of simulating the stochastic process. Three types of reference points: inside of the assimilation area, outside of the assimilation area, and the boundary points are analyzed to show the improvement of the assimilation process and the influence after assimilation. This study also investigates the impacts of the updating interval for the assimilation process, the felicitous updating interval is chosen by comparison. To compare the improvement of operating Ensemble Optimal Interpolation with Direct Insertion and Optimal Interpolation, RMS error and data assimilation skill are calculated.

  4. Estimating soil moisture and soil thermal and hydraulic properties by assimilating soil temperatures using a particle batch smoother

    Science.gov (United States)

    Dong, Jianzhi; Steele-Dunne, Susan C.; Ochsner, Tyson E.; Giesen, Nick van de

    2016-05-01

    This study investigates the potential of estimating the soil moisture profile and the soil thermal and hydraulic properties by assimilating soil temperature at shallow depths using a particle batch smoother (PBS) using synthetic tests. Soil hydraulic properties influence the redistribution of soil moisture within the soil profile. Soil moisture, in turn, influences the soil thermal properties and surface energy balance through evaporation, and hence the soil heat transfer. Synthetic experiments were used to test the hypothesis that assimilating soil temperature observations could lead to improved estimates of soil hydraulic properties. We also compared different data assimilation strategies to investigate the added value of jointly estimating soil thermal and hydraulic properties in soil moisture profile estimation. Results show that both soil thermal and hydraulic properties can be estimated using shallow soil temperatures. Jointly updating soil hydraulic properties and soil states yields robust and accurate soil moisture estimates. Further improvement is observed when soil thermal properties were also estimated together with the soil hydraulic properties and soil states. Finally, we show that the inclusion of a tuning factor to prevent rapid fluctuations of parameter estimation, yields improved soil moisture, temperature, and thermal and hydraulic properties.

  5. Assimilation of ASCAT near-surface soil moisture into the SIM hydrological model over France

    Directory of Open Access Journals (Sweden)

    C. Draper

    2011-12-01

    Full Text Available This study examines whether the assimilation of remotely sensed near-surface soil moisture observations might benefit an operational hydrological model, specifically Météo-France's SAFRAN-ISBA-MODCOU (SIM model. Soil moisture data derived from ASCAT backscatter observations are assimilated into SIM using a Simplified Extended Kalman Filter (SEKF over 3.5 years. The benefit of the assimilation is tested by comparison to a delayed cut-off version of SIM, in which the land surface is forced with more accurate atmospheric analyses, due to the availability of additional atmospheric observations after the near-real time data cut-off. However, comparing the near-real time and delayed cut-off SIM models revealed that the main difference between them is a dry bias in the near-real time precipitation forcing, which resulted in a dry bias in the root-zone soil moisture and associated surface moisture flux forecasts. While assimilating the ASCAT data did reduce the root-zone soil moisture dry bias (by nearly 50%, this was more likely due to a bias within the SEKF, than due to the assimilation having accurately responded to the precipitation errors. Several improvements to the assimilation are identified to address this, and a bias-aware strategy is suggested for explicitly correcting the model bias. However, in this experiment the moisture added by the SEKF was quickly lost from the model surface due to the enhanced surface fluxes (particularly drainage induced by the wetter soil moisture states. Consequently, by the end of each winter, during which frozen conditions prevent the ASCAT data from being assimilated, the model land surface had returned to its original (dry-biased climate. This highlights that it would be more effective to address the precipitation bias directly, than to correct it by constraining the model soil moisture through data assimilation.

  6. A land surface soil moisture data assimilation framework in consideration of the model subgrid-scale heterogeneity and soil water thawing and freezing

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The Ensemble Kalman Filter (EnKF) is well known and widely used in land data assimilation for its high precision and simple operation. The land surface models used as the forecast operator in a land data assimilation system are usually designed to consider the model subgrid-heterogeneity and soil water thawing and freezing. To neglect their effects could lead to some errors in soil moisture assimilation. The dual EnKF method is employed in soil moisture data assimilation to build a soil moisture data as- similation framework based on the NCAR Community Land Model version 2.0 (CLM 2.0) in considera- tion of the effects of the model subgrid-heterogeneity and soil water thawing and freezing: Liquid volumetric soil moisture content in a given fraction is assimilated through the state filter process, while solid volumetric soil moisture content in the same fraction and solid/liquid volumetric soil moisture in the other fractions are optimized by the parameter filter. Preliminary experiments show that this dual EnKF-based assimilation framework can assimilate soil moisture more effectively and precisely than the usual EnKF-based assimilation framework without considering the model subgrid-scale heteroge- neity and soil water thawing and freezing. With the improvement of soil moisture simulation, the soil temperature-simulated precision can be also improved to some extent.

  7. Surface Temperature Data Analysis

    Science.gov (United States)

    Hansen, James; Ruedy, Reto

    2012-01-01

    Small global mean temperature changes may have significant to disastrous consequences for the Earth's climate if they persist for an extended period. Obtaining global means from local weather reports is hampered by the uneven spatial distribution of the reliably reporting weather stations. Methods had to be developed that minimize as far as possible the impact of that situation. This software is a method of combining temperature data of individual stations to obtain a global mean trend, overcoming/estimating the uncertainty introduced by the spatial and temporal gaps in the available data. Useful estimates were obtained by the introduction of a special grid, subdividing the Earth's surface into 8,000 equal-area boxes, using the existing data to create virtual stations at the center of each of these boxes, and combining temperature anomalies (after assessing the radius of high correlation) rather than temperatures.

  8. Results from Assimilating AMSR-E Soil Moisture Estimates into a Land Surface Model Using an Ensemble Kalman Filter in the Land Information System

    Science.gov (United States)

    Blankenship, Clay B.; Crosson, William L.; Case, Jonathan L.; Hale, Robert

    2010-01-01

    Improve simulations of soil moisture/temperature, and consequently boundary layer states and processes, by assimilating AMSR-E soil moisture estimates into a coupled land surface-mesoscale model Provide a new land surface model as an option in the Land Information System (LIS)

  9. Joint assimilation of piezometric heads and groundwater temperatures for improved modelling of river-aquifer interactions

    Science.gov (United States)

    Kurtz, Wolfgang; Hendricks-Franssen, Harrie-Jan; Vereecken, Harry

    2013-04-01

    Measured groundwater temperatures close to streams contain valuable information for the assessment of mass transfer rates between river and aquifer and the hydraulic properties around a streambed. For groundwater management close to rivers, the characterization of these hydraulic properties is of special interest because exchange fluxes between river and aquifer influence the sustainability of groundwater abstraction and the quality of pumped drinking water. Additionally, it can be important for groundwater management to gain reliable predictions of groundwater temperatures, e.g. in order to regulate the temperature of extracted drinking water. Data assimilation techniques, like the ensemble Kalman filter (EnKF), provide a flexible stochastic framework to merge model simulations with different types of measurement data in order to enhance the (real-time) prediction of groundwater states and to improve the estimation of uncertain hydraulic subsurface parameters. EnKF has already been used for managed river-aquifer systems to improve the prediction of groundwater levels and the estimation of hydraulic parameters by the assimilation of measured piezometric head data. As temperature data can provide additional information on stream-aquifer exchange it is investigated whether this information further constrains states, fluxes and parameters of the river-groundwater system. For this purpose, we performed data assimilation experiments with two different model setups: (i) a simple synthetic model of a river-aquifer system where the parameters and simulation conditions were perfectly known (ii) a more complex model of the Limmat aquifer in Zurich where real-world data were assimilated. Results for the synthetic case suggest that a joint assimilation of piezometric heads and groundwater temperatures together with updating of uncertain hydraulic conductivities and leakage coefficients gives the best estimation of states, fluxes and hydraulic properties (i.e., hydraulic

  10. Observation and Numerical Simulations with Radar and Surface Data Assimilation for Heavy Rainfall over Central Korea

    Institute of Scientific and Technical Information of China (English)

    Ji-Hyun HA; Hyung-Woo KIM; Dong-Kyou LEE

    2011-01-01

    This study investigated the impact of multiple-Doppler radar data and surface data assimilation on forecasts of heavy rainfall over the central Korean Peninsula; the Weather Research and Forecasting (WRF)model and its three-dimensional variational data assimilation system (3DVAR) were used for this purpose.During data assimilation, the WRF 3DVAR cycling mode with incremental analysis updates (IAU) was used.A maximum rainfall of 335.0 mm occurred during a 12-h period from 2100 UTC 11 July 2006 to 0900 UTC 12 July 2006. Doppler radar data showed that the heavy rainfall was due to the back-building formation of mesoscale convective systems (MCSs). New convective ceils were continuously formed in the upstream region, which was characterized by a strong southwesterly low-level jet (LLJ). The LLJ also facilitated strong convergence due to horizontal wind shear, which resulted in maintenance of the storms. The assimilation of both multiple-Doppler radar and surface data improved the accuracy of precipitation forecasts and had a more positive impact on quantitative forecasting (QPF) than the assimilation of either radar data or surface data only. The back-building characteristic was successfully forecasted when the multiple-Doppler radar data and surface data were assimilated. In data assimilation experiments, the radar data helped forecast the development of convective storms responsible for heavy rainfall, and the surface data contributed to the occurrence of intensified low-level winds. The surface data played a significant role in enhancing the thermal gradient and modulating the planetary boundary layer of the model, which resulted in favorable conditions for convection.

  11. Observation and Numerical Simulations with Radar and Surface Data Assimilation for Heavy Rainfall over Central Korea

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    This study investigated the impact of multiple-Doppler radar data and surface data assimilation on forecasts of heavy rainfall over the central Korean Peninsula;the Weather Research and Forecasting(WRF) model and its three-dimensional variational data assimilation system(3DVAR) were used for this purpose. During data assimilation,the WRF 3DVAR cycling mode with incremental analysis updates(IAU) was used. A maximum rainfall of 335.0 mm occurred during a 12-h period from 2100 UTC 11 July 2006 to 0900 UTC 12 July 2006.Doppler radar data showed that the heavy rainfall was due to the back-building formation of mesoscale convective systems(MCSs).New convective cells were continuously formed in the upstream region,which was characterized by a strong southwesterly low-level jet(LLJ).The LLJ also facilitated strong convergence due to horizontal wind shear,which resulted in maintenance of the storms.The assimilation of both multiple-Doppler radar and surface data improved the accuracy of precipitation forecasts and had a more positive impact on quantitative forecasting(QPF) than the assimilation of either radar data or surface data only.The back-building characteristic was successfully forecasted when the multiple-Doppler radar data and surface data were assimilated.In data assimilation experiments,the radar data helped forecast the development of convective storms responsible for heavy rainfall,and the surface data contributed to the occurrence of intensified low-level winds.The surface data played a significant role in enhancing the thermal gradient and modulating the planetary boundary layer of the model,which resulted in favorable conditions for convection.

  12. Bias Correction for Assimilation of Retrieved AIRS Profiles of Temperature and Humidity

    Science.gov (United States)

    Blakenship, Clay; Zavodsky, Bradley; Blackwell, William

    2014-01-01

    The Atmospheric Infrared Sounder (AIRS) is a hyperspectral radiometer aboard NASA's Aqua satellite designed to measure atmospheric profiles of temperature and humidity. AIRS retrievals are assimilated into the Weather Research and Forecasting (WRF) model over the North Pacific for some cases involving "atmospheric rivers". These events bring a large flux of water vapor to the west coast of North America and often lead to extreme precipitation in the coastal mountain ranges. An advantage of assimilating retrievals rather than radiances is that information in partly cloudy fields of view can be used. Two different Level 2 AIRS retrieval products are compared: the Version 6 AIRS Science Team standard retrievals and a neural net retrieval from MIT. Before assimilation, a bias correction is applied to adjust each layer of retrieved temperature and humidity so the layer mean values agree with a short-term model climatology. WRF runs assimilating each of the products are compared against each other and against a control run with no assimilation. Forecasts are against ERA reanalyses.

  13. COBE Sea Surface Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The COBE-SST is a gridded 1x1 resolution SST monitoring dataset. It is used as input for the JMA Climate Data Assimilation System (JCDAS) and the Japanese 25-year...

  14. Assimilating synthetic hyperspectral sounder temperature and humidity retrievals to improve severe weather forecasts

    Science.gov (United States)

    Jones, Thomas A.; Koch, Steven; Li, Zhenglong

    2017-04-01

    Assimilation of hyperspectral sounder data into numerical weather prediction (NWP) models has proven vital to generating accurate model analyses of tropospheric temperature and humidity where few conventional observations exist. Applications to storm-scale models are limited since the low temporal resolution provided by polar orbiting sensors cannot adequately sample rapidly changing environments associated with high impact weather events. To address this limitation, hyperspectral sounders have been proposed for geostationary orbiting satellites, but these have yet to be built and launched in part due to much higher engineering costs and a lack of a definite requirement for the data. This study uses an Observation System Simulation Experiment (OSSE) approach to simulate temperature and humidity profiles from a hypothetical geostationary-based sounder from a nature run of a high impact weather event on 20 May 2013. The simulated observations are then assimilated using an ensemble adjustment Kalman filter approach, testing both hourly and 15 minute cycling to determine their relative effectiveness at improving the near storm environment. Results indicate that assimilating both temperature and humidity profiles reduced mid-tropospheric both mean and standard deviation of analysis and forecast errors compared to assimilating conventional observations alone. The 15 minute cycling generally produced the lowest errors while also generating the best 2-4 hour updraft helicity forecasts of ongoing convection. This study indicates the potential for significant improvement in short-term forecasting of severe storms from the assimilation of hyperspectral geostationary satellite data. However, more studies are required using improved OSSE designs encompassing multiple storm environments and additional observation types such as radar reflectivity to fully define the effectiveness of assimilating geostationary hyperspectral observations for high impact weather forecasting

  15. Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

    Science.gov (United States)

    Naha, Shaini; Thakur, Praveen K.; Aggarwal, S. P.

    2016-06-01

    The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity) is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH) have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006). Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I) and Ensemble Kalman Filter (EnKF) that uses observations of snow covered area (SCA) to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU), rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD) data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated using observed

  16. Hydrological Modelling and data assimilation of Satellite Snow Cover Area using a Land Surface Model, VIC

    Directory of Open Access Journals (Sweden)

    S. Naha

    2016-06-01

    Full Text Available The snow cover plays an important role in Himalayan region as it contributes a useful amount to the river discharge. So, besides estimating rainfall runoff, proper assessment of snowmelt runoff for efficient management and water resources planning is also required. A Land Surface Model, VIC (Variable Infiltration Capacity is used at a high resolution grid size of 1 km. Beas river basin up to Thalot in North West Himalayas (NWH have been selected as the study area. At first model setup is done and VIC has been run in its energy balance mode. The fluxes obtained from VIC has been routed to simulate the discharge for the time period of (2003-2006. Data Assimilation is done for the year 2006 and the techniques of Data Assimilation considered in this study are Direct Insertion (D.I and Ensemble Kalman Filter (EnKF that uses observations of snow covered area (SCA to update hydrologic model states. The meteorological forcings were taken from 0.5 deg. resolution VIC global forcing data from 1979-2006 with daily maximum temperature, minimum temperature from Climate Research unit (CRU, rainfall from daily variability of NCEP and wind speed from NCEP-NCAR analysis as main inputs and Indian Meteorological Department (IMD data of 0.25 °. NBSSLUP soil map and land use land cover map of ISRO-GBP project for year 2014 were used for generating the soil parameters and vegetation parameters respectively. The threshold temperature i.e. the minimum rain temperature is -0.5°C and maximum snow temperature is about +0.5°C at which VIC can generate snow fluxes. Hydrological simulations were done using both NCEP and IMD based meteorological Forcing datasets, but very few snow fluxes were obtained using IMD data met forcing, whereas NCEP based met forcing has given significantly better snow fluxes throughout the simulation years as the temperature resolution as given by IMD data is 0.5°C and rainfall resolution of 0.25°C. The simulated discharge has been validated

  17. From skin to bulk: An adjustment technique for assimilation of satellite-derived temperature observations in numerical models of small inland water bodies

    Science.gov (United States)

    Javaheri, Amir; Babbar-Sebens, Meghna; Miller, Robert N.

    2016-06-01

    Data Assimilation (DA) has been proposed for multiple water resources studies that require rapid employment of incoming observations to update and improve accuracy of operational prediction models. The usefulness of DA approaches in assimilating water temperature observations from different types of monitoring technologies (e.g., remote sensing and in-situ sensors) into numerical models of in-land water bodies (e.g., lakes and reservoirs) has, however, received limited attention. In contrast to in-situ temperature sensors, remote sensing technologies (e.g., satellites) provide the benefit of collecting measurements with better X-Y spatial coverage. However, assimilating water temperature measurements from satellites can introduce biases in the updated numerical model of water bodies because the physical region represented by these measurements do not directly correspond with the numerical model's representation of the water column. This study proposes a novel approach to address this representation challenge by coupling a skin temperature adjustment technique based on available air and in-situ water temperature observations, with an ensemble Kalman filter based data assimilation technique. Additionally, the proposed approach used in this study for four-dimensional analysis of a reservoir provides reasonably accurate surface layer and water column temperature forecasts, in spite of the use of a fairly small ensemble. Application of the methodology on a test site - Eagle Creek Reservoir - in Central Indiana demonstrated that assimilation of remotely sensed skin temperature data using the proposed approach improved the overall root mean square difference between modeled surface layer temperatures and the adjusted remotely sensed skin temperature observations from 5.6°C to 0.51°C (i.e., 91% improvement). In addition, the overall error in the water column temperature predictions when compared with in-situ observations also decreased from 1.95°C (before assimilation

  18. Influence of Assimilation of Subsurface Temperature Measurements on Simulations of Equatorial Undercurrent and South Equatorial Current Along the Pacific Equator

    Science.gov (United States)

    Halpern, David; Leetmaan, Ants; Reynolds, Richard W.; Ji, Ming

    1997-01-01

    Equatorial Pacific current and temperature fields were simulated with and without assimilation of subsurface temperature measurements for April 1992 - March 1995, and compared with moored bouy and research vessel current measurements.

  19. GODAE, SFCOBS - Surface Temperature Observations

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GODAE, SFCOBS - Surface Temperature Observations: Ship, fixed/drifting buoy, and CMAN in-situ surface temperature. Global Telecommunication System (GTS) Data. The...

  20. Improving forecast skill by assimilation of quality-controlled AIRS temperature retrievals under partially cloudy conditions

    Science.gov (United States)

    Reale, O.; Susskind, J.; Rosenberg, R.; Brin, E.; Liu, E.; Riishojgaard, L. P.; Terry, J.; Jusem, J. C.

    2008-04-01

    The National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite is now recognized as an important contributor towards the improvement of weather forecasts. At this time only a small fraction of the total data produced by AIRS is being used by operational weather systems. In fact, in addition to effects of thinning and quality control, the only AIRS data assimilated are radiance observations of channels unaffected by clouds. Observations in mid-lower tropospheric sounding AIRS channels are assimilated primarily under completely clear-sky conditions, thus imposing a very severe limitation on the horizontal distribution of the AIRS-derived information. In this work it is shown that the ability to derive accurate temperature profiles from AIRS observations in partially cloud-contaminated areas can be utilized to further improve the impact of AIRS observations in a global model and forecasting system. The analyses produced by assimilating AIRS temperature profiles obtained under partial cloud cover result in a substantially colder representation of the northern hemisphere lower midtroposphere at higher latitudes. This temperature difference has a strong impact, through hydrostatic adjustment, in the midtropospheric geopotential heights, which causes a different representation of the polar vortex especially over northeastern Siberia and Alaska. The AIRS-induced anomaly propagates through the model's dynamics producing improved 5-day forecasts.

  1. Improving Forecast Skill by Assimilation of Quality-controlled AIRS Temperature Retrievals under Partially Cloudy Conditions

    Science.gov (United States)

    Reale, O.; Susskind, J.; Rosenberg, R.; Brin, E.; Riishojgaard, L.; Liu, E.; Terry, J.; Jusem, J. C.

    2007-01-01

    The National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite has been long recognized as an important contributor towards the improvement of weather forecasts. At this time only a small fraction of the total data produced by AIRS is being used by operational weather systems. In fact, in addition to effects of thinning and quality control, the only AIRS data assimilated are radiance observations of channels unaffected by clouds. Observations in mid-lower tropospheric sounding AIRS channels are assimilated primarily under completely clear-sky conditions, thus imposing a very severe limitation on the horizontal distribution of the AIRS-derived information. In this work it is shown that the ability to derive accurate temperature profiles from AIRS observations in partially cloud-contaminated areas can be utilized to further improve the impact of AIRS observations in a global model and forecasting system. The analyses produced by assimilating AIRS temperature profiles obtained under partial cloud cover result in a substantially colder representation of the northern hemisphere lower midtroposphere at higher latitudes. This temperature difference has a strong impact, through hydrostatic adjustment, in the midtropospheric geopotential heights, which causes a different representation of the polar vortex especially over northeastern Siberia and Alaska. The AIRS-induced anomaly propagates through the model's dynamics producing improved 5-day forecasts.

  2. GISS Surface Temperature Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The GISTEMP dataset is a global 2x2 gridded temperature anomaly dataset. Temperature data is updated around the middle of every month using current data files from...

  3. On the effectiveness of surface assimilation in probabilistic nowcasts of planetary boundary layer profiles

    Science.gov (United States)

    Rostkier-Edelstein, Dorita; Hacker, Joshua

    2013-04-01

    Surface observations comprise a wide, non-expensive and reliable source of information about the state of the near-surface planetary boundary layer (PBL). Operational data assimilation systems have encountered several difficulties in effectively assimilating them, among others due to their local-scale representativeness, the transient coupling between the surface and the atmosphere aloft and the balance constraints usually used. A long-term goal of this work is to find an efficient system for probabilistic PBL nowcasting that can be employed wherever surface observations are present. Earlier work showed that surface observations can be an important source of information with a single column model (SCM) and an ensemble filter (EF). Here we extend that work to quantify the probabilistic skill of ensemble SCM predictions with a model including added complexity. We adopt a factor separation analysis to quantify the contribution of surface assimilation relative to that of selected model components (parameterized radiation and externally imposed horizontal advection) to the probabilistic skill of the system, and of any beneficial or detrimental interactions between them. To assess the real utility of the flow-dependent covariances estimated with the EF and of the SCM of the PBL we compare the skill of the SCM/EF system to that of a reference one based on climatological covariances and a 30-min persistence model. It consists of a dressing technique, whereby a deterministic 3D mesoscale forecast (e.g. from WRF model) is adjusted and dressed with uncertainty using a seasonal sample of mesoscale forecasts and surface forecast errors. Results show that assimilation of surface observations can improve deterministic and probabilistic profile predictions more significantly than major model improvements. Flow-dependent covariances estimated with the SCM/EF show clear advantage over the use of climatological covariances when the flow is characterized by wide variability, when

  4. Assimilation of stratospheric and mesospheric temperatures from MLS and SABER into a global NWP model

    Directory of Open Access Journals (Sweden)

    K. W. Hoppel

    2008-05-01

    Full Text Available The forecast model and three-dimensional variational data assimilation components of the Navy Operational Global Atmospheric Prediction System (NOGAPS have each been extended into the upper stratosphere and mesosphere to form an Advanced Level Physics High Altitude (ALPHA version of NOGAPS extending to ~100 km. This NOGAPS-ALPHA NWP prototype is used to assimilate stratospheric and mesospheric temperature data from the Microwave Limb Sounder (MLS and the Sounding of the Atmosphere using Broadband Radiometry (SABER instruments. A 60-day analysis period in January and February, 2006, was chosen that includes a well documented stratospheric sudden warming. SABER temperatures indicate that the SSW caused the polar winter stratopause at ~40 km to disappear, then reform at ~80 km altitude and slowly descend during February. The NOGAPS-ALPHA analysis reproduces this observed stratospheric and mesospheric temperature structure, as well as realistic evolution of zonal winds, residual velocities, and Eliassen-Palm fluxes that aid interpretation of the vertically deep circulation and eddy flux anomalies that developed in response to this wave-breaking event. The observation minus forecast (O-F standard deviations for MLS and SABER are ~2 K in the mid-stratosphere and increase monotonically to about 6 K in the upper mesosphere. Increasing O-F standard deviations in the mesosphere are expected due to increasing instrument error and increasing geophysical variance at small spatial scales in the forecast model. In the mid/high latitude winter regions, 10-day forecast skill is improved throughout the upper stratosphere and mesosphere when the model is initialized using the high-altitude analysis based on assimilation of both SABER and MLS data.

  5. Can We Estimate Surface Carbon Fluxes With a 6-hour Data Assimilation System?

    Science.gov (United States)

    Kalnay, E.; Kang, J.; Liu, J.; Fung, I.

    2011-12-01

    The estimation of surface carbon fluxes from atmospheric measurements of CO2 is an ill-posed problem (Enting, 2002). In the real atmosphere emissions are transported and mixed, losing information; measuring atmospheric concentrations introduces further errors; and the calculation of transports with imperfect models amplifies the errors in estimating surface sources and sinks. Because of this ill-posedness, prior information on carbon surface fluxes is essential for inverse estimations (e.g., Gurney et al., 2004, Baker et al., 2006, Roedenbeck et al., 2003). Peters et al. (2007) have used instead an Ensemble Kalman Filter (EnKF) data assimilation approach where the winds are given (e.g., from ECMWF). They use a Kalman smoother with a 5-week smoother, producing the operational "Carbon Tracker" estimation of surface fluxes at NOAA. We address the ill-posedness by assimilating simultaneously every 6 hours both carbon concentrations and meteorological variables, since within this time scale changes in atmospheric CO2 concentrations should be dominated by surface fluxes rather than transport and mixing. A simulation system using the Local Ensemble Transform Kalman Filter (LETKF) to assimilate CO2 from a realistic observing system including GOSAT, AIRS and surface observations, and is able to estimate in detail the seasonal evolution of "true" surface fluxes (including fossil fuel emissions) even in the absence of prior information. These promising results (albeit simulated) suggest that with more advanced models and accurate column observations such as those expected from OCO-2 it may be possible to estimate surface carbon fluxes if the LETKF is optimized (Kang et al., 2011).

  6. Temperature dependence of surface nanobubbles

    NARCIS (Netherlands)

    Berkelaar, R.P.; Seddon, James Richard Thorley; Zandvliet, Henricus J.W.; Lohse, Detlef

    2012-01-01

    The temperature dependence of nanobubbles was investigated experimentally using atomic force microscopy. By scanning the same area of the surface at temperatures from 51 °C to 25 °C it was possible to track geometrical changes of individual nanobubbles as the temperature was decreased.

  7. On the Charney Conjecture of Data Assimilation Employing Temperature Measurements Alone: The Paradigm of 3D Planetary Geostrophic Model

    CERN Document Server

    Farhat, Aseel; Titi, Edriss S

    2016-01-01

    Analyzing the validity and success of a data assimilation algorithm when some state variable observations are not available is an important problem in meteorology and engineering. We present an improved data assimilation algorithm for recovering the exact full reference solution (i.e. the velocity and temperature) of the 3D Planetary Geostrophic model, at an exponential rate in time, by employing coarse spatial mesh observations of the temperature alone. This provides, in the case of this paradigm, a rigorous justification to an earlier conjecture of Charney which states that temperature history of the atmosphere, for certain simple atmospheric models, determines all other state variables.

  8. Assessing satellite sea surface salinity from ocean color radiometric measurements for coastal hydrodynamic model data assimilation

    Science.gov (United States)

    Vogel, Ronald L.; Brown, Christopher W.

    2016-07-01

    Improving forecasts of salinity from coastal hydrodynamic models would further our predictive capacity of physical, chemical, and biological processes in the coastal ocean. However, salinity is difficult to estimate in coastal and estuarine waters at the temporal and spatial resolution required. Retrieving sea surface salinity (SSS) using satellite ocean color radiometry may provide estimates with reasonable accuracy and resolution for coastal waters that could be assimilated into hydrodynamic models to improve SSS forecasts. We evaluated the applicability of satellite SSS retrievals from two algorithms for potential assimilation into National Oceanic and Atmospheric Administration's Chesapeake Bay Operational Forecast System (CBOFS) hydrodynamic model. Of the two satellite algorithms, a generalized additive model (GAM) outperformed that of an artificial neural network (ANN), with mean bias and root-mean-square error (RMSE) of 1.27 and 3.71 for the GAM and 3.44 and 5.01 for the ANN. However, the RMSE for the SSS predicted by CBOFS (2.47) was lower than that of both satellite algorithms. Given the better precision of the CBOFS model, assimilation of satellite ocean color SSS retrievals will not improve CBOFS forecasts of SSS in Chesapeake Bay. The bias in the GAM SSS retrievals suggests that adding a variable related to precipitation may improve its performance.

  9. Assimilation of temperature and hydraulic gradients for quantifying the spatial variability of streambed hydraulics

    Science.gov (United States)

    Huang, Xiang; Andrews, Charles B.; Liu, Jie; Yao, Yingying; Liu, Chuankun; Tyler, Scott W.; Selker, John S.; Zheng, Chunmiao

    2016-08-01

    Understanding the spatial and temporal characteristics of water flux into or out of shallow aquifers is imperative for water resources management and eco-environmental conservation. In this study, the spatial variability in the vertical specific fluxes and hydraulic conductivities in a streambed were evaluated by integrating distributed temperature sensing (DTS) data and vertical hydraulic gradients into an ensemble Kalman filter (EnKF) and smoother (EnKS) and an empirical thermal-mixing model. The formulation of the EnKF/EnKS assimilation scheme is based on a discretized 1D advection-conduction equation of heat transfer in the streambed. We first systematically tested a synthetic case and performed quantitative and statistical analyses to evaluate the performance of the assimilation schemes. Then a real-world case was evaluated to calculate assimilated specific flux. An initial estimate of the spatial distributions of the vertical hydraulic gradients was obtained from an empirical thermal-mixing model under steady-state conditions using a constant vertical hydraulic conductivity. Then, this initial estimate was updated by repeatedly dividing the assimilated specific flux by estimates of the vertical hydraulic gradients to obtain a refined spatial distribution of vertical hydraulic gradients and vertical hydraulic conductivities. Our results indicate that optimal parameters can be derived with fewer iterations but greater simulation effort using the EnKS compared with the EnKF. For the field application in a stream segment of the Heihe River Basin in northwest China, the average vertical hydraulic conductivities in the streambed varied over three orders of magnitude (5 × 10-1 to 5 × 102 m/d). The specific fluxes ranged from near zero (qz < ±0.05 m/d) to ±1.0 m/d, while the vertical hydraulic gradients were within the range of -0.2 to 0.15 m/m. The highest and most variable fluxes occurred adjacent to a debris-dam and bridge pier. This phenomenon is very likely

  10. The study of single station inverting the sea surface current by HF ground wave radar based on adjoint assimilation technology

    Science.gov (United States)

    Han, Shuzong; Yang, Hua; Xue, Wenhu; Wang, Xingchi

    2017-06-01

    This paper introduces the assimilation technology in an ocean dynamics model and discusses the feasibility of inverting the sea surface current in the detection zone by assimilating the sea current radial velocity detected by single station HF ground wave radar in ocean dynamics model. Based on the adjoint assimilation and POM model, the paper successfully inverts the sea surface current through single station HF ground wave radar in the Zhoushan sea area. The single station HF radar inversion results are also compared with the bistatic HF radar composite results and the fixed point measured results by Annderaa current meter. The error analysis shows that acquisition of flow velocity and flow direction data from the single station HF radar based on adjoint assimilation and POM model is viable and the data obtained have a high correlation and consistency with the flow field observed by HF radar.

  11. Temperature and Carbon Assimilation Regulate the Chlorosome Biogenesis in Green Sulfur Bacteria

    CERN Document Server

    Tang, Joseph Kuo-Hsiang; Pingali, Sai Venkatesh; Enriquez, Miriam M; Huh, Joonsuk; Frank, Harry A; Urban, Volker S; Aspuru-Guzik, Alan

    2013-01-01

    Green photosynthetic bacteria adjust the structure and functionality of the chlorosome - the light absorbing antenna complex - in response to environmental stress factors. The chlorosome is a natural self-assembled aggregate of bacteriochlorophyll (BChl) molecules. In this study we report the regulation of the biogenesis of the Chlorobaculum tepidum chlorosome by carbon assimilation in conjunction with temperature changes. Our studies indicate that the carbon source and thermal stress culture of Cba. tepidum grows slower and incorporates less BChl c in the chlorosome. Compared with the chlorosome from other cultural conditions we investigated, the chlorosome from the carbon source and thermal stress culture displays: (a) smaller cross-sectional radius and overall size; (b) simplified BChl c homologues with smaller side chains; (c) blue-shifted Qy absorption maxima and (d) a sigmoid-shaped circular dichroism (CD) spectra. Using a theoretical model we analyze how the observed spectral modifications can be assoc...

  12. Diverging temperature responses of CO2 assimilation and plant development explain the overall effect of temperature on biomass accumulation in wheat leaves and grains.

    Science.gov (United States)

    Collins, Nicholas C; Parent, Boris

    2017-01-09

    There is a growing consensus in the literature that rising temperatures influence the rate of biomass accumulation by shortening the development of plant organs and the whole plant and by altering rates of respiration and photosynthesis. A model describing the net effects of these processes on biomass would be useful, but would need to reconcile reported differences in the effects of night and day temperature on plant productivity. In this study, the working hypothesis was that the temperature responses of CO2 assimilation and plant development rates were divergent, and that their net effects could explain observed differences in biomass accumulation. In wheat (Triticum aestivum) plants, we followed the temperature responses of photosynthesis, respiration and leaf elongation, and confirmed that their responses diverged. We measured the amount of carbon assimilated per "unit of plant development" in each scenario and compared it to the biomass that accumulated in growing leaves and grains. Our results suggested that, up to a temperature optimum, the rate of any developmental process increased with temperature more rapidly than that of CO2 assimilation and that this discrepancy, summarised by the CO2 assimilation rate per unit of plant development, could explain the observed reductions in biomass accumulation in plant organs under high temperatures. The model described the effects of night and day temperature equally well, and offers a simple framework for describing the effects of temperature on plant growth.

  13. Orexinergic neurotransmission in temperature responses to methamphetamine and stress: mathematical modeling as a data assimilation approach.

    Directory of Open Access Journals (Sweden)

    Abolhassan Behrouzvaziri

    Full Text Available Orexinergic neurotransmission is involved in mediating temperature responses to methamphetamine (Meth. In experiments in rats, SB-334867 (SB, an antagonist of orexin receptors (OX1R, at a dose of 10 mg/kg decreases late temperature responses (t > 60 min to an intermediate dose of Meth (5 mg/kg. A higher dose of SB (30 mg/kg attenuates temperature responses to low dose (1 mg/kg of Meth and to stress. In contrast, it significantly exaggerates early responses (t < 60 min to intermediate and high doses (5 and 10 mg/kg of Meth. As pretreatment with SB also inhibits temperature response to the stress of injection, traditional statistical analysis of temperature responses is difficult.We have developed a mathematical model that explains the complexity of temperature responses to Meth as the interplay between excitatory and inhibitory nodes. We have extended the developed model to include the stress of manipulations and the effects of SB. Stress is synergistic with Meth on the action on excitatory node. Orexin receptors mediate an activation of on both excitatory and inhibitory nodes by low doses of Meth, but not on the node activated by high doses (HD. Exaggeration of early responses to high doses of Meth involves disinhibition: low dose of SB decreases tonic inhibition of HD and lowers the activation threshold, while the higher dose suppresses the inhibitory component. Using a modeling approach to data assimilation appears efficient in separating individual components of complex response with statistical analysis unachievable by traditional data processing methods.

  14. Orexinergic Neurotransmission in Temperature Responses to Methamphetamine and Stress: Mathematical Modeling as a Data Assimilation Approach

    Science.gov (United States)

    Behrouzvaziri, Abolhassan; Fu, Daniel; Tan, Patrick; Yoo, Yeonjoo; Zaretskaia, Maria V.; Rusyniak, Daniel E.; Molkov, Yaroslav I.; Zaretsky, Dmitry V.

    2015-01-01

    Experimental Data Orexinergic neurotransmission is involved in mediating temperature responses to methamphetamine (Meth). In experiments in rats, SB-334867 (SB), an antagonist of orexin receptors (OX1R), at a dose of 10 mg/kg decreases late temperature responses (t>60 min) to an intermediate dose of Meth (5 mg/kg). A higher dose of SB (30 mg/kg) attenuates temperature responses to low dose (1 mg/kg) of Meth and to stress. In contrast, it significantly exaggerates early responses (t<60 min) to intermediate and high doses (5 and 10 mg/kg) of Meth. As pretreatment with SB also inhibits temperature response to the stress of injection, traditional statistical analysis of temperature responses is difficult. Mathematical Modeling We have developed a mathematical model that explains the complexity of temperature responses to Meth as the interplay between excitatory and inhibitory nodes. We have extended the developed model to include the stress of manipulations and the effects of SB. Stress is synergistic with Meth on the action on excitatory node. Orexin receptors mediate an activation of on both excitatory and inhibitory nodes by low doses of Meth, but not on the node activated by high doses (HD). Exaggeration of early responses to high doses of Meth involves disinhibition: low dose of SB decreases tonic inhibition of HD and lowers the activation threshold, while the higher dose suppresses the inhibitory component. Using a modeling approach to data assimilation appears efficient in separating individual components of complex response with statistical analysis unachievable by traditional data processing methods. PMID:25993564

  15. The surface temperature of Europa

    CERN Document Server

    Ashkenazy, Yosef

    2016-01-01

    Previous estimates of the surface temperature of Jupiter's moon, Europa, neglected the effect of the eccentricity of Jupiter's orbit around the Sun, the effect of the eclipse of Europa (i.e., the relative time that Europa is within the shadow of Jupiter), and the effect of Europa's internal heating. Here we estimate the surface temperature of Europa, when Europa's obliquity, eclipse and internal heating, as well as the eccentricity of Jupiter, are all taken into account. For a typical internal heating rate of 0.05 W/m$^2$ (corresponding to an ice thickness of about 10 kms), the equator, pole, and global mean surface temperatures are 101.7 K, 45.26 K, and 94.75 K, respectively. We found that the temperature at the high latitudes is significantly affected by the internal heating. We also studied the effect of the internal heating on the mean thickness of Europa's icy shell and conclude that the polar region temperature can be used to constrain the internal heating and the depth of the ice. Our approach and form...

  16. Direct assimilation of Chinese FY-3C Microwave Temperature Sounder-2 radiances in the global GRAPES system

    Science.gov (United States)

    Li, Juan; Liu, Guiqing

    2016-07-01

    FengYun-3C (FY-3C) is an operational polar-orbiting satellite carrying the new-generation microwave sounding instruments in China. This paper describes the assimilation of the FY-3C Microwave Temperature Sounder-2 (MWTS-2) radiances in the Global and Regional Assimilation and PrEdiction System (GRAPES) of China Meteorological Administration. A quality control (QC) procedure for the assimilation of MWTS-2 radiance is proposed. Extensive monitoring before assimilation shows that MWTS-2 observations exhibit a clear striping pattern. A technique combining principal component analysis (PCA) and ensemble empirical mode decomposition (EEMD) is applied to the observations to remove the striping noise. Cloudy field-of-views (FOVs) are identified by applying the Visible and InfrarRed Radiometer (VIRR) cloud fraction threshold of 76 %. Other QC steps are conducted in the follow order: (i) coastal FOVs are removed, (ii) eight outmost FOVs are not used, (iii) channel 5 data over sea ice and land are not used, (iv) channel 6 observations are not used if the terrain altitudes are higher than 500 m, and (v) outliers with large differences between observations and model simulations are removed. Approximately 83, 75, 40, and 40 % of the observations are removed by the proposed QC for channels 5-8, respectively. After QC, the global biases and standard deviations are reduced significantly. The assimilation of the MWTS-2 radiances shows a positive impact when the control experiment assimilates only conventional observations. The experiments also show that the analysis and forecast errors are slightly reduced when the striping noise is removed from the observations. The quality control scheme of extracting the striping noise may contribute to the analysis and forecast accuracy. The impact of MWTS-2 is neutral when the conventional data and other satellite data are all assimilated.

  17. Estimating surface turbulent heat fluxes from land surface temperature and soil moisture observations using the particle batch smoother

    Science.gov (United States)

    Lu, Yang; Dong, Jianzhi; Steele-Dunne, Susan C.; van de Giesen, Nick

    2016-11-01

    Surface heat fluxes interact with the overlying atmosphere and play a crucial role in meteorology, hydrology, and climate change studies, but in situ observations are costly and difficult. It has been demonstrated that surface heat fluxes can be estimated from assimilation of land surface temperature (LST). One approach is to estimate a neutral bulk heat transfer coefficient (CHN) to scale the sum of turbulent heat fluxes, and an evaporative fraction (EF) that represents the partitioning between fluxes. Here the newly developed particle batch smoother (PBS) is implemented. The PBS makes no assumptions about the prior distributions and is therefore well-suited for non-Gaussian processes. It is also particularly advantageous for parameter estimation by tracking the entire prior distribution of parameters using Monte Carlo sampling. To improve the flux estimation on wet or densely vegetated surfaces, a simple soil moisture scheme is introduced to further constrain EF, and soil moisture observations are assimilated simultaneously. This methodology is implemented with the FIFE 1987 and 1988 data sets. Validation against observed fluxes indicates that assimilating LST using the PBS significantly improves the flux estimates at both daily and half-hourly timescales. When soil moisture is assimilated, the estimated EFs become more accurate, particularly when the surface heat flux partitioning is energy-limited. The feasibility of extending the methodology to use remote sensing observations is tested by limiting the number of LST observations. Results show that flux estimates are greatly improved after assimilating soil moisture, particularly when LST observations are sparse.

  18. Determining soil moisture and soil properties in vegetated areas by assimilating soil temperatures

    Science.gov (United States)

    Dong, Jianzhi; Steele-Dunne, Susan C.; Ochsner, Tyson E.; van de Giesen, Nick

    2016-06-01

    This study addresses two critical barriers to the use of Passive Distributed Temperature Sensing (DTS) for large-scale, high-resolution monitoring of soil moisture. In recent research, a particle batch smoother (PBS) was developed to assimilate sequences of temperature data at two depths into Hydrus-1D to estimate soil moisture as well as soil thermal and hydraulic properties. However, this approach was limited to bare soil and assumed that the cable depths were perfectly known. In order for Passive DTS to be more broadly applicable as a soil hydrology research and remote sensing soil moisture product validation tool, it must be applicable in vegetated areas. To address this first limitation, the forward model (Hydrus-1D) was improved through the inclusion of a canopy energy balance scheme. Synthetic tests were used to demonstrate that without the canopy energy balance scheme, the PBS estimated soil moisture could be even worse than the open loop case (no assimilation). When the improved Hydrus-1D model was used as the forward model in the PBS, vegetation impacts on the soil heat and water transfer were well accounted for. This led to accurate and robust estimates of soil moisture and soil properties. The second limitation is that, cable depths can be highly uncertain in DTS installations. As Passive DTS uses the downward propagation of heat to extract moisture-related variations in thermal properties, accurate estimates of cable depths are essential. Here synthetic tests were used to demonstrate that observation depths can be jointly estimated with other model states and parameters. The state and parameter results were only slightly poorer than those obtained when the cable depths were perfectly known. Finally, in situ temperature data from four soil profiles with different, but known, soil textures were used to test the proposed approach. Results show good agreement between the observed and estimated soil moisture, hydraulic properties, thermal properties, and

  19. Assimilating the Cosmic-Ray Soil Moisture Observing System Measurements for Land Surface Hydrologic Model Parameter Estimation Using the Ensemble Kalman Filter

    Science.gov (United States)

    Xiao, D.; Shi, Y.; Li, L.

    2015-12-01

    Parameter estimation is generally required for land surface models (LSMs) and hydrologic models to reproduce observed water and energy fluxes in different watersheds. Using soil moisture observations for parameter estimation in addition to discharge and land surface temperature observations can improve the prediction of land surface and subsurface processes. Due to their representativity, point measurements cannot capture the watershed-scale soil moisture conditions and may lead to notable bias in watershed soil moisture predictions if used for model calibration. The intermediate-scale cosmic-ray soil moisture observing system (COSMOS) provides average soil water content measurement over a footprint of 0.34 m2 and depths up to 50 cm, and may provide better calibration data for low-order watersheds. In this study, we will test using COSMOS observations for Flux-PIHM parameter and state estimation via the ensemble Kalman filter (EnKF). Flux-PIHM is a physically-based land surface hydrologic model that couples the Penn State Integrated Hydrologic Model (PIHM) with the Noah land surface model. Synthetic data experiments will be performed at the Shale Hills watershed (area: 0.08 km2, smaller than COSMOS footprint) and the Garner Run watershed (1.34 km2, larger than COSMOS footprint) in the Shale Hills Susquehanna Critical Zone Observatory in central Pennsylvania. COSMOS observations will be assimilated into Flux-PIHM using the EnKF, in addition to discharge and land surface temperature (LST) observations. The accuracy of EnKF estimated parameters and water and energy flux predictions will be evaluated. In addition, the results will be compared with assimilating point soil moisture measurement (in addition to discharge and LST), to assess the effects of using different scales of soil moisture observations for parameter estimation. The results at Shale Hills and Garner Run will be compared to test whether performance of COSMOS data assimilation is affected by the size of

  20. Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model

    Science.gov (United States)

    De Lannoy, Gabrielle J.M.; Reichle, Rolf H.; Houser, Paul R.; Arsenault, Kristi R.; Verhoest, Niko E.C.; Paulwels, Valentijn R.N.

    2009-01-01

    An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.

  1. Data assimilation for the investigation of deep temperature and geothermal energy in the Netherlands.

    Science.gov (United States)

    Bonté, Damien; Limberger, Jon; Lipsey, Lindsey; Cloetingh, Sierd; van Wees, Jan-Diederik

    2016-04-01

    Deep geothermal energy systems, mostly for the direct use of heat, have been attracting more and more interest in the past 10 years in Western Europe. In the Netherlands, where the sector took off with the first system in 2005, geothermal energy is seen has a key player for a sustainable future. To support the development of deep geothermal energy system, the scientific community has been working on tools that could be used to highlight area of potential interest for geothermal exploration. In the Netherlands, ThermoGIS is one such tool that has been developed to inform the general public, policy makers, and developers in the energy sector of the possibility of geothermal energy development. One major component incorporated in this tool is the temperature model. For the Netherlands, we created a thermal model at the lithospheric scale that focus on the sedimentary deposits for deep geothermal exploration. This regional thermal modelling concentrates on the variations of geological thermal conductivity and heat production both in the sediments and in the crust. In addition, we carried out special modelling in order to specifically understand convectivity in the basin, focusing on variations at a regional scale. These works, as well as recent improved of geological knowledge in the deeper part of the basin, show interesting evidence for geothermal energy development. At this scale, the aim of this work is to build on these models and, using data assimilation, to discriminate in the actual causes of the observed anomalies. The temperature results obtained for the Netherlands show some thermal patterns that relate to the variation of the thermal conductivity and the geometry of the sediments. There is also strong evidence to indicate that deep convective flows are responsible for thermal anomalies. The combination of conductive and local convective thermal patterns makes the deeper part of the Dutch sedimentary basin of great interest for the development of geothermal

  2. Land surface parameter optimisation through data assimilation: the adJULES system

    Science.gov (United States)

    Raoult, Nina; Jupp, Tim; Cox, Peter

    2017-04-01

    Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed to search for locally optimum parameters by calibrating against observations. We present adJULES in a data assimilation framework and demonstrate its ability to improve the model-data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85% of the sites used in the study, at both the calibration and evaluation stages. The new improved parameters for JULES are presented along with the associated uncertainties for each parameter.

  3. Decadal changes in global surface NOx emissions from multi-constituent satellite data assimilation

    Science.gov (United States)

    Miyazaki, Kazuyuki; Eskes, Henk; Sudo, Kengo; Folkert Boersma, K.; Bowman, Kevin; Kanaya, Yugo

    2017-01-01

    Global surface emissions of nitrogen oxides (NOx) over a 10-year period (2005-2014) are estimated from an assimilation of multiple satellite data sets: tropospheric NO2 columns from Ozone Monitoring Instrument (OMI), Global Ozone Monitoring Experiment-2 (GOME-2), and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), O3 profiles from Tropospheric Emission Spectrometer (TES), CO profiles from Measurement of Pollution in the Troposphere (MOPITT), and O3 and HNO3 profiles from Microwave Limb Sounder (MLS) using an ensemble Kalman filter technique. Chemical concentrations of various species and emission sources of several precursors are simultaneously optimized. This is expected to improve the emission inversion because the emission estimates are influenced by biases in the modelled tropospheric chemistry, which can be partly corrected by also optimizing the concentrations. We present detailed distributions of the estimated emission distributions for all major regions, the diurnal and seasonal variability, and the evolution of these emissions over the 10-year period. The estimated regional total emissions show a strong positive trend over India (+29 % decade-1), China (+26 % decade-1), and the Middle East (+20 % decade-1), and a negative trend over the USA (-38 % decade-1), southern Africa (-8.2 % decade-1), and western Europe (-8.8 % decade-1). The negative trends in the USA and western Europe are larger during 2005-2010 relative to 2011-2014, whereas the trend in China becomes negative after 2011. The data assimilation also suggests a large uncertainty in anthropogenic and fire-related emission factors and an important underestimation of soil NOx sources in the emission inventories. Despite the large trends observed for individual regions, the global total emission is almost constant between 2005 (47.9 Tg N yr-1) and 2014 (47.5 Tg N yr-1).

  4. Assimilation of GRACE Terrestrial Water Storage Observations into a Land Surface Model for the Assessment of Regional Flood Potential

    Science.gov (United States)

    Reager, John T.; Thomas, Alys C.; Sproles, Eric A.; Rodell, Matthew; Beaudoing, Hiroko K.; Li, Bailing; Famiglietti, James S.

    2015-01-01

    We evaluate performance of the Catchment Land Surface Model (CLSM) under flood conditions after the assimilation of observations of the terrestrial water storage anomaly (TWSA) from NASA's Gravity Recovery and Climate Experiment (GRACE). Assimilation offers three key benefits for the viability of GRACE observations to operational applications: (1) near-real time analysis; (2) a downscaling of GRACE's coarse spatial resolution; and (3) state disaggregation of the vertically-integrated TWSA. We select the 2011 flood event in the Missouri river basin as a case study, and find that assimilation generally made the model wetter in the months preceding flood. We compare model outputs with observations from 14 USGS groundwater wells to assess improvements after assimilation. Finally, we examine disaggregated water storage information to improve the mechanistic understanding of event generation. Validation establishes that assimilation improved the model skill substantially, increasing regional groundwater anomaly correlation from 0.58 to 0.86. For the 2011 flood event in the Missouri river basin, results show that groundwater and snow water equivalent were contributors to pre-event flood potential, providing spatially-distributed early warning information.

  5. Assimilation of GRACE Terrestrial Water Storage Observations into a Land Surface Model for the Assessment of Regional Flood Potential

    Science.gov (United States)

    Reager, John T.; Thomas, Alys C.; Sproles, Eric A.; Rodell, Matthew; Beaudoing, Hiroko K.; Li, Bailing; Famiglietti, James S.

    2015-01-01

    We evaluate performance of the Catchment Land Surface Model (CLSM) under flood conditions after the assimilation of observations of the terrestrial water storage anomaly (TWSA) from NASA's Gravity Recovery and Climate Experiment (GRACE). Assimilation offers three key benefits for the viability of GRACE observations to operational applications: (1) near-real time analysis; (2) a downscaling of GRACE's coarse spatial resolution; and (3) state disaggregation of the vertically-integrated TWSA. We select the 2011 flood event in the Missouri river basin as a case study, and find that assimilation generally made the model wetter in the months preceding flood. We compare model outputs with observations from 14 USGS groundwater wells to assess improvements after assimilation. Finally, we examine disaggregated water storage information to improve the mechanistic understanding of event generation. Validation establishes that assimilation improved the model skill substantially, increasing regional groundwater anomaly correlation from 0.58 to 0.86. For the 2011 flood event in the Missouri river basin, results show that groundwater and snow water equivalent were contributors to pre-event flood potential, providing spatially-distributed early warning information.

  6. Towards the implementation of L-band Soil Moisture Brightness Temperatures in the Canadian Land Data Assimilation System (CaLDAS)

    Science.gov (United States)

    Carrera, Marco; Bilodeau, Bernard; Russell, Albert; Wang, Xihong; Belair, Stephane

    2016-04-01

    The Canadian Land Data Assimilation System (CaLDAS) currently runs in Environment Canada (EC) operations and provides the initial conditions for soil moisture and soil temperature to the High-Resolution Regional Deterministic Prediction System (HRDPS). Errors in screen-level temperature and dew-point temperature are used to analyze soil moisture and soil temperature. The observational gap in soil moisture is being alleviated by significant advances in remote sensing technologies specifically dedicated to the measurement of soil moisture. The Soil Moisture and Ocean Salinity (SMOS) satellite was launched by the European Space Agency (ESA) in November 2009 and has been providing global coverage of near-surface soil moisture every 3 days. In January 2015, the Soil Moisture Active Passive (SMAP) satellite was launched by NASA, and similar to SMOS, is equipped with a passive radiometer measuring the soil emission in the highly sensitive L-band frequency. The land-surface modeling component within CaLDAS has been coupled to the CMEM (Community Microwave Emission Modeling Platform) microwave radiative transfer model to allow for the assimilation of L-band brightness temperatures (TB). This study reports upon a series of pre-operational experiments exploring how best to combine the traditional screen-level variables with the more direct measurements of soil moisture provided by SMOS and SMAP for a better analysis of the soil moisture state. The study period will be the warm season periods for 2014 and 2015 over North America. Analyzed soil moistures will be compared against in-situ monitoring networks, but the principal focus will be upon the impacts in numerical weather prediction (NWP) mode. EC's Regional Deterministic Prediction System (RDPS), with 10 km grid spacing, is the principal NWP guidance used by Meteorological Service of Canada forecasters in the 1-2 day range. CaLDAS will be run assimilating different configurations of screen-level data and SMOS/SMAP TBs to

  7. Soil thermal dynamics, snow cover, and frozen depth under five temperature treatments in an ombrotrophic bog: Constrained forecast with data assimilation

    Science.gov (United States)

    Huang, Yuanyuan; Jiang, Jiang; Ma, Shuang; Ricciuto, Daniel; Hanson, Paul J.; Luo, Yiqi

    2017-08-01

    Accurate simulation of soil thermal dynamics is essential for realistic prediction of soil biogeochemical responses to climate change. To facilitate ecological forecasting at the Spruce and Peatland Responses Under Climatic and Environmental change site, we incorporated a soil temperature module into a Terrestrial ECOsystem (TECO) model by accounting for surface energy budget, snow dynamics, and heat transfer among soil layers and during freeze-thaw events. We conditioned TECO with detailed soil temperature and snow depth observations through data assimilation before the model was used for forecasting. The constrained model reproduced variations in observed temperature from different soil layers, the magnitude of snow depth, the timing of snowfall and snowmelt, and the range of frozen depth. The conditioned TECO forecasted probabilistic distributions of soil temperature dynamics in six soil layers, snow, and frozen depths under temperature treatments of +0.0, +2.25, +4.5, +6.75, and +9.0°C. Air warming caused stronger elevation in soil temperature during summer than winter due to winter snow and ice. And soil temperature increased more in shallow soil layers in summer in response to air warming. Whole ecosystem warming (peat + air warmings) generally reduced snow and frozen depths. The accuracy of forecasted snow and frozen depths relied on the precision of weather forcing. Uncertainty is smaller for forecasting soil temperature but large for snow and frozen depths. Timely and effective soil thermal forecast, constrained through data assimilation that combines process-based understanding and detailed observations, provides boundary conditions for better predictions of future biogeochemical cycles.

  8. The impact of Surface Wind Velocity Data Assimilation on the Predictability of Plume Advection in the Lower Troposphere

    Science.gov (United States)

    Sekiyama, Thomas; Kajino, Mizuo; Kunii, Masaru

    2017-04-01

    The authors investigated the impact of surface wind velocity data assimilation on the predictability of plume advection in the lower troposphere exploiting the radioactive cesium emitted by the Fukushima nuclear accident in March 2011 as an atmospheric tracer. It was because the radioactive cesium plume was dispersed from the sole point source exactly placed at the Fukushima Daiichi Nuclear Power Plant and its surface concentration was measured at many locations with a high frequency and high accuracy. We used a non-hydrostatic regional weather prediction model with a horizontal resolution of 3 km, which was coupled with an ensemble Kalman filter data assimilation system in this study, to simulate the wind velocity and plume advection. The main module of this weather prediction model has been developed and used operationally by the Japan Meteorological Agency (JMA) since before March 2011. The weather observation data assimilated into the model simulation were provided from two data resources; [#1] the JMA observation archives collected for numerical weather predictions (NWPs) and [#2] the land-surface wind velocity data archived by the JMA surface weather observation network. The former dataset [#1] does not contain land-surface wind velocity observations because their spatial representativeness is relatively small and therefore the land-surface wind velocity data assimilation normally deteriorates the more than one day NWP performance. The latter dataset [#2] is usually used for real-time weather monitoring and never used for the data assimilation of more than one day NWPs. We conducted two experiments (STD and TEST) to reproduce the radioactive cesium plume behavior for 48 hours from 12UTC 14 March to 12UTC 16 March 2011 over the land area of western Japan. The STD experiment was performed to replicate the operational NWP using only the #1 dataset, not assimilating land-surface wind observations. In contrast, the TEST experiment was performed assimilating both

  9. Extended Reconstructed Sea Surface Temperature (ERSST)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Extended Reconstructed Sea Surface Temperature (ERSST) dataset is a global monthly sea surface temperature analysis derived from the International Comprehensive...

  10. NOAA Global Surface Temperature (NOAAGlobalTemp)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a merged land–ocean surface temperature analysis (formerly known as MLOST) (link is external). It is...

  11. An ensemble Kalman filter dual assimilation of thermal infrared and microwave satellite observations of soil moisture into the Noah land surface model

    Science.gov (United States)

    Hain, Christopher R.; Crow, Wade T.; Anderson, Martha C.; Mecikalski, John R.

    2012-11-01

    Studies that have assimilated remotely sensed soil moisture (SM) into land surface models (LSMs) have generally focused on retrievals from microwave (MW) sensors. However, retrievals from thermal infrared (TIR) sensors have also been shown to add unique information, especially where MW sensors are not able to provide accurate retrievals (due to, e.g., dense vegetation). In this study, we examine the assimilation of a TIR product based on surface evaporative flux estimates from the Atmosphere Land Exchange Inverse (ALEXI) model and the MW-based VU Amsterdam NASA surface SM product generated with the Land Parameter Retrieval Model (LPRM). A set of data assimilation experiments using an ensemble Kalman filter are performed over the contiguous United States to assess the impact of assimilating ALEXI and LPRM SM retrievals in isolation and together in a dual-assimilation case. The relative skill of each assimilation case is assessed through a data denial approach where a LSM is forced with an inferior precipitation data set. The ability of each assimilation case to correct for precipitation errors is quantified by comparing with a simulation forced with a higher-quality precipitation data set. All three assimilation cases (ALEXI, LPRM, and Dual assimilation) show relative improvements versus the open loop (i.e., reduced RMSD) for surface and root zone SM. In the surface zone, the dual assimilation case provides the largest improvements, followed by the LPRM case. However, the ALEXI case performs best in the root zone. Results from the data denial experiment are supported by comparisons between assimilation results and ground-based SM observations from the Soil Climate Analysis Network.

  12. Quantifying the impacts of snow on surface energy balance through assimilating snow cover fraction and snow depth

    Science.gov (United States)

    Meng, Chunlei

    2016-10-01

    Seasonal snow plays an important part in Earth's climate system. Snow cover regulates the land surface energy balance through altering the albedo of the land surface. To utilize the satellite-retrieved snow cover fraction (SCF) and snow depth (SD) data sufficiently and avoid inconsistency, this paper developed a very simple but robust quality control method to assimilate Fengyun satellite-retrieved SCF and SD simultaneously. The results show that the assimilation method which this paper implemented can not only utilize the satellite-retrieved SCF and SD data sufficiently but also avoid the inconsistency of them. Two experiments were designed and performed to quantify the impacts of snow on land surface energy balance using the integrated urban land model. With the increase of the SCF and SD, the net radiation decreased significantly during the day and increased a little at night; the sensible heat flux decreased significantly during the day; the evapotranspiration and ground heat flux decreased during the day too.

  13. Probabilistic nowcast of PBL profiles with a single column model and ensemble filter assimilation of surface observations

    Science.gov (United States)

    Rostkier-Edelstein, D.; Hacker, J. P.

    2009-09-01

    A long-term goal of this work is to find an efficient system for probabilistic planetary boundary layer (PBL) nowcasting that can be deployed wherever surface observations are present. One approach showing promise is the use of a single column model (SCM) and ensemble filter (EF) data assimilation techniques. Earlier work showed that surface observations can be an important source of information with an SCM and an EF. Here we extend that work to quantify the deterministic and probabilistic skill of ensemble SCM predictions with added complexity. Although it is appealing to add additional physics and dynamics to the SCM model it is not immediately clear that additional complexity will improve the performance of a PBL nowcasting system based on a simple model. We address this question with regard to treatment of surface assimilation, radiation in the column, and also advection to account for realistic 3D dynamics (a timely WRF prediction). We adopt factor separation analysis to quantify the individual contribution of each model component to the deterministic and probabilistic skill of the system, as well as any beneficial or detrimental interactions between them. Deterministic skill of the system is evaluated through the mean absolute error, and probabilistic skill through the Brier Skill Score (BSS) and the area under the relative operating characteristic (ROC) curve (AUR). The BSS is further decomposed into both a reliability and resolution term to understand the trade-offs in different components of probabilistic skill. An alternative system based on climatological covariances and surface observations is used as a reference to assess the real utility of the flow-dependent covariances estimated with the ensemble system. In essence it is a dressing technique, whereby a deterministic 3D mesoscale forecast (e.g. WRF) is corrected with surface forecast errors and covariances computed from a distribution of available historical mesoscale forecasts. The adjusted profile

  14. Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions

    Directory of Open Access Journals (Sweden)

    A. Babenhauserheide

    2015-09-01

    Full Text Available Data assimilation systems allow for estimating surface fluxes of greenhouse gases from atmospheric concentration measurements. Good knowledge about fluxes is essential to understand how climate change affects ecosystems and to characterize feedback mechanisms. Based on the assimilation of more than 1 year of atmospheric in situ concentration measurements, we compare the performance of two established data assimilation models, CarbonTracker and TM5-4DVar (Transport Model 5 – Four-Dimensional Variational model, for CO2 flux estimation. CarbonTracker uses an ensemble Kalman filter method to optimize fluxes on ecoregions. TM5-4DVar employs a 4-D variational method and optimizes fluxes on a 6° × 4° longitude–latitude grid. Harmonizing the input data allows for analyzing the strengths and weaknesses of the two approaches by direct comparison of the modeled concentrations and the estimated fluxes. We further assess the sensitivity of the two approaches to the density of observations and operational parameters such as the length of the assimilation time window. Our results show that both models provide optimized CO2 concentration fields of similar quality. In Antarctica CarbonTracker underestimates the wintertime CO2 concentrations, since its 5-week assimilation window does not allow for adjusting the distant surface fluxes in response to the detected concentration mismatch. Flux estimates by CarbonTracker and TM5-4DVar are consistent and robust for regions with good observation coverage, regions with low observation coverage reveal significant differences. In South America, the fluxes estimated by TM5-4DVar suffer from limited representativeness of the few observations. For the North American continent, mimicking the historical increase of the measurement network density shows improving agreement between CarbonTracker and TM5-4DVar flux estimates for increasing observation density.

  15. Indication of temperature inverted microbial assimilative capacities (extracellular enzymes activities in the pelagic of Lake Sevan (Armenia

    Directory of Open Access Journals (Sweden)

    Arevik MINASYAN

    2016-06-01

    Full Text Available Pioneering records of extracellular enzymes activities (EEA in Lake Sevan waters highlight dependence of heterotrophic functioning on physicochemical characteristics and bacterial assemblage. Values of EEA, ranged 0.11-30.39 µg C/P L-1h-1, were higher in upper layers compared to the omission in deeper parts. Particles associated (ecto- enzymes mainly predominated over free dissolved (exo- enzymes. In June activities of all studied enzymes followed similar pattern, particularly, decreasing at thermocline and increasing twice/more in cold deeper waters. Regardless higher bacterial density and temperature in June, with no similar records up to now, EEA revealed reverse relationship to temperature and bacteria data and were significantly lesser than in March. Our finding might be suggested as temperature inverted impact to heterotrophic activities in eutrophic conditions. We assume that observed, with temperature raise, declined EEA was due to blocked enzymatic active center from colloids and DOM components interaction, which, in overall, may suppress organic substrate utilization and result in weakening of first and rate limiting step of biological self-purification in Lake Sevan waters. Therefore, since temperature is co-regulator of assimilative/carrying capacity of aquatic ecosystems, climate warming might have unexpected negative feedbacks also through lowering assimilative capacities of water bodies, jeopardizing their quality and ecology.

  16. The Pacific sea surface temperature

    Energy Technology Data Exchange (ETDEWEB)

    Douglass, David H., E-mail: douglass@pas.rochester.edu [Department of Physics and Astronomy, University of Rochester, Rochester, NY 14627-0171 (United States)

    2011-12-05

    The Pacific sea surface temperature data contains two components: N{sub L}, a signal that exhibits the familiar El Niño/La Niña phenomenon and N{sub H}, a signal of one-year period. Analysis reveals: (1) The existence of an annual solar forcing F{sub S}; (2) N{sub H} is phase locked directly to F{sub S} while N{sub L} is frequently phase locked to the 2nd or 3rd subharmonic of F{sub S}. At least ten distinct subharmonic time segments of N{sub L} since 1870 are found. The beginning or end dates of these segments have a near one-to-one correspondence with the abrupt climate changes previously reported. Limited predictability is possible. -- Highlights: ► El Niño/La Niña consists of 2 components phase-locked to annual solar cycle. ► The first component N{sub L} is the familiar El Niño/La Niña effect. ► The second N{sub H} component has a period of 1 cycle/year. ► N{sub L} can be phase-locked to 2nd or 3rd subharmonic of annual cycle. ► Ends of phase-locked segments correspond to abrupt previously reported climate changes.

  17. Estimating the Soil Moisture Profile by Assimilating Near-Surface Observations with the Ensemble Kalman Filter (EnKF)

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The paper investigates the ability to retrieve the true soil moisture profile by assimilating near-surface soil moisture into a soil moisture model with an ensemble Kalman filter (EnKF) assimilation scheme,including the effect of ensemble size, update interval and nonlinearities in the profile retrieval, the required time for full retrieval of the soil moisture profiles, and the possible influence of the depth of the soil moisture observation. These questions are addressed by a desktop study using synthetic data. The "true"soil moisture profiles are generated from the soil moisture model under the boundary condition of 0.5 cm d-1 evaporation. To test the assimilation schemes, the model is initialized with a poor initial guess of the soil moisture profile, and different ensemble sizes are tested showing that an ensemble of 40 members is enough to represent the covariance of the model forecasts. Also compared are the results with those from the direct insertion assimilation scheme, showing that the EnKF is superior to the direct insertion assimilation scheme, for hourly observations, with retrieval of the soil moisture profile being achieved in 16 h as compared to 12 days or more. For daily observations, the true soil moisture profile is achieved in about 15 days with the EnKF, but it is impossible to approximate the true moisture within 18 days by using direct insertion. It is also found that observation depth does not have a significant effect on profile retrieval time for the EnKF. The nonlinearities have some negative influence on the optimal estimates of soil moisture profile but not very seriously.

  18. Surface temperature measurements of diamond

    CSIR Research Space (South Africa)

    Masina, BN

    2006-07-01

    Full Text Available ) and the waist position (z0) 3. TEMPERATURE MEASUREMENTS There are many methods to measure the temperature of a body. Here we used a thermocou- ple and a pyrometer, while future plans involve emission spectroscopy. A thermocouple is a temperature... sensor that consists of two wires con- nected together made from different metals, which produces an electrical voltage that is dependant on tem- perature. A Newport electronic thermocou- ple was used to meas- ured temperature. It can measure...

  19. Data Assimilation algorithm for 3D B\\'enard convection in porous media employing only temperature measurements

    CERN Document Server

    Farhat, Aseel; Titi, Edriss S

    2015-01-01

    In this paper we propose a continuous data assimilation (downscaling) algorithm for the B\\'enard convection in porous medium using only coarse mesh measurements of the temperature field. In this algorithm, we incorporate the observables as a feedback (nudging) term in the evolution equation of the temperature. We show that under an appropriate choice of the nudging parameter and the size of the mesh, and under the assumption that the observed data is error free, the solution of the proposed algorithm approaches at an exponential rate asymptotically in time to the unique exact unknown reference solution of the original system, associated with the observed (finite dimensional projection of) temperature data. Moreover, in the case where the observational measurements are not error free, one can estimate the error between the solution of the algorithm and the exact reference solution of the system in terms of the error in the measurements.

  20. TerrSysMP-PDAF (version 1.0): a modular high-performance data assimilation framework for an integrated land surface-subsurface model

    Science.gov (United States)

    Kurtz, Wolfgang; He, Guowei; Kollet, Stefan J.; Maxwell, Reed M.; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

    2016-04-01

    Modelling of terrestrial systems is continuously moving towards more integrated modelling approaches, where different terrestrial compartment models are combined in order to realise a more sophisticated physical description of water, energy and carbon fluxes across compartment boundaries and to provide a more integrated view on terrestrial processes. While such models can effectively reduce certain parameterisation errors of single compartment models, model predictions are still prone to uncertainties regarding model input variables. The resulting uncertainties of model predictions can be effectively tackled by data assimilation techniques, which allow one to correct model predictions with observations taking into account both the model and measurement uncertainties. The steadily increasing availability of computational resources makes it now increasingly possible to perform data assimilation also for computationally highly demanding integrated terrestrial system models. However, as the computational burden for integrated models as well as data assimilation techniques is quite large, there is an increasing need to provide computationally efficient data assimilation frameworks for integrated models that allow one to run on and to make efficient use of massively parallel computational resources. In this paper we present a data assimilation framework for the land surface-subsurface part of the Terrestrial System Modelling Platform (TerrSysMP). TerrSysMP is connected via a memory-based coupling approach with the pre-existing parallel data assimilation library PDAF (Parallel Data Assimilation Framework). This framework provides a fully parallel modular environment for performing data assimilation for the land surface and the subsurface compartment. A simple synthetic case study for a land surface-subsurface system (0.8 million unknowns) is used to demonstrate the effects of data assimilation in the integrated model TerrSysMP and to assess the scaling behaviour of the

  1. Modelling global fresh surface water temperature

    NARCIS (Netherlands)

    Beek, L.P.H. van; Eikelboom, T.; Vliet, M.T.H. van; Bierkens, M.F.P.

    2011-01-01

    Temperature directly determines a range of water physical properties including vapour pressure, surface tension, density and viscosity, and the solubility of oxygen and other gases. Indirectly water temperature acts as a strong control on fresh water biogeochemistry, influencing sediment

  2. Modelling global fresh surface water temperature

    NARCIS (Netherlands)

    Beek, L.P.H. van; Eikelboom, T.; Vliet, M.T.H. van; Bierkens, M.F.P.

    2011-01-01

    Temperature directly determines a range of water physical properties including vapour pressure, surface tension, density and viscosity, and the solubility of oxygen and other gases. Indirectly water temperature acts as a strong control on fresh water biogeochemistry, influencing sediment concentrati

  3. Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions

    Directory of Open Access Journals (Sweden)

    A. Babenhauserheide

    2015-03-01

    Full Text Available Data assimilation systems allow for estimating surface fluxes of greenhouse gases from atmospheric concentration measurements. Good knowledge about fluxes is essential to understand how climate change affects ecosystems and to characterize feedback mechanisms. Based on assimilation of more than one year of atmospheric in-situ concentration measurements, we compare the performance of two established data assimilation models, CarbonTracker and TM5-4DVar, for CO2 flux estimation. CarbonTracker uses an Ensemble Kalman Filter method to optimize fluxes on ecoregions. TM5-4DVar employs a 4-D variational method and optimizes fluxes on a 6° × 4° longitude/latitude grid. Harmonizing the input data allows analyzing the strengths and weaknesses of the two approaches by direct comparison of the modelled concentrations and the estimated fluxes. We further assess the sensitivity of the two approaches to the density of observations and operational parameters such as temporal and spatial correlation lengths. Our results show that both models provide optimized CO2 concentration fields of similar quality. In Antarctica CarbonTracker underestimates the wintertime CO2 concentrations, since its 5-week assimilation window does not allow for adjusting the far-away surface fluxes in response to the detected concentration mismatch. Flux estimates by CarbonTracker and TM5-4DVar are consistent and robust for regions with good observation coverage, regions with low observation coverage reveal significant differences. In South America, the fluxes estimated by TM5-4DVar suffer from limited representativeness of the few observations. For the North American continent, mimicking the historical increase of measurement network density shows improving agreement between CarbonTracker and TM5-4DVar flux estimates for increasing observation density.

  4. A new stepwise carbon cycle data assimilation system using multiple data streams to constrain the simulated land surface carbon cycle

    Science.gov (United States)

    Peylin, Philippe; Bacour, Cédric; MacBean, Natasha; Leonard, Sébastien; Rayner, Peter; Kuppel, Sylvain; Koffi, Ernest; Kane, Abdou; Maignan, Fabienne; Chevallier, Frédéric; Ciais, Philippe; Prunet, Pascal

    2016-09-01

    Large uncertainties in land surface models (LSMs) simulations still arise from inaccurate forcing, poor description of land surface heterogeneity (soil and vegetation properties), incorrect model parameter values and incomplete representation of biogeochemical processes. The recent increase in the number and type of carbon cycle-related observations, including both in situ and remote sensing measurements, has opened a new road to optimize model parameters via robust statistical model-data integration techniques, in order to reduce the uncertainties of simulated carbon fluxes and stocks. In this study we present a carbon cycle data assimilation system that assimilates three major data streams, namely the Moderate Resolution Imaging Spectroradiometer (MODIS)-Normalized Difference Vegetation Index (NDVI) observations of vegetation activity, net ecosystem exchange (NEE) and latent heat (LE) flux measurements at more than 70 sites (FLUXNET), as well as atmospheric CO2 concentrations at 53 surface stations, in order to optimize the main parameters (around 180 parameters in total) of the Organizing Carbon and Hydrology in Dynamics Ecosystems (ORCHIDEE) LSM (version 1.9.5 used for the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations). The system relies on a stepwise approach that assimilates each data stream in turn, propagating the information gained on the parameters from one step to the next. Overall, the ORCHIDEE model is able to achieve a consistent fit to all three data streams, which suggests that current LSMs have reached the level of development to assimilate these observations. The assimilation of MODIS-NDVI (step 1) reduced the growing season length in ORCHIDEE for temperate and boreal ecosystems, thus decreasing the global mean annual gross primary production (GPP). Using FLUXNET data (step 2) led to large improvements in the seasonal cycle of the NEE and LE fluxes for all ecosystems (i.e., increased amplitude for temperate ecosystems). The

  5. The impact of assumed error variances on surface soil moisture and snow depth hydrologic data assimilation

    Science.gov (United States)

    Accurate knowledge of antecedent soil moisture and snow depth conditions is often important for obtaining reliable hydrological simulations of stream flow. Data assimilation (DA) methods can be used to integrate remotely-sensed (RS) soil moisture and snow depth retrievals into a hydrology model and...

  6. Assimilating Remotely Sensed Surface Soil Moisture into SWAT using Ensemble Kalman Filter

    Science.gov (United States)

    In this study, a 1-D Ensemble Kalman Filter has been used to update the soil moisture states of the Soil and Water Assessment Tool (SWAT) model. Experiments were conducted for the Cobb Creek Watershed in southeastern Oklahoma for 2006-2008. Assimilation of in situ data proved limited success in the ...

  7. Data Assimilation for Wildland Fires: Ensemble Kalman filters in coupled atmosphere-surface models

    OpenAIRE

    Mandel, Jan; Beezley, Jonathan D.; Coen, Janice L.; Kim, Minjeong

    2007-01-01

    Two wildland fire models are described, one based on reaction-diffusion-convection partial differential equations, and one based on semi-empirical fire spread by the level let method. The level set method model is coupled with the Weather Research and Forecasting (WRF) atmospheric model. The regularized and the morphing ensemble Kalman filter are used for data assimilation.

  8. Data Assimilation for Wildland Fires: Ensemble Kalman filters in coupled atmosphere-surface models

    CERN Document Server

    Mandel, Jan; Coen, Janice L; Kim, Minjeong

    2007-01-01

    Two wildland fire models are described, one based on reaction-diffusion-convection partial differential equations, and one based on empirical fire spread by the level let method. The level set method model is coupled with the Weather Research and Forecasting (WRF) atmospheric model. The regularized and the morphing ensemble Kalman filter are used for data assimilation.

  9. Assimilation of Soil Wetness Index and Leaf Area Index into the ISBA-A-gs land surface model: grassland case study

    Directory of Open Access Journals (Sweden)

    A. L. Barbu

    2011-02-01

    Full Text Available The performance of the joint assimilation in a land surface model of a Soil Wetness Index (SWI product provided by an exponential filter together with Leaf Area Index (LAI is investigated. The data assimilation is evaluated with different setups using the SURFEX modeling platform, for a period of seven years (2001–2007, at the SMOSREX grassland site in southwestern France. The results obtained with a Simplified Extended Kalman Filter demonstrate the effectiveness of a joint data assimilation scheme when both SWI and Leaf Area Index are merged into the ISBA-A-gs land surface model. The assimilation of a retrieved Soil Wetness Index product presents several challenges that are investigated in this study. A significant improvement of around 13% of the root-zone soil water content is obtained by assimilating dimensionless root-zone SWI data. For comparison, the assimilation of in situ surface soil moisture is considered as well. A lower impact on the root zone is noticed. Under specific conditions, the transfer of the information from the surface to the root zone was found not accurate. Also, our results indicate that the assimilation of in situ LAI data may correct a number of deficiencies in the model, such as low LAI values in the senescence phase by using a seasonal-dependent error definition for background and observations. In order to verify the specification of the errors for SWI and LAI products, a posteriori diagnostics are employed. This approach highlights the importance of the assimilation design on the quality of the analysis. The impact of data assimilation scheme on CO2 fluxes is also quantified by using measurements of net CO2 fluxes gathered at the SMOSREX site from 2005 to 2007. An improvement of about 5% in terms of rms error is obtained.

  10. Role of surface temperature in fluorocarbon plasma-surface interactions

    Energy Technology Data Exchange (ETDEWEB)

    Nelson, Caleb T.; Overzet, Lawrence J.; Goeckner, Matthew J. [Department of Electrical Engineering, University of Texas at Dallas, PO Box 830688, Richardson, TX 75083 (United States)

    2012-07-15

    This article examines plasma-surface reaction channels and the effect of surface temperature on the magnitude of those channels. Neutral species CF{sub 4}, C{sub 2}F{sub 6}, and C{sub 3}F{sub 8} are produced on surfaces. The magnitude of the production channel increases with surface temperature for all species, but favors higher mass species as the temperature is elevated. Additionally, the production rate of CF{sub 2} increases by a factor of 5 as the surface temperature is raised from 25 Degree-Sign C to 200 Degree-Sign C. Fluorine density, on the other hand, does not change as a function of either surface temperature or position outside of the plasma glow. This indicates that fluorine addition in the gas-phase is not a dominant reaction. Heating reactors can result in higher densities of depositing radical species, resulting in increased deposition rates on cooled substrates. Finally, the sticking probability of the depositing free radical species does not change as a function of surface temperature. Instead, the surface temperature acts together with an etchant species (possibly fluorine) to elevate desorption rates on that surface at temperatures lower than those required for unassisted thermal desorption.

  11. Data assimilation of surface displacements to improve geomechanical parameters of gas storage reservoirs

    Science.gov (United States)

    Zoccarato, C.; Baó, D.; Ferronato, M.; Gambolati, G.; Alzraiee, A.; Teatini, P.

    2016-03-01

    Although the beginning of reservoir geomechanics dates back to the late 1960s, only recently stochastical geomechanical modelling has been introduced into the general framework of reservoir operational planning. In this study, the ensemble smoother (ES) algorithm, i.e., an ensemble-based data assimilation method, is employed to reduce the uncertainty of the constitutive parameters characterizing the geomechanical model of an underground gas storage (UGS) field situated in the upper Adriatic sedimentary basin (Italy), the Lombardia UGS. The model is based on a nonlinear transversely isotropic stress-strain constitutive law and is solved by 3-D finite elements. The Lombardia UGS experiences seasonal pore pressure change caused by fluid extraction/injection leading to land settlement/upheaval. The available observations consist of vertical and horizontal time-lapse displacements accurately measured by persistent scatterer interferometry (PSI) on RADARSAT scenes acquired between 2003 and 2008. The positive outcome of preliminary tests on simplified cases has supported the use of the ES to jointly assimilate vertical and horizontal displacements. The ES approach is shown to effectively reduce the spread of the uncertain parameters, i.e., the Poisson's ratio, the ratio between the horizontal and vertical Young and shear moduli, and the ratio between the virgin loading (I cycle) and unloading/reloading (II cycle) compressibility. The outcomes of the numerical simulations point out that the updated parameters depend on the assimilated measurement locations as well as the error associated to the PSI measurements. The parameter estimation may be improved by taking into account possible model and/or observation biases along with the use of an assimilation approach, e.g., the Iterative ensemble smoother, more appropriate for nonlinear problems.

  12. An Ensemble Recentering Kalman Filter with an Application to Argo Temperature Data Assimilation into the NASA GEOS-5 Coupled Model

    Science.gov (United States)

    Keppenne, Christian L.

    2013-01-01

    A two-step ensemble recentering Kalman filter (ERKF) analysis scheme is introduced. The algorithm consists of a recentering step followed by an ensemble Kalman filter (EnKF) analysis step. The recentering step is formulated such as to adjust the prior distribution of an ensemble of model states so that the deviations of individual samples from the sample mean are unchanged but the original sample mean is shifted to the prior position of the most likely particle, where the likelihood of each particle is measured in terms of closeness to a chosen subset of the observations. The computational cost of the ERKF is essentially the same as that of a same size EnKF. The ERKF is applied to the assimilation of Argo temperature profiles into the OGCM component of an ensemble of NASA GEOS-5 coupled models. Unassimilated Argo salt data are used for validation. A surprisingly small number (16) of model trajectories is sufficient to significantly improve model estimates of salinity over estimates from an ensemble run without assimilation. The two-step algorithm also performs better than the EnKF although its performance is degraded in poorly observed regions.

  13. Assimilation of surface NO2 and O3 observations into the SILAM chemistry transport model

    Science.gov (United States)

    Vira, J.; Sofiev, M.

    2015-02-01

    This paper describes the assimilation of trace gas observations into the chemistry transport model SILAM (System for Integrated modeLling of Atmospheric coMposition) using the 3D-Var method. Assimilation results for the year 2012 are presented for the prominent photochemical pollutants ozone (O3) and nitrogen dioxide (NO2). Both species are covered by the AirBase observation database, which provides the observational data set used in this study. Attention was paid to the background and observation error covariance matrices, which were obtained primarily by the iterative application of a posteriori diagnostics. The diagnostics were computed separately for 2 months representing summer and winter conditions, and further disaggregated by time of day. This enabled the derivation of background and observation error covariance definitions, which included both seasonal and diurnal variation. The consistency of the obtained covariance matrices was verified using χ2 diagnostics. The analysis scores were computed for a control set of observation stations withheld from assimilation. Compared to a free-running model simulation, the correlation coefficient for daily maximum values was improved from 0.8 to 0.9 for O3 and from 0.53 to 0.63 for NO2.

  14. The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

    Science.gov (United States)

    Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

    2006-01-01

    Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

  15. Assimilation of leaf area index and surface soil moisture satellite observations into the SIM hydrological model over France

    Science.gov (United States)

    Fairbairn, David; Calvet, Jean-Christophe; Mahfouf, Jean-Francois; Barbu, Alina

    2016-04-01

    Hydrological models have a variety of uses, including flood and drought prediction and water management. The SAFRAN-ISBA-MODCOU (SIM) hydrological model consists of three stages: An atmospheric analysis (SAFRAN) over France, which forces a land surface model (ISBA-A-gs), which then provides drainage and runoff inputs to a hydrological model (MODCOU). The river discharge from MODCOU is validated using observed river discharge over France. Data assimilation (DA) combines a short model forecast from the past with observations to improve the estimate of the model state. The ISBA-A-gs representation of soil moisture and its influence by vegetation can be improved by assimilating surface soil moisture (SSM) and leaf area index (LAI) observations respectively. The Advanced Scatterometer (ASCAT) on board the MetOP satellite measures a low-frequency microwave signal, which is used to retrieve daily SSM over France. The SPOT-VGT sensor observes LAI over France at a temporal frequency of about 10 days. The Simplified Extended Kalman (SEKF) filter combines the model and observed variables by weighting them according to their respective accuracies. Although the SEKF makes incorrect linear assumptions, past experiments have shown that it improves on the model estimates of SSM and LAI. However, due to nonlinearities in the land surface model, improvements in SSM and LAI do not imply improved soil moisture fluxes (drainage, runoff and evapotranspiration). This study indirectly examines the impact of the SEKF on the soil moisture fluxes using the MODCOU hydrological model. The ISBA-A-gs model appears to underestimate the LAI for grasslands in winter and spring, which results in an underestimation (overestimation) of evapotranspiration (drainage and runoff). The excess water flowing into the rivers and aquifers contributes to an overestimation of the MODCOU discharge. Assimilating LAI observations slightly increases the LAI analysis in winter and spring and therefore reduces the

  16. Impact of satellite-based lake surface observations on the initial state of HIRLAM. Part II: Analysis of lake surface temperature and ice cover

    Directory of Open Access Journals (Sweden)

    Homa Kheyrollah Pour

    2014-09-01

    Full Text Available This paper presents results from a study on the impact of remote-sensing Lake Surface Water Temperature (LSWT observations in the analysis of lake surface state of a numerical weather prediction (NWP model. Data assimilation experiments were performed with the High Resolution Limited Area Model (HIRLAM, a three-dimensional operational NWP model. Selected thermal remote-sensing LSWT observations provided by the Moderate Resolution Imaging Spectroradiometer (MODIS and Advanced Along-Track Scanning Radiometer (AATSR sensors onboard the Terra/Aqua and ENVISAT satellites, respectively, were included into the assimilation. The domain of our experiments, which focussed on two winters (2010–2011 and 2011–2012, covered northern Europe. Validation of the resulting objective analyses against independent observations demonstrated that the description of the lake surface state can be improved by the introduction of space-borne LSWT observations, compared to the result of pure prognostic parameterisations or assimilation of the available limited number of in-situ lake temperature observations. Further development of the data assimilation methods and solving of several practical issues are necessary in order to fully benefit from the space-borne observations of lake surface state for the improvement of the operational weather forecast. This paper is the second part of a series of two papers aimed at improving the objective analysis of lake temperature and ice conditions in HIRLAM.

  17. Gravity increased by lunar surface temperature

    Science.gov (United States)

    Keene, James

    2013-04-01

    Quantitatively large effects of lunar surface temperature on apparent gravitational force measured by lunar laser ranging (LLR) and lunar perigee may challenge widely accepted theories of gravity. LLR data grouped by days from full moon shows the moon is about 5 percent closer to earth at full moon compared to 8 days before or after full moon. In a second, related result, moon perigees were least distant in days closer to full moon. Moon phase was used as proxy independent variable for lunar surface temperature. The results support the prediction by binary mechanics that gravitational force increases with object surface temperature.

  18. Forecasting of Surface Currents via Correcting Wind Stress with Assimilation of High-Frequency Radar Data in a Three-Dimensional Model

    Directory of Open Access Journals (Sweden)

    Lei Ren

    2016-01-01

    Full Text Available This paper details work in assessing the capability of a hydrodynamic model to forecast surface currents and in applying data assimilation techniques to improve model forecasts. A three-dimensional model Environment Fluid Dynamics Code (EFDC was forced with tidal boundary data and onshore wind data, and so forth. Surface current data from a high-frequency (HF radar system in Galway Bay were used for model intercomparisons and as a source for data assimilation. The impact of bottom roughness was also investigated. Having developed a “good” water circulation model the authors sought to improve its forecasting ability through correcting wind shear stress boundary conditions. The differences in surface velocity components between HF radar measurements and model output were calculated and used to correct surface shear stresses. Moreover, data assimilation cycle lengths were examined to extend the improvements of surface current’s patterns during forecasting period, especially for north-south velocity component. The influence of data assimilation in model forecasting was assessed using a Data Assimilation Skill Score (DASS. Positive magnitude of DASS indicated that both velocity components were considerably improved during forecasting period. Additionally, the improvements of RMSE for vector direction over domain were significant compared with the “free run.”

  19. Sea Surface Temperature Average_SST_Master

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Sea surface temperature collected via satellite imagery from http://www.esrl.noaa.gov/psd/data/gridded/data.noaa.ersst.html and averaged for each region using ArcGIS...

  20. OW NOAA GOES Sea-Surface Temperature

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset contains satellite-derived sea-surface temperature measurements collected by means of the Geostationary Orbiting Environmental Satellite. The data is...

  1. evaluation of land surface temperature parameterization ...

    African Journals Online (AJOL)

    user

    1 DEPARTMENT OF PHYSICS, ADEYEMI COLLEGE OF EDUCATION, ONDO, ... Surface temperature (Ts) is vital to the study of land-atmosphere interactions and climate variabilities. .... value = 0.167 m3m-3), and very low for dry days (mean.

  2. Monthly Near-Surface Air Temperature Averages

    Data.gov (United States)

    National Aeronautics and Space Administration — Global surface temperatures in 2010 tied 2005 as the warmest on record. The International Satellite Cloud Climatology Project (ISCCP) was established in 1982 as part...

  3. Sea Surface Temperature (14 KM North America)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Product shows local sea surface temperatures (degrees C). It is a composite gridded-image derived from 8-km resolution SST Observations. It is generated every 48...

  4. Analysed foundation sea surface temperature, global

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The through-cloud capabilities of microwave radiometers provide a valuable picture of global sea surface temperature (SST). To utilize this, scientists at Remote...

  5. Assimilation of GRACE Terrestrial Water Storage into a Land Surface Model: Evaluation 1 and Potential Value for Drought Monitoring in Western and Central Europe

    Science.gov (United States)

    Li, Bailing; Rodell, Matthew; Zaitchik, Benjamin F.; Reichle, Rolf H.; Koster, Randal D.; van Dam, Tonie M.

    2012-01-01

    A land surface model s ability to simulate states (e.g., soil moisture) and fluxes (e.g., runoff) is limited by uncertainties in meteorological forcing and parameter inputs as well as inadequacies in model physics. In this study, anomalies of terrestrial water storage (TWS) observed by the Gravity Recovery and Climate Experiment (GRACE) satellite mission were assimilated into the NASA Catchment land surface model in western and central Europe for a 7-year period, using a previously developed ensemble Kalman smoother. GRACE data assimilation led to improved runoff correlations with gauge data in 17 out of 18 hydrological basins, even in basins smaller than the effective resolution of GRACE. Improvements in root zone soil moisture were less conclusive, partly due to the shortness of the in situ data record. In addition to improving temporal correlations, GRACE data assimilation also reduced increasing trends in simulated monthly TWS and runoff associated with increasing rates of precipitation. GRACE assimilated root zone soil moisture and TWS fields exhibited significant changes in their dryness rankings relative to those without data assimilation, suggesting that GRACE data assimilation could have a substantial impact on drought monitoring. Signals of drought in GRACE TWS correlated well with MODIS Normalized Difference Vegetation Index (NDVI) data in most areas. Although they detected the same droughts during warm seasons, drought signatures in GRACE derived TWS exhibited greater persistence than those in NDVI throughout all seasons, in part due to limitations associated with the seasonality of vegetation.

  6. Urban aerosol effects on surface insolation and surface temperature

    Science.gov (United States)

    Jin, M.; Burian, S. J.; Remer, L. A.; Shepherd, M. J.

    2007-12-01

    Urban aerosol particulates may play a fundamental role in urban microclimates and city-generated mesoscale circulations via its effects on energy balance of the surface. Key questions that need to be addressed include: (1) How do these particles affect the amount of solar energy reaching the surface and resulting surface temperature? (2) Is the effect the same in all cities? and (3) How does it vary from city to city? Using NASA AERONET in-situ observations, a radiative transfer model, and a regional climate mode (MM5), we assess aerosol effects on surface insolation and surf ace temperature for dense urban-polluted regions. Two big cities, one in a developing country (Beijing, P.R. China) and another in developed country (New York City, USA), are selected for inter-comparison. The study reveals that aerosol effects on surface temperature depends largely on aerosols' optical and chemical properties as well as atmosphere and land surface conditions, such as humidity and land cover. Therefore, the actual magnitudes of aerosol effects differ from city to city. Aerosol measurements from AERONET show both average and extreme cases for aerosol impacts on surface insolation. In general, aerosols reduce surface insolation by 30Wm-2. Nevertheless, in extreme cases, such reduction can exceed 100 Wm-2. Consequently, this reduces surface skin temperature 2-10C in an urban environment.

  7. Modeling of global surface air temperature

    Science.gov (United States)

    Gusakova, M. A.; Karlin, L. N.

    2012-04-01

    A model to assess a number of factors, such as total solar irradiance, albedo, greenhouse gases and water vapor, affecting climate change has been developed on the basis of Earth's radiation balance principle. To develop the model solar energy transformation in the atmosphere was investigated. It's a common knowledge, that part of the incoming radiation is reflected into space from the atmosphere, land and water surfaces, and another part is absorbed by the Earth's surface. Some part of outdoing terrestrial radiation is retained in the atmosphere by greenhouse gases (carbon dioxide, methane, nitrous oxide) and water vapor. Making use of the regression analysis a correlation between concentration of greenhouse gases, water vapor and global surface air temperature was obtained which, it is turn, made it possible to develop the proposed model. The model showed that even smallest fluctuations of total solar irradiance intensify both positive and negative feedback which give rise to considerable changes in global surface air temperature. The model was used both to reconstruct the global surface air temperature for the 1981-2005 period and to predict global surface air temperature until 2030. The reconstructions of global surface air temperature for 1981-2005 showed the models validity. The model makes it possible to assess contribution of the factors listed above in climate change.

  8. Impacts of AMSU-A/MHS and IASI data assimilation on temperature and humidity forecasts with GSI/WRF over the Western United States

    Directory of Open Access Journals (Sweden)

    Y. Bao

    2015-06-01

    Full Text Available Using NOAA's Gridpoint Statistical Interpolation (GSI data assimilation system and NCAR's Advanced Research WRF (ARW-WRF regional model, six experiments are designed by (1 control experiment (CTRL and five data assimilation (DA experiments with different data sets including (2 conventional data only (CON, (3 microwave data (AMSU-A + MHS only (MW, (4 infrared data (IASI only (IR, (5 combination of microwave and infrared data (MWIR, (6 combination of conventional, microwave and infrared observation data (ALL. One month experiments in July 2012 and impacts of the DA on temperature and moisture forecasts at the surface and four vertical layers, which over the western United States have been investigated. The four layers include lower troposphere (LT from 800 to 1000 hPa}, middle troposphere (MT from 400 to 800 hPa, upper troposphere (UT from 200 to 400 hPa and lower stratosphere (LS from 50 to 200 hPa. The results show that the regional GSI/WRF system is underestimating the observed temperature in the LT and overestimating in the UT and LS. The MW DA reduced the forecast bias from the MT to the LS within 30 h forecasts, and the CON DA kept a smaller forecast bias in the LT for 2-day forecasts. The largest RMS error is observed in the LT and at the surface (SFC. Compared to the CTRL, the MW DA made the most positive contribution in the UT and LS, and the CON DA mainly improved the temperature forecasts at the SFC. However, the IR DA made a negative contribution in the LT. Most of the observed humidity in the different vertical layers is overestimated in the humidity forecasts except in the UT. The smallest bias in the humidity forecast occurred at the SFC and UT. The DA experiments apparently reduced the bias from the LT to UT, especially for the IR DA experiment, but the RMS errors are not reduced in the humidity forecasts. Compared to the CTRL, the IR DA experiment has a larger RMS error in the moisture forecast although the smallest bias is found

  9. Snow Radiance Assimilation Studies

    Science.gov (United States)

    Kim, E. J.; Durand, M. T.; Toure, A.; Margulis, S. A.; Goita, K.; Royer, A.; Lu, H.

    2009-12-01

    Passive microwave-based retrievals of terrestrial snow parameters from satellite observations form a 30-year global record which will continue for the forseeable future. So far, these snow retrievals have been generated primarily by regression-based empirical “inversion” methods based on snapshots in time, and are limited to footprints around 25 km in diameter. Assimilation of microwave radiances into physical land surface models may be used to create a retrieval framework that is inherently self-consistent with respect to model physics as well as a more physically-based approach vs. legacy retrieval/inversion methods. This radiance assimilation approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success, and represents one motivation for our work. A radiance assimilation scheme for snow requires a snowpack land surface model (LSM) coupled to a radiative transfer model (RTM). In previous local-scale studies, Durand, Kim, & Margulis (2008) explored the requirements on LSM model fidelity (i.e., snowpack state information) required in order for the RTM to produce brightness temperatures suitable for radiance assimilation purposes at a local scale, using the well-known Microwave Emission Model for Layered Snowpacks (MEMLS) as the RTM and a combination of Simple SIB (SSiB) and Snow Atmosphere (SAST) as the LSM. They also demonstrated improvement of simulated snow depth through the use of an ensemble Kalman filter scheme at this local scale (2009). This modeling framework reflects another motivation—namely, possibilities for downscaling. Our focus at this stage has been at the local scale where high-quality ground truth data is available in order to evaluate radiance assimilation under a “best case scenario.” The quantitative results then form a benchmark for future assessment of effects such as sparse forcing data, upscaling/downscaling, forest attenuation, and model details. Field data from

  10. Application of altimetry data assimilation on mesoscale eddies simulation

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Mesoscale eddy plays an important role in the ocean circulation. In order to improve the simulation accuracy of the mesoscale eddies, a three-dimensional variation (3DVAR) data assimilation system called Ocean Variational Analysis System (OVALS) is coupled with a POM model to simulate the mesoscale eddies in the Northwest Pacific Ocean. In this system, the sea surface height anomaly (SSHA) data by satellite altimeters are assimilated and translated into pseudo temperature and salinity (T-S) profile data. Then, these profile data are taken as observation data to be assimilated again and produce the three-dimensional analysis T-S field. According to the characteristics of mesoscale eddy, the most appropriate assimilation parameters are set up and testified in this system. A ten years mesoscale eddies simulation and comparison experiment is made, which includes two schemes: assimilation and non-assimilation. The results of comparison between two schemes and the observation show that the simulation accuracy of the assimilation scheme is much better than that of non-assimilation, which verified that the altimetry data assimilation method can improve the simulation accuracy of the mesoscale dramatically and indicates that it is possible to use this system on the forecast of mesoscale eddies in the future.

  11. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  12. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 2 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  13. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 3 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Land Surface Temperature Databank contains monthly timescale mean, maximum, and minimum temperature for approximately 40,000 stations globally. It was...

  14. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Daily

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  15. International Surface Temperature Initiative (ISTI) Global Land Surface Temperature Databank - Stage 1 Monthly

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global land surface temperature databank contains monthly timescale mean, max, and min temperature for approximately 40,000 stations globally. It was developed...

  16. Calibration of surface temperature on rocky exoplanets

    Science.gov (United States)

    Kashyap Jagadeesh, Madhu

    2016-07-01

    Study of exoplanets and the search for life elsewhere has been a very fascinating area in recent years. Presently, lots of efforts have been channelled in this direction in the form of space exploration and the ultimate search for the habitable planet. One of the parametric methods to analyse the data available from the missions such as Kepler, CoRoT, etc, is the Earth Similarity Index (ESI), defined as a number between zero (no similarity) and one (identical to Earth), introduced to assess the Earth likeness of exoplanets. A multi-parameter ESI scale depends on the radius, density, escape velocity and surface temperature of exoplanets. Our objective is to establish how exactly the individual parameters, entering the interior ESI and surface ESI, are contributing to the global ESI, using the graphical analysis. Presently, the surface temperature estimates are following a correction factor of 30 K, based on the Earth's green-house effect. The main objective of this work in calculations of the global ESI using the HabCat data is to introduce a new method to better estimate the surface temperature of exoplanets, from theoretical formula with fixed albedo factor and emissivity (Earth values). From the graphical analysis of the known data for the Solar System objects, we established the calibration relation between surface and equilibrium temperatures for the Solar System objects. Using extrapolation we found that the power function is the closest description of the trend to attain surface temperature. From this we conclude that the correction term becomes very effective way to calculate the accurate value of the surface temperature, for further analysis with our graphical methodology.

  17. Towards a satellite driven land surface model using SURFEX modelling platform Offline Data Assimilation: an assessment of the method over Europe and the Mediterranean basin

    Science.gov (United States)

    Albergel, Clément; Munier, Simon; Leroux, Delphine; Fairbairn, David; Dorigo, Wouter; Decharme, Bertrand; Calvet, Jean-Christophe

    2017-04-01

    Modelling platforms including Land Surface Models (LSMs), forced by gridded atmospheric variables and coupled to river routing models are necessary to increase our understanding of the terrestrial water cycle. These LSMs need to simulate biogeophysical variables like Surface and Root Zone Soil Moisture (SSM, RZSM), Leaf Area Index (LAI) in a way that is fully consistent with the representation of surface/energy fluxes and river discharge simulations. Global SSM and LAI products are now operationally available from spaceborne instruments and they can be used to constrain LSMs through Data Assimilation (DA) techniques. In this study, an offline data assimilation system implemented in Météo-France's modelling platform (SURFEX) is tested over Europe and the Mediterranean basin to increase prediction accuracy for land surface variables. The resulting Land Data Assimilation System (LDAS) makes use of a simplified Extended Kalman Filter (SEKF). It is able to ingests information from satellite derived (i) SSM from the latest version of the ESA Climate Change Initiative as well as (ii) LAI from the Copernicus GLS project to constrain the multilayer, CO2-responsive version of the Interactions Between Soil, Biosphere, and Atmosphere model (ISBA) coupled with Météo-France's version of the Total Runoff Integrating Pathways continental hydrological system (ISBA-CTRIP). ERA-Interim observations based atmospheric forcing with precipitations corrected from Global Precipitation Climatology Centre observations (GPCC) is used to force ISBA-CTRIP at a resolution of 0.5 degree over 2000-2015. The model sensitivity to the assimilated observations is presented and a set of statistical diagnostics used to evaluate the impact of assimilating SSM and LAI on different model biogeophysical variables are provided. It is demonstrated that the assimilation scheme works effectively. The SEKF is able to extract useful information from the data signal at the grid scale and distribute the RZSM

  18. Integrative inversion of land surface component temperature

    Institute of Scientific and Technical Information of China (English)

    FAN Wenjie; XU Xiru

    2005-01-01

    In this paper, the row winter wheat was selected as the example to study the component temperature inversion method of land surface target in detail. The result showed that the structural pattern of row crop can affect the inversion precision of component temperature evidently. Choosing appropriate structural pattern of row crop can improve the inversion precision significantly. The iterative method combining inverse matrix was a stable method that was fit for inversing component temperature of land surface target. The result of simulation and field experiment showed that the integrative method could remarkably improve the inversion accuracy of the lighted soil surface temperature and the top layer canopy temperature, and enhance inversion stability of components temperature. Just two parameters were sufficient for accurate atmospheric correction of multi-angle and multi-spectral thermal infrared data: atmospheric transmittance and the atmospheric upwelling radiance. If the atmospheric parameters and component temperature can be inversed synchronously, the really and truly accurate atmospheric correction can be achieved. The validation using ATSRII data showed that the method was useful.

  19. SST data assimilation experiments using an adaptive variational method

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An adaptive variational data assimilation method is proposed by Zhu and Kamachi[1]. This method can adaptively adjust the model state without knowing explicitly the model error covariance matrix. The method enables very flexible ways to form some reduced order problems. A proper reduced order problem not only reduces computational burden but also leads to corrections that are more consistent with the model dynamics that trends to produce better forecast. These features make the adaptive variational method a good candidate for SST data assimilation because the model error of an ocean model is usually difficult to estimate. We applied this method to an SST data assimilation problem using the LOTUS data sets and an ocean mixed layer model (Mellor-Yamada level 2.5). Results of assimilation experiments showed good skill of improvement subsurface temperatures by assimilating surface observation alone.

  20. Ocean Data Assimilation for Coupled Models

    Science.gov (United States)

    2016-06-07

    MODAS) developed at NRL Stennis, CODA now assimilates altimeter sea surface height ( SSH ) data, in the form of MODAS synthetic temperature and...The residual errors are time and space dependent and residual errors are at a minimum where the relationship between SSH , SST and temperature at depth...is well-defined (e.g. western boundary currents). In a CODA analysis, residual errors are combined with errors in the SST and SSH predictor fields to

  1. A snow extent time series assimilation using MODIS images and temperature data, case study Koohrang, Iran

    Science.gov (United States)

    Abdollahi, K.; Batelaan, O.

    2012-04-01

    A unique advantage of satellite data is the possibility for delineation of snow line and calculation of snow cover area. Recent availability of remote sensing data offers promise for better performance of hydrological models, which contain a snow component. The near-daily coverage of Moderate Resolution Imaging Spectrometer (MODIS) data and its moderate resolution provide a powerful capability for time series analysis of snow cover area. However, because of several reasons like cloud cover, technical problems, etc., images are not available or usable. This paper suggests a regional solution to fill the gap of missing data for purpose of snow cover assessment. In this study 27 images of MODIS from NASA have been used to calculate basin scale snow cover area by applying NDSI technique. Also a temperature dataset was collected from the Koohrang station, which was measured by the Iranian meteorological organization for the period 2004-2008. The elevation of the Koohrang station is 2285 m above sea level and geographically it is located at latitude 32 26' and longitude 50 07'. The study considered snow cover derived from satellite imagery as dependent variable and temperature as independent variable. To find a relationship between snow extent and temperature we used the CURVEEXPERT 1.4 package. This program uses the Levenberg-Marquardt algorithm to solve nonlinear regressions by combination of steepest-descent method and a Taylor series technique. Our methodology is applied each time when snow extent is not available and it estimates snow extend based on the remaining data. A wide range of built in models were tested for this purpose but finally a Logistic, Exponential, Richards, Gompertz, Linear Fit and Exponential model were adopted because of high correlation relationship and low variance.

  2. Temperature limit values for gripping cold surfaces

    NARCIS (Netherlands)

    Malchaire, J.; Geng, Q.; Den Hartog, E.; Havenith, G.; Holmer, I.; Piette, A.; Powell, S.L.; Rintamäki, H.; Rissanen, S.

    2002-01-01

    Objectives. At the request of the European Commission and in the framework of the European Machinery Directive, research was conducted jointly in five different laboratories to develop specifications for surface temperature limit values for the gripping and handling of cold items. Methods. Four

  3. Temperature limit values for gripping cold surfaces

    NARCIS (Netherlands)

    Malchaire, J.; Geng, Q.; Den Hartog, E.; Havenith, G.; Holmer, I.; Piette, A.; Powell, S.L.; Rintamäki, H.; Rissanen, S.

    2002-01-01

    Objectives. At the request of the European Commission and in the framework of the European Machinery Directive, research was conducted jointly in five different laboratories to develop specifications for surface temperature limit values for the gripping and handling of cold items. Methods. Four hund

  4. Surface temperature excess in heterogeneous catalysis

    NARCIS (Netherlands)

    Zhu, L.

    2005-01-01

    In this dissertation we study the surface temperature excess in heterogeneous catalysis. For heterogeneous reactions, such as gas-solid catalytic reactions, the reactions take place at the interfaces between the two phases: the gas and the solid catalyst. Large amount of reaction heats are released

  5. Surface temperature excess in heterogeneous catalysis

    NARCIS (Netherlands)

    Zhu, L.

    2005-01-01

    In this dissertation we study the surface temperature excess in heterogeneous catalysis. For heterogeneous reactions, such as gas-solid catalytic reactions, the reactions take place at the interfaces between the two phases: the gas and the solid catalyst. Large amount of reaction heats are released

  6. Trend patterns in global sea surface temperature

    DEFF Research Database (Denmark)

    Barbosa, S.M.; Andersen, Ole Baltazar

    2009-01-01

    Isolating long-term trend in sea surface temperature (SST) from El Nino southern oscillation (ENSO) variability is fundamental for climate studies. In the present study, trend-empirical orthogonal function (EOF) analysis, a robust space-time method for extracting trend patterns, is applied...

  7. DISAGGREGATION OF GOES LAND SURFACE TEMPERATURES USING SURFACE EMISSIVITY

    Science.gov (United States)

    Accurate temporal and spatial estimation of land surface temperatures (LST) is important for modeling the hydrological cycle at field to global scales because LSTs can improve estimates of soil moisture and evapotranspiration. Using remote sensing satellites, accurate LSTs could be routine, but unfo...

  8. Variational assimilation of Lagrangian trajectories in the Mediterranean ocean Forecasting System

    Directory of Open Access Journals (Sweden)

    J. A. U. Nilsson

    2011-12-01

    Full Text Available A novel method for three-dimensional variational assimilation of Lagrangian data with a primitive-equation ocean model is proposed. The assimilation scheme was implemented in the Mediterranean ocean Forecasting System and evaluated for a 4-month period. Four experiments were designed to assess the impact of trajectory assimilation on the model output, i.e. the sea-surface height, velocity, temperature and salinity fields. It was found from the drifter and Argo trajectory assimilation experiment that the forecast skill of surface-drifter trajectories improved by 15 %, that of intermediate-depth float trajectories by 20 %, and moreover, the forecasted sea-surface height fields improved locally by 5 % compared to satellite data, while the quality of the temperature and salinity fields remained at previous levels. In conclusion, the addition of Lagrangian trajectory assimilation proved to reduce the uncertainties in the model fields, thus yielding a higher accuracy of the ocean forecasts.

  9. Surface defects and temperature on atomic friction

    Energy Technology Data Exchange (ETDEWEB)

    Fajardo, O Y; Mazo, J J, E-mail: yovany@unizar.es [Departamento de Fisica de la Materia Condensada and Instituto de Ciencia de Materiales de Aragon, CSIC-Universidad de Zaragoza, 50009 Zaragoza (Spain)

    2011-09-07

    We present a theoretical study of the effect of surface defects on atomic friction in the stick-slip dynamical regime of a minimalistic model. We focus on how the presence of defects and temperature change the average properties of the system. We have identified two main mechanisms which modify the mean friction force of the system when defects are considered. As expected, defects change the potential profile locally and thus affect the friction force. But the presence of defects also changes the probability distribution function of the tip slip length and thus the mean friction force. We corroborated both effects for different values of temperature, external load, dragging velocity and damping. We also show a comparison of the effects of surface defects and surface disorder on the dynamics of the system. (paper)

  10. Surface temperature distribution in broiler houses

    Directory of Open Access Journals (Sweden)

    MS Baracho

    2011-09-01

    Full Text Available In the Brazilian meat production scenario broiler production is the most dynamic segment. Despite of the knowledge generated in the poultry production chain, there are still important gaps on Brazilian rearing conditions as housing is different from other countries. This research study aimed at analyzing the variation in bird skin surface as function of heat distribution inside broiler houses. A broiler house was virtually divided into nine sectors and measurements were made during the first four weeks of the grow-out in a commercial broiler farm in the region of Rio Claro, São Paulo, Brazil. Rearing ambient temperature and relative humidity, as well as light intensity and air velocity, were recorded in the geometric center of each virtual sector to evaluate the homogeneity of these parameters. Broiler surface temperatures were recorded using infrared thermography. Differences both in surface temperature (Ts and dry bulb temperature (DBT were significant (p<0.05 as a function of week of rearing. Ts was different between the first and fourth weeks (p<0.05 in both flocks. Results showed important variations in rearing environment parameters (temperature and relative humidity and in skin surface temperature as a function of week and house sector. Air velocity data were outside the limits in the first and third weeks in several sectors. Average light intensity values presented low variation relative to week and house sector. The obtained values were outside the recommended ranges, indicating that broilers suffered thermal distress. This study points out the need to record rearing environment data in order to provide better environmental control during broiler grow-out.

  11. Land-surface parameter optimisation using data assimilation techniques: the adJULES system V1.0

    Science.gov (United States)

    Raoult, Nina M.; Jupp, Tim E.; Cox, Peter M.; Luke, Catherine M.

    2016-08-01

    Land-surface models (LSMs) are crucial components of the Earth system models (ESMs) that are used to make coupled climate-carbon cycle projections for the 21st century. The Joint UK Land Environment Simulator (JULES) is the land-surface model used in the climate and weather forecast models of the UK Met Office. JULES is also extensively used offline as a land-surface impacts tool, forced with climatologies into the future. In this study, JULES is automatically differentiated with respect to JULES parameters using commercial software from FastOpt, resulting in an analytical gradient, or adjoint, of the model. Using this adjoint, the adJULES parameter estimation system has been developed to search for locally optimum parameters by calibrating against observations. This paper describes adJULES in a data assimilation framework and demonstrates its ability to improve the model-data fit using eddy-covariance measurements of gross primary production (GPP) and latent heat (LE) fluxes. adJULES also has the ability to calibrate over multiple sites simultaneously. This feature is used to define new optimised parameter values for the five plant functional types (PFTs) in JULES. The optimised PFT-specific parameters improve the performance of JULES at over 85 % of the sites used in the study, at both the calibration and evaluation stages. The new improved parameters for JULES are presented along with the associated uncertainties for each parameter.

  12. Geomagnetic effects on the average surface temperature

    Science.gov (United States)

    Ballatore, P.

    Several results have previously shown as the solar activity can be related to the cloudiness and the surface solar radiation intensity (Svensmark and Friis-Christensen, J. Atmos. Sol. Terr. Phys., 59, 1225, 1997; Veretenenkoand Pudovkin, J. Atmos. Sol. Terr. Phys., 61, 521, 1999). Here, the possible relationships between the averaged surface temperature and the solar wind parameters or geomagnetic activity indices are investigated. The temperature data used are the monthly SST maps (generated at RAL and available from the related ESRIN/ESA database) that represent the averaged surface temperature with a spatial resolution of 0.5°x0.5° and cover the entire globe. The interplanetary data and the geomagnetic data are from the USA National Space Science Data Center. The time interval considered is 1995-2000. Specifically, possible associations and/or correlations of the average temperature with the interplanetary magnetic field Bz component and with the Kp index are considered and differentiated taking into account separate geographic and geomagnetic planetary regions.

  13. Three-dimensional soil moisture profile retrieval by assimilation of near-surface measurements: Simplified Kalman filter covariance forecasting and field application

    Science.gov (United States)

    Walker, Jeffrey P.; Willgoose, Garry R.; Kalma, Jetse D.

    2002-12-01

    The Kalman filter data assimilation technique is applied to a distributed three-dimensional soil moisture model for retrieval of the soil moisture profile in a 6 ha catchment using near-surface soil moisture measurements. A simplified Kalman filter covariance forecasting methodology is developed based on forecasting of the state correlations and imposed state variances. This covariance forecasting technique, termed the modified Kalman filter, was then used in a 1 month three-dimensional field application. Two updating scenarios were tested: (1) updating every 2 to 3 days and (2) a single update. The data used were from the Nerrigundah field site, near Newcastle, Australia. This study demonstrates the feasibility of data assimilation in a quasi three-dimensional distributed soil moisture model, provided simplified covariance forecasting techniques are used. It also identifies that (1) the soil moisture profile cannot be retrieved from near-surface soil moisture measurements when the near-surface and deep soil layers become decoupled, such as during extreme drying events; (2) if simulation of the soil moisture profile is already good, the assimilation can result in a slight degradation, but if the simulation is poor, assimilation can yield a significant improvement; (3) soil moisture profile retrieval results are independent of initial conditions; and (4) the required update frequency is a function of the errors in model physics and forcing data.

  14. Ensemble data assimilation in the Whole Atmosphere Community Climate Model

    Science.gov (United States)

    Pedatella, N. M.; Raeder, K.; Anderson, J. L.; Liu, H.-L.

    2014-08-01

    We present results pertaining to the assimilation of real lower, middle, and upper atmosphere observations in the Whole Atmosphere Community Climate Model (WACCM) using the Data Assimilation Research Testbed (DART) ensemble adjustment Kalman filter. The ability to assimilate lower atmosphere observations of aircraft and radiosonde temperature and winds, satellite drift winds, and Constellation Observing System for Meteorology, Ionosphere, and Climate refractivity along with middle/upper atmosphere temperature observations from SABER and Aura MLS is demonstrated. The WACCM+DART data assimilation system is shown to be able to reproduce the salient features, and variability, of the troposphere present in the National Centers for Environmental Prediction/National Center for Atmospheric Research Re-Analysis. In the mesosphere, the fit of WACCM+DART to observations is found to be slightly worse when only lower atmosphere observations are assimilated compared to a control experiment that is reflective of the model climatological variability. This differs from previous results which found that assimilation of lower atmosphere observations improves the fit to mesospheric observations. This discrepancy is attributed to the fact that due to the gravity wave drag parameterizations, the model climatology differs significantly from the observations in the mesosphere, and this is not corrected by the assimilation of lower atmosphere observations. The fit of WACCM+DART to mesospheric observations is, however, significantly improved compared to the control experiment when middle/upper atmosphere observations are assimilated. We find that assimilating SABER observations reduces the root-mean-square error and bias of WACCM+DART relative to the independent Aura MLS observations by ˜50%, demonstrating that assimilation of middle/upper atmosphere observations is essential for accurate specification of the mesosphere and lower thermosphere region in WACCM+DART. Last, we demonstrate that

  15. Development of a Chinese land data assimilation system: its progress and prospects

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The objective of land data assimilation is to merge multi-source observations into the dynamics of land surface model for improving the estimation of land surface states. We have developed a land data assimilation system for China's land territory. In this system, the Common Land Model and Simple Biosphere Model 2 are used to simulate land surface processes. The radiative transfer models of thawed and frozen soil, snow, lake, and vegetation are used as observation operators to transfer model predictions into estimated brightness temperatures. A Monte-Carlo based sequential filter, the ensemble Kalman filter, is implemented as data assimilation method to integrate modeling and observation. The system is capable of assimilating passive microwave remotely sensed data such as special sensor microwave/imager (SSM/I), TRMM microwave imager (TMI), and advanced microwave scanning radiometer enhanced for EOS (AMSRE) and the conventional in situ measurements of soil and snow. A spatiotemporally consistent assimilated dataset for soil moisture, soil temperature, snow and frozen soil, with a spatial resolution of 0.25 degree and temporal resolution of one hour, has been produced. This paper introduces the development of Chinese land data assimilation system and the progress made on data assimilation algorithms, land surface modeling, microwave remote sensing of land surface hydrological variables, and the preparation of atmospheric forcing data. The distinct characteristics and challenges of developing land data assimilation system and the perspectives for future development are also discussed .

  16. Combined effect of temperature and food concentration on the filtration and clarification rates and assimilation efficiency of Atrina tuberculosa Sowerby, 1835 (Mollusca: Bivalvia) under laboratory conditions

    OpenAIRE

    2013-01-01

    In Mexico, Atrina tuberculosa and other bivalve mollusks of commercial importance are intensively exploited, resulting in a drastic decline in their natural populations. This makes the ecophysiological studies of our native mollusks very important. The filtration and clarification rates, and the assimilation efficiency of Atrina tuberculosa at three temperatures (17, 22.5 and 28°C) and three microalgae concentrations (20,000, 40,000 and 60,000 cell•mL-1) were evaluated under laboratory ...

  17. Sensitivity of simulated terrestrial carbon assimilation and canopy transpiration to different stomatal conductance and carbon assimilation schemes

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Haishan [Nanjing University of Information Science and Technology, Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing (China); Georgia Institute of Technology, School of Earth and Atmospheric Sciences, Atlanta, GA (United States); Dickinson, Robert E. [Georgia Institute of Technology, School of Earth and Atmospheric Sciences, Atlanta, GA (United States); The University of Texas at Austin, Department of Geological Sciences, Austin, TX (United States); Dai, Yongjiu [Beijing Normal University, State Key Laboratory of Earth Surface Processes and Resource Ecology, School of Global Change and Earth System Science, Beijing (China); Zhou, Liming [Georgia Institute of Technology, School of Earth and Atmospheric Sciences, Atlanta, GA (United States)

    2011-03-15

    Accurate simulations of terrestrial carbon assimilation and canopy transpiration are needed for both climate modeling and vegetation dynamics. Coupled stomatal conductance and carbon assimilation (A - g{sub s}) models have been widely used as part of land surface parameterizations in climate models to describe the biogeophysical and biogeochemical roles of terrestrial vegetation. Differences in various A - g{sub s} schemes produce substantial differences in the estimation of carbon assimilation and canopy transpiration, as well as in other land-atmosphere fluxes. The terrestrial carbon assimilation and canopy transpiration simulated by two different representative A - g{sub s} schemes, a simple A-g{sub s} scheme adopted from the treatments of the NCAR model (Scheme I) and a two-big-leaf A - g{sub s} scheme newly developed by Dai et al. (J Clim 17:2281-2299, 2004) (Scheme II), are compared via some sensitivity experiments to investigate impacts of different A - g{sub s} schemes on the simulations. Major differences are found in the estimate of canopy carbon assimilation rate, canopy conductance and canopy transpiration between the two schemes, primarily due to differences in (a) functional forms used to estimate parameters for carbon assimilation sub-models, (b) co-limitation methods used to estimate carbon assimilation rate from the three limiting rates, and (c) leaf-to-canopy scaling schemes. On the whole, the differences in the scaling approach are the largest contributor to the simulation discrepancies, but the different methods of co-limitation of assimilation rate also impact the results. Except for a few biomes, the residual effects caused by the different parameter estimations in assimilation sub-models are relatively small. It is also noted that the two-leaf temperature scheme produces distinctly different sunlit and shaded leaf temperatures but has negligible impacts on the simulation of the carbon assimilation. (orig.)

  18. MODIS Surface Temperatures for Cryosphere Studies (Invited)

    Science.gov (United States)

    Hall, D. K.; Comiso, J. C.; DiGirolamo, N. E.; Shuman, C. A.; Riggs, G. A.

    2013-12-01

    We have used Moderate-resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST) and ice-surface temperature (IST) products for several applications in studies of the cryosphere. A climate-quality climate data record (CDR) of the IST of the Greenland ice sheet has been developed and was one of the data sources used to monitor the extreme melt event covering nearly the entire Greenland ice sheet on 11 - 12 July 2012. The IST CDR is available online for users to employ in models, and to study temperature distributions and melt trends on the ice sheet. We continue to assess accuracy of the IST product through comparative analysis with air temperature data from the NOAA Logan temperature sensor at Summit Station, Greenland. We find a small offset between the air temperature and the IST with the IST being slightly lower which is consistent with findings of other studies. The LST data product has been applied in studies of snow melt in regions where snow is a significant water resource. We have used LST data in seasonally snow-covered areas such as the Wind River Range, Wyoming, to monitor the relationship between LST and seasonal streamflow. A close association between a sudden and sustained increase in LST and complete snowmelt, and between melt-season maximum LST and maximum daily streamflow has been documented. Use of LST and MODIS snow-cover and products in hydrological models increases the accuracy of the modeled prediction of runoff. The IST and LST products have also been applied to study of sea ice, e.g. extent and concentration, and lake ice, such as determining ice-out dates, and these efforts will also be described.

  19. The SMAP level 4 surface and root zone soil moisture data assimilation product

    Science.gov (United States)

    The NASA Soil Moisture Active Passive (SMAP) mission is scheduled for launch in January 2015 and will provide L-band radar and radiometer observations that are sensitive to surface soil moisture (in the top few centimeters of the soil column). For several of the key applications targeted by SMAP, ho...

  20. Role of subsurface physics in the assimilation of surface soil moisture observations

    Science.gov (United States)

    Soil moisture controls the exchange of water and energy between the land surface and the atmosphere and exhibits memory that may be useful for climate prediction at monthly time scales. Though spatially distributed observations of soil moisture are increasingly becoming available from remotely sense...

  1. Ocean Data Assimilation in the Gulf of Mexico Using 3D VAR Approach - Preliminary Results

    Science.gov (United States)

    Paturi, S.; Garraffo, Z. D.; Cummings, J. A.; Rivin, I.; Mehra, A.; Kim, H. C.

    2016-12-01

    Approaches to ocean data assimilation vary widely, both in terms of the sophistication of the method and the observations assimilated.A three-dimensional variational (3DVAR) data assimilation system, part of the Navy Coupled Ocean Data Assimilation (NCODA) system developed at Navy Research Laboratory (NRL), is used for assimilating Sea Surface Temperature (SST) and Sea Surface Height (SSH) in the Gulf of Mexico (GoM). The NCODA 3DVAR produces simultaneous analyses of temperature, salinity, and vector velocity and uses all possible sources of ocean data observations.The Hybrid Coordinate Ocean Model (HYCOM) is used for the simulations, at 1/25o grid resolution for July 2011 period. After successful implementation of NCODA 3DVAR in the GoM, the system will be extended to the global ocean with the intent of making it operational.

  2. Theoretical analyses and numerical experiments of variational assimilation for one-dimensional ocean temperature model with techniques in inverse problems

    Institute of Scientific and Technical Information of China (English)

    HUANG; Sixun; HAN; Wei; WU; Rongsheng

    2004-01-01

    In the present work, the data assimilation problem in meteorology and physical oceanography is re-examined using the variational optimal control approaches in combination with regularization techniques in inverse problem. Here the estimations of the initial condition,boundary condition and model parameters are performed simultaneously in the framework of variational data assimilation. To overcome the difficulty of ill-posedness, especially for the model parameters distributed in space and time, an additional term is added into the cost functional as a stabilized functional. Numerical experiments show that even with noisy observations the initial conditions and model parameters are recovered to an acceptable degree of accuracy.

  3. The international surface temperature initiative's global land surface databank

    Science.gov (United States)

    Lawrimore, J. H.; Rennie, J.; Gambi de Almeida, W.; Christy, J.; Flannery, M.; Gleason, B.; Klein-Tank, A.; Mhanda, A.; Ishihara, K.; Lister, D.; Menne, M. J.; Razuvaev, V.; Renom, M.; Rusticucci, M.; Tandy, J.; Thorne, P. W.; Worley, S.

    2013-09-01

    The International Surface Temperature Initiative (ISTI) consists of an end-to-end process for land surface air temperature analyses. The foundation is the establishment of a global land surface Databank. This builds upon the groundbreaking efforts of scientists in the 1980s and 1990s. While using many of their principles, a primary aim is to improve aspects including data provenance, version control, openness and transparency, temporal and spatial coverage, and improved methods for merging disparate sources. The initial focus is on daily and monthly timescales. A Databank Working Group is focused on establishing Stage-0 (original observation forms) through Stage-3 data (merged dataset without quality control). More than 35 sources of data have already been added and efforts have now turned to development of the initial version of the merged dataset. Methods have been established for ensuring to the extent possible the provenance of all data from the point of observation through all intermediate steps to final archive and access. Databank submission procedures were designed to make the process of contributing data as easy as possible. All data are provided openly and without charge. We encourage the use of these data and feedback from interested users.

  4. Low Temperature Surface Carburization of Stainless Steels

    Energy Technology Data Exchange (ETDEWEB)

    Collins, Sunniva R; Heuer, Arthur H; Sikka, Vinod K

    2007-12-07

    Low-temperature colossal supersaturation (LTCSS) is a novel surface hardening method for carburization of austenitic stainless steels (SS) without the precipitation of carbides. The formation of carbides is kinetically suppressed, enabling extremely high or colossal carbon supersaturation. As a result, surface carbon concentrations in excess of 12 at. % are routinely achieved. This treatment increases the surface hardness by a factor of four to five, improving resistance to wear, corrosion, and fatigue, with significant retained ductility. LTCSS is a diffusional surface hardening process that provides a uniform and conformal hardened gradient surface with no risk of delamination or peeling. The treatment retains the austenitic phase and is completely non-magnetic. In addition, because parts are treated at low temperature, they do not distort or change dimensions. During this treatment, carbon diffusion proceeds into the metal at temperatures that constrain substitutional diffusion or mobility between the metal alloy elements. Though immobilized and unable to assemble to form carbides, chromium and similar alloying elements nonetheless draw enormous amounts of carbon into their interstitial spaces. The carbon in the interstitial spaces of the alloy crystals makes the surface harder than ever achieved before by more conventional heat treating or diffusion process. The carbon solid solution manifests a Vickers hardness often exceeding 1000 HV (equivalent to 70 HRC). This project objective was to extend the LTCSS treatment to other austenitic alloys, and to quantify improvements in fatigue, corrosion, and wear resistance. Highlights from the research include the following: • Extension of the applicability of the LTCSS process to a broad range of austenitic and duplex grades of steels • Demonstration of LTCSS ability for a variety of different component shapes and sizes • Detailed microstructural characterization of LTCSS-treated samples of 316L and other alloys

  5. The surface temperature of free evaporating drops

    Science.gov (United States)

    Borodulin, V. Y.; Letushko, V. N.; Nizovtsev, M. I.; Sterlyagov, A. N.

    2016-10-01

    Complex experimental and theoretical investigation of heat and mass transfer processes was performed at evaporation of free liquid drops. For theoretical calculation the emission-diffusion model was proposed. This allowed taking into account the characteristics of evaporation of small droplets, for which heat and mass transfer processes are not described in the conventional diffusion model. The calculation results of evaporation of droplets of different sizes were compared using two models: the conventional diffusion and emission-diffusion models. To verify the proposed physical model, the evaporation of droplets suspended on a polypropylene fiber was experimentally investigated. The form of droplets in the evaporation process was determined using microphotographing. The temperature was measured on the surfaces of evaporating drops using infrared thermography. The experimental results have showed good agreement with the numerical data for the time of evaporation and the temperature of evaporating drops.

  6. Low temperature surface conductivity of hydrogenated diamond

    Energy Technology Data Exchange (ETDEWEB)

    Sauerer, C.; Ertl, F.; Nebel, C.E.; Stutzmann, M. [Technische Univ. Muenchen, Garching (Germany). Walter-Schottky-Inst. fuer Physikalische Grundlagen der Halbleiterelektronik; Bergonzo, P. [LIST(CEA-Recherche Technology)/DIMIR/SIAR/Saclay, Gif-sur-Yvette (France); Williams, O.A.; Jackman, R.A. [University Coll., London (United Kingdom). Dept. of Electrical and Electronic Engineering

    2001-07-23

    Conductivity and Hall experiments are performed on hydrogenated poly-CVD, atomically flat homoepitaxially grown Ib and natural type IIa diamond layers in the regime 0.34 to 400 K. For all experiments hole transport is detected with sheet resistivities at room temperature in the range 10{sup 4} to 10{sup 5} {omega}/{radical}. We introduce a transport model where a disorder induced tail of localized states traps holes at very low temperatures (T < 70 K). The characteristic energy of the tail is in the range of 6 meV. Towards higher temperatures (T > 70 K) the hole density is approximately constant and the hole mobility {mu} is increasing two orders of magnitude. In the regime 70 K < T < 200 K, {mu} is exponentially activated with 22 meV, above it follows a {proportional_to}T{sup 3/2} law. The activation energy of the hole density at T < 70 K is governed by the energy gap between holes trapped in the tail and the mobility edge which they can propagate. In the temperature regime T < 25 K an increasing hole mobility is detected which is attributed to transport in delocalized states at the surface. (orig.)

  7. Identification of characteristic model-observation deviations for coupled data assimilation

    Science.gov (United States)

    Geppert, Gernot; Ament, Felix

    2016-04-01

    Exchange fluxes of water and energy between the land surface and the atmosphere lead to the propagation of errors from one model component to the other. Data assimilation can correct such errors in two ways, either by correcting the observed state directly or by changing the state that caused the exchange fluxes. The land surface, for example, strongly determines the temperature in the atmospheric boundary layer. The assimilation of boundary layer temperature can then correct the model's temperature directly. Or the assimilation of boundary layer temperature can act on the model's land surface state. A coupled data assimilation system should exploit these links and enable the second type of correction across model components. Data assimilation relies on instantaneous deviations between model forecasts and observations. Such instantaneous deviations are often hard to relate to errors in specific model components. Therefore, model verification builds on more sophisticated statistics such as long-term biases, gradients, phase shifts, or conditional differences that yield characteristic differences between model forecasts and observations. Compared to the instantaneous deviations in data assimilation, the characteristic deviations in model verification are more closely linked to errors in specific model components. Consequently, such characteristic deviations can potentially be used for data assimilation across model components where instantaneous deviations are not sufficiently informative. As a first step towards data assimilation with characteristic deviations (here named fingerprints), we use ensembles of simulations with the Icosahedral Non-hydrostatic (ICON) model to identify applicable statistics of observable variables. We run ICON in a large eddy simulation configuration on a small, limited domain and systematically perturb soil and land-surface parameters and states to produce the ensembles. Subsequently, we test statistics of boundary layer observables to

  8. Impact of Assimilating Surface Velocity Observations on the Model Sea Surface Height Using the NCOM-4DVAR

    Science.gov (United States)

    2016-09-26

    atmospheric pressure , and surface heat flux is provided by the 0.58 NOGAPS model every 3h (Rosmond et al. 2002); river forcing is provided via an...horizontal pressure -gradient force in an oceanic model with nonaligned vertical grid. J. Geophys. Res., 108, 3090, doi:10.1029/2001JC001047. ——, and... Model Sea Surface Height Using the NCOM-4DVAR 0602435N 73-4727-14-5 MATTHEW J. CARRIER, HANS E. NGODOCK, PHILIP MUSCARELLA, AND SCOTT SMITH Naval

  9. Analysis of Multiple Precipitation Products and Preliminary Assessment of Their Impact on Global Land Data Assimilation System (GLDAS) Land Surface States

    Science.gov (United States)

    Gottschalck, Jon; Meng, Jesse; Rodel, Matt; Houser, paul

    2005-01-01

    Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth's water cycle and climate variability. NASA's Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type). Precipitation is arguably the most important input to LSMs. Many precipitation datasets have been produced using satellite and rain gauge observations and weather forecast models. In this study, seven different global precipitation datasets were evaluated over the United States, where dense rain gauge networks contribute to reliable precipitation maps. We then used the seven datasets as inputs to GLDAS simulations, so that we could diagnose their impacts on output stocks and fluxes of water. In terms of totals, the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) had the closest agreement with the US rain gauge dataset for all seasons except winter. The CMAP precipitation was also the most closely correlated in time with the rain gauge data during spring, fall, and winter, while the satellitebased estimates performed best in summer. The GLDAS simulations revealed that modeled soil moisture is highly

  10. Evaluation and Monitoring of Jpss Land Surface Temperature Data

    Science.gov (United States)

    Yu, Y.; Yu, P.; Liu, Y.; Csiszar, I. A.

    2016-12-01

    Land Surface Temperature (LST) is one of environmental data records (EDRs) produced operationally through the U.S. Joint Polar Satellite System (JPSS) mission. LST is an important parameter for understanding climate change, modeling the hydrological and biogeochemical cycles, and is a prime candidate for Numerical Weather Prediction (NWP) assimilation models. Recently, the international LST and Emissivity Working Ggroup (ILSTE-WG) is promoting to the inclusion of the LST as essential climate variable (ECV) in the Global Climate Observation System (GCOS) of the Word Meteorological Organization (WMO). At the Center for Satellite Applications and Research (STAR) of National Atmospheric and Oceanic Administration (NOAA), we, are as a science team, are responsible to for the science of JPSS LST production. In this work, we present our activities and accomplishments on the JPSS LST evaluation and monitoring since the launch of the first JPSS satellite, i.e. S-NPP, satellite. Beta version, provisional version, and validated stage 1 version of the S-NPP LST products which were announced in May 2013, July 2014, and March 2015, respectively. Evaluation of the LST products have been performed versus ground measurements and other polar-orbiting satellite LST data (e,g. MODIS LSTs); some results will be illustrated. A daily monitoring system of the JPSS LST production has been developed, which presents daily, weekly and monthly global LST maps and inter-comparison results on the STAR JPSS program website. Further, evaluation of the enterprise LST algorithm for JPSS mission which is in development at STAR currently are presented in this work. Finally, evaluation and monitoring plan of the LST production for the JPSS-1 satellite are also presented.

  11. Satellite Sensed Skin Sea Surface Temperature

    Science.gov (United States)

    Donlon, Craig

    1997-01-01

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

  12. Extended Reconstructed Sea Surface Temperature (ERSST), Version 4

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Extended Reconstructed Sea Surface Temperature (ERSST) dataset is a global monthly sea surface temperature analysis on a 2x2 degree grid derived from the...

  13. NOAA Global Surface Temperature Dataset, Version 4.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is derived from two independent analyses: the Extended Reconstructed Sea Surface Temperature (ERSST)...

  14. HTPro: Low-temperature Surface Hardening of Stainless Steel

    DEFF Research Database (Denmark)

    Christiansen, Thomas Lundin; Somers, Marcel A. J.

    2013-01-01

    Low-temperature surface hardening of stainless steel provides the required performance properties without affecting corrosion resistance.......Low-temperature surface hardening of stainless steel provides the required performance properties without affecting corrosion resistance....

  15. Merged Land and Ocean Surface Temperature, Version 3.5

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The historical Merged Land-Ocean Surface Temperature Analysis (MLOST) is derived from two independent analyses, an Extended Reconstructed Sea Surface Temperature...

  16. Middle Pliocene sea surface temperature variability

    Science.gov (United States)

    Dowsett, H.J.; Chandler, M.A.; Cronin, T. M.; Dwyer, G.S.

    2005-01-01

    Estimates of sea surface temperature (SST) based upon foraminifer, diatom, and ostracod assemblages from ocean cores reveal a warm phase of the Pliocene between about 3.3 and 3.0 Ma. Pollen records and plant megafossils, although not as well dated, show evidence for a warmer climate at about the same time. Increased greenhouse forcing and altered ocean heat transport are the leading candidates for the underlying cause of Pliocene global warmth. Despite being a period of global warmth, this interval encompasses considerable variability. Two new SST reconstructions are presented that are designed to provide a climatological error bar for warm peak phases of the Pliocene and to document the spatial distribution and magnitude of SST variability within the mid-Pliocene warm period. These data suggest long-term stability of low-latitude SST and document greater variability in regions of maximum warming. Copyright 2005 by the American Geophysical Union.

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

    Science.gov (United States)

    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

  18. Impact of Atlantic sea surface temperatures on the warmest global surface air temperature of 1998

    Science.gov (United States)

    Lu, Riyu

    2005-03-01

    The year 1998 is the warmest year in the record of instrumental measurements. In this study, an atmospheric general circulation model is used to investigate the role of sea surface temperatures (SSTs) in this warmth, with a focus on the role of the Atlantic Ocean. The model forced with the observed global SSTs captures the main features of land surface air temperature anomalies in 1998. A sensitivity experiment shows that in comparison with the global SST anomalies, the Atlantic SST anomalies can explain 35% of the global mean surface air temperature (GMAT) anomaly, and 57% of the land surface air temperature anomaly in 1998. The mechanisms through which the Atlantic Ocean influences the GMAT are likely different from season to season. Possible detailed mechanisms involve the impact of SST anomalies on local convection in the tropical Atlantic region, the consequent excitation of a Rossby wave response that propagates into the North Atlantic and the Eurasian continent in winter and spring, and the consequent changes in tropical Walker circulation in summer and autumn that induce changes in convection over the tropical Pacific. This in turn affects climate in Asia and Australia. The important role of the Atlantic Ocean suggests that attention should be paid not only to the tropical Pacific Ocean, but also to the tropical Atlantic Ocean in understanding the GMAT variability and its predictability.

  19. Low Temperature Surface Carburization of Stainless Steels

    Energy Technology Data Exchange (ETDEWEB)

    Collins, Sunniva R; Heuer, Arthur H; Sikka, Vinod K

    2007-12-07

    Low-temperature colossal supersaturation (LTCSS) is a novel surface hardening method for carburization of austenitic stainless steels (SS) without the precipitation of carbides. The formation of carbides is kinetically suppressed, enabling extremely high or colossal carbon supersaturation. As a result, surface carbon concentrations in excess of 12 at. % are routinely achieved. This treatment increases the surface hardness by a factor of four to five, improving resistance to wear, corrosion, and fatigue, with significant retained ductility. LTCSS is a diffusional surface hardening process that provides a uniform and conformal hardened gradient surface with no risk of delamination or peeling. The treatment retains the austenitic phase and is completely non-magnetic. In addition, because parts are treated at low temperature, they do not distort or change dimensions. During this treatment, carbon diffusion proceeds into the metal at temperatures that constrain substitutional diffusion or mobility between the metal alloy elements. Though immobilized and unable to assemble to form carbides, chromium and similar alloying elements nonetheless draw enormous amounts of carbon into their interstitial spaces. The carbon in the interstitial spaces of the alloy crystals makes the surface harder than ever achieved before by more conventional heat treating or diffusion process. The carbon solid solution manifests a Vickers hardness often exceeding 1000 HV (equivalent to 70 HRC). This project objective was to extend the LTCSS treatment to other austenitic alloys, and to quantify improvements in fatigue, corrosion, and wear resistance. Highlights from the research include the following: • Extension of the applicability of the LTCSS process to a broad range of austenitic and duplex grades of steels • Demonstration of LTCSS ability for a variety of different component shapes and sizes • Detailed microstructural characterization of LTCSS-treated samples of 316L and other alloys

  20. Turbulent Flow past High Temperature Surfaces

    Science.gov (United States)

    Mehmedagic, Igbal; Thangam, Siva; Carlucci, Pasquale; Buckley, Liam; Carlucci, Donald

    2014-11-01

    Flow over high-temperature surfaces subject to wall heating is analyzed with applications to projectile design. In this study, computations are performed using an anisotropic Reynolds-stress model to study flow past surfaces that are subject to radiative flux. The model utilizes a phenomenological treatment of the energy spectrum and diffusivities of momentum and heat to include the effects of wall heat transfer and radiative exchange. The radiative transport is modeled using Eddington approximation including the weighted effect of nongrayness of the fluid. The time-averaged equations of motion and energy are solved using the modeled form of transport equations for the turbulence kinetic energy and the scalar form of turbulence dissipation with an efficient finite-volume algorithm. The model is applied for available test cases to validate its predictive capabilities for capturing the effects of wall heat transfer. Computational results are compared with experimental data available in the literature. Applications involving the design of projectiles are summarized. Funded in part by U.S. Army, ARDEC.

  1. Global Land Data Assimilation System

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The goal of the Global Land Data Assimilation System (GLDAS) is to ingest satellite- and ground-based observational data products, using advanced land surface...

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

    Science.gov (United States)

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

    2015-12-01

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

  3. Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France

    Directory of Open Access Journals (Sweden)

    A. L. Barbu

    2014-01-01

    Full Text Available The land monitoring service of the European Copernicus programme has developed a set of satellite-based biogeophysical products, including surface soil moisture (SSM and leaf area index (LAI. This study investigates the impact of joint assimilation of remotely sensed SSM derived from Advanced Scatterometer (ASCAT backscatter data and the Copernicus Global Land GEOV1 satellite-based LAI product into the the vegetation growth version of the Interactions between Soil Biosphere Atmosphere (ISBA-A-gs land surface model within the the externalised surface model (SURFEX modelling platform of Météo-France. The ASCAT data were bias corrected with respect to the model climatology by using a seasonal-based CDF (Cumulative Distribution Function matching technique. A multivariate multi-scale land data assimilation system (LDAS based on the extended Kalman Filter (EKF is used for monitoring the soil moisture, terrestrial vegetation, surface carbon and energy fluxes across the domain of France at a spatial resolution of 8 km. Each model grid box is divided into a number of land covers, each having its own set of prognostic variables. The filter algorithm is designed to provide a distinct analysis for each land cover while using one observation per grid box. The updated values are aggregated by computing a weighted average. In this study, it is demonstrated that the assimilation scheme works effectively within the ISBA-A-gs model over a four-year period (2008–2011. The EKF is able to extract useful information from the data signal at the grid scale and distribute the root-zone soil moisture and LAI increments throughout the mosaic structure of the model. The impact of the assimilation on the vegetation phenology and on the water and carbon fluxes varies from one season to another. The spring drought of 2011 is an interesting case study of the potential of the assimilation to improve drought monitoring. A comparison between simulated and in situ soil

  4. Data Assimilation in Ocean Prediction

    Science.gov (United States)

    2016-06-07

    contour plots of the estimates of the sea surface height ( SSH ) for the top layer after 5 Topex/ Poseidon simulated repeat cycles. The top plot in Figure... SSH ): Top: SSH for the actual truth; middle: SSH with no data assimilation; and bottom: SSH with data assimilation from satellite altimetry. Darker...regions are deeper, lighter regions are higher. 2: RMSE of the SSH for the top two layers. The lower curve is the RMSE for the surface layer while the

  5. Validation Test Report for the Variational Assimilation of Satellite Sea Surface Temperature Radiances

    Science.gov (United States)

    2014-08-04

    DOCUMENTATION PAGE Form ApprovedOMB No. 0704-0188 3. DATES COVERED (From - To) Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 Public... DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 6. AUTHOR(S) 8. PERFORMING ORGANIZATION REPORT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 10...fields provide situation dependent prior error statistics that vary with location and evolve with time. The combined effect of radiometric noise in

  6. Data assimilation in a coupled physical-biogeochemical model of the California current system using an incremental lognormal 4-dimensional variational approach: Part 3-Assimilation in a realistic context using satellite and in situ observations

    Science.gov (United States)

    Song, Hajoon; Edwards, Christopher A.; Moore, Andrew M.; Fiechter, Jerome

    2016-10-01

    A fully coupled physical and biogeochemical ocean data assimilation system is tested in a realistic configuration of the California Current System using the Regional Ocean Modeling System. In situ measurements for sea surface temperature and salinity as well as satellite observations for temperature, sea level and chlorophyll are used for the year 2000. Initial conditions of the combined physical and biogeochemical state are adjusted at the start of each 3-day assimilation cycle. Data assimilation results in substantial reduction of root-mean-square error (RMSE) over unconstrained model output. RMSE for physical variables is slightly lower when assimilating only physical variables than when assimilating both physical variables and surface chlorophyll. Surface chlorophyll RMSE is lowest when assimilating both physical variables and surface chlorophyll. Estimates of subsurface, nitrate and chlorophyll show modest improvements over the unconstrained model run relative to independent, unassimilated in situ data. Assimilation adjustments to the biogeochemical initial conditions are investigated within different regions of the California Current System. The incremental, lognormal 4-dimensional data assimilation method tested here represents a viable approach to coupled physical biogeochemical state estimation at practical computational cost.

  7. A balanced Kalman filter ocean data assimilation system with application to the South Australian Sea

    Science.gov (United States)

    Li, Yi; Toumi, Ralf

    2017-08-01

    In this paper, an Ensemble Kalman Filter (EnKF) based regional ocean data assimilation system has been developed and applied to the South Australian Sea. This system consists of the data assimilation algorithm provided by the NCAR Data Assimilation Research Testbed (DART) and the Regional Ocean Modelling System (ROMS). We describe the first implementation of the physical balance operator (temperature-salinity, hydrostatic and geostrophic balance) to DART, to reduce the spurious waves which may be introduced during the data assimilation process. The effect of the balance operator is validated in both an idealised shallow water model and the ROMS model real case study. In the shallow water model, the geostrophic balance operator eliminates spurious ageostrophic waves and produces a better sea surface height (SSH) and velocity analysis and forecast. Its impact increases as the sea surface height and wind stress increase. In the real case, satellite-observed sea surface temperature (SST) and SSH are assimilated in the South Australian Sea with 50 ensembles using the Ensemble Adjustment Kalman Filter (EAKF). Assimilating SSH and SST enhances the estimation of SSH and SST in the entire domain, respectively. Assimilation with the balance operator produces a more realistic simulation of surface currents and subsurface temperature profile. The best improvement is obtained when only SSH is assimilated with the balance operator. A case study with a storm suggests that the benefit of the balance operator is of particular importance under high wind stress conditions. Implementing the balance operator could be a general benefit to ocean data assimilation systems.

  8. Monitoring temperature and pressure over surfaces using sensitive paints

    Science.gov (United States)

    Guerrero-Viramontes, J. Ascención; Moreno Hernández, David; Mendoza Santoyo, Fernando; Morán Loza, José Miguel; García Arreola, Alicia

    2007-03-01

    Two techniques for monitoring temperature and pressure variations over surfaces using sensitive paints are presented. The analysis is done by the acquisition of a set of images of the surface under analysis. The surface is painted by a paint called Pressure Sensitive Paint (PSP) for pressure measurements and Temperature Sensitive Paints (TSP) for temperature measurements. These kinds of paints are deposited over the surface under analysis. The recent experimental advances in calibration process are presented in this paper.

  9. Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0

    Science.gov (United States)

    Schürmann, Gregor J.; Kaminski, Thomas; Köstler, Christoph; Carvalhais, Nuno; Voßbeck, Michael; Kattge, Jens; Giering, Ralf; Rödenbeck, Christian; Heimann, Martin; Zaehle, Sönke

    2016-09-01

    We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS) built around the tangent-linear version of the JSBACH land-surface scheme, which is part of the MPI-Earth System Model v1. The simulated phenology and net land carbon balance were constrained by globally distributed observations of the fraction of absorbed photosynthetically active radiation (FAPAR, using the TIP-FAPAR product) and atmospheric CO2 at a global set of monitoring stations for the years 2005 to 2009. When constrained by FAPAR observations alone, the system successfully, and computationally efficiently, improved simulated growing-season average FAPAR, as well as its seasonality in the northern extra-tropics. When constrained by atmospheric CO2 observations alone, global net and gross carbon fluxes were improved, despite a tendency of the system to underestimate tropical productivity. Assimilating both data streams jointly allowed the MPI-CCDAS to match both observations (TIP-FAPAR and atmospheric CO2) equally well as the single data stream assimilation cases, thereby increasing the overall appropriateness of the simulated biosphere dynamics and underlying parameter values. Our study thus demonstrates the value of multiple-data-stream assimilation for the simulation of terrestrial biosphere dynamics. It further highlights the potential role of remote sensing data, here the TIP-FAPAR product, in stabilising the strongly underdetermined atmospheric inversion problem posed by atmospheric transport and CO2 observations alone. Notwithstanding these advances, the constraint of the observations on regional gross and net CO2 flux patterns on the MPI-CCDAS is limited through the coarse-scale parametrisation of the biosphere model. We expect improvement through a refined initialisation strategy and inclusion of further biosphere observations as constraints.

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

    Science.gov (United States)

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

    2012-01-01

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

  11. The temperature response of CO2 assimilation, photochemical activities and Rubisco activation in Camelina sativa, a potential bioenergy crop with limited capacity for acclimation to heat stress.

    Science.gov (United States)

    Carmo-Silva, A Elizabete; Salvucci, Michael E

    2012-11-01

    The temperature optimum of photosynthesis coincides with the average daytime temperature in a species' native environment. Moderate heat stress occurs when temperatures exceed the optimum, inhibiting photosynthesis and decreasing productivity. In the present study, the temperature response of photosynthesis and the potential for heat acclimation was evaluated for Camelina sativa, a bioenergy crop. The temperature optimum of net CO(2) assimilation rate (A) under atmospheric conditions was 30-32 °C and was only slightly higher under non-photorespiratory conditions. The activation state of Rubisco was closely correlated with A at supra-optimal temperatures, exhibiting a parallel decrease with increasing leaf temperature. At both control and elevated temperatures, the modeled response of A to intercellular CO(2) concentration was consistent with Rubisco limiting A at ambient CO(2). Rubisco activation and photochemical activities were affected by moderate heat stress at lower temperatures in camelina than in the warm-adapted species cotton and tobacco. Growth under conditions that imposed a daily interval of moderate heat stress caused a 63 % reduction in camelina seed yield. Levels of cpn60 protein were elevated under the higher growth temperature, but acclimation of photosynthesis was minimal. Inactivation of Rubisco in camelina at temperatures above 35 °C was consistent with the temperature response of Rubisco activase activity and indicated that Rubisco activase was a prime target of inhibition by moderate heat stress in camelina. That photosynthesis exhibited no acclimation to moderate heat stress will likely impact the development of camelina and other cool season Brassicaceae as sources of bioenergy in a warmer world.

  12. Estimation of sea surface temperature (SST) using marine seismic data

    Digital Repository Service at National Institute of Oceanography (India)

    Sinha, S.K.; Dewangan, P.; Sain, K.

    .g. Wu et al. [1999]). However, due to the skin effect, sea surface temperatures as measured by satellites can be very different from temperatures a few centimeters below the sea surface (i.e. in-situ temperatures) [Emery et al., 1994]. Therefore...

  13. Noncontact Monitoring of Surface Temperature Distribution by Laser Ultrasound Scanning

    Science.gov (United States)

    Yamada, Hiroyuki; Kosugi, Akira; Ihara, Ikuo

    2011-07-01

    A laser ultrasound scanning method for measuring a surface temperature distribution of a heated material is presented. An experiment using an aluminum plate heated up to 120 °C is carried out to verify the feasibility of the proposed method. A series of one-dimensional surface acoustic wave (SAW) measurements within an area of a square on the aluminum surface are performed by scanning a pulsed laser for generating SAW using a galvanometer system, where the SAWs are detected at a fixed location on the surface. An inverse analysis is then applied to SAW data to determine the surface temperature distribution in a certain direction. The two-dimensional distribution of the surface temperature in the square is constructed by combining the one-dimensional surface temperature distributions obtained within the square. The surface temperature distributions obtained by the proposed method almost agrees with those obtained using an infrared radiation camera.

  14. A three-dimensional variational ocean data assimilation system: Scheme and preliminary results

    Institute of Scientific and Technical Information of China (English)

    ZHU; Jiang; ZHOU; Guangqing; YAN; Changxiang; FU; Weiwei

    2006-01-01

    A new 3DVAR-based Ocean Variational Analysis System (OVALS) is developed. OVALS is capable of assimilating in situ sea water temperature and salinity observations and satellite altimetry data. As a component of OVALS, a new variational scheme is proposed to assimilate the sea surface height data. This scheme considers both the vertical correlation of background errors and the nonlinear temperature-salinity relationship which is derived from the generalization of the linear balance constraints to the nonlinear in the 3DVAR. By this scheme, the model temperature and salinity fields are directly adjusted from the altimetry data. Additionally, OVALS can assimilate the temperature and salinity profiles from the ARGO floats which have been implemented in recent years and some temperature and salinity data such as from expendable bathythermograph, moored ocean buoys, etc.A 21-year assimilation experiment is carried out by using OVALS and the Tropical Pacific circulation model. The results show that the assimilation system may effectively improve the estimations of temperature and salinity by assimilating all kinds of observations. Moreover, the root mean square errors of temperature and salinity in the upper depth less than 420 m reach 0.63℃ and 0.34 psu.

  15. Numerical Solution of the Variational Data Assimilation Problem Using Satellite Data

    Science.gov (United States)

    Agoshkov, V. I.; Lebedv, S. A.; Parmuzin, E. I.

    2010-12-01

    The problem of variational assimilation of satellite observational data on the ocean surface temperature is formulated and numerically investigated in order to reconstruct surface heat fluxes with the use of the global three-dimensional model of ocean hydrothermodynamics developed at the Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), and observational data on the ocean surface temperature over the year 2004. The algorithms of the numerical solution to the problem are elaborated and substantiated, and the data assimilation block is developed and incorporated into the global three-dimensional model. Numerical experiments are carried out with the use of the Indian Ocean water area as an example. Numerical experiments confirm the theoretical conclusions obtained and demonstrate the expediency of combining the model with a block of assimilating operational observational data on the surface temperature.

  16. Optimality in Data Assimilation

    Science.gov (United States)

    Nearing, Grey; Yatheendradas, Soni

    2016-04-01

    prior (i.e., the model uncertainty distribution), and in the likelihood (i.e., the observation operator and observation uncertainty distribution). In this way, we can directly identify the parts of a data assimilation algorithm that contribute most to assimilation error in a way that (unlike traditional DA performance metrics) considers nonlinearity in the model and observation and non-optimality in the fit between filter assumptions and the real system. To reiterate, the method we propose is theoretically rigorous but also dead-to-rights simple, and can be implemented in no more than a few hours by a competent programmer. We use this to show that careful applications of the Ensemble Kalman Filter use substantially less than half of the information contained in remote sensing soil moisture retrievals (LPRM, AMSR-E, SMOS, and SMOPS). We propose that this finding may explain some of the results from several recent large-scale experiments that show lower-than-expected value to assimilating soil moisture retrievals into land surface models forced by high-quality precipitation data. Our results have important implications for the SMAP mission because over half of the SMAP-affiliated "early adopters" plan to use the EnKF as their primary method for extracting information from SMAP retrievals.

  17. Technique for the estimation of surface temperatures from embedded temperature sensing for rapid, high energy surface deposition.

    Energy Technology Data Exchange (ETDEWEB)

    Watkins, Tyson R.; Schunk, Peter Randall; Roberts, Scott Alan

    2014-07-01

    Temperature histories on the surface of a body that has been subjected to a rapid, highenergy surface deposition process can be di cult to determine, especially if it is impossible to directly observe the surface or attach a temperature sensor to it. In this report, we explore two methods for estimating the temperature history of the surface through the use of a sensor embedded within the body very near to the surface. First, the maximum sensor temperature is directly correlated with the peak surface temperature. However, it is observed that the sensor data is both delayed in time and greatly attenuated in magnitude, making this approach unfeasible. Secondly, we propose an algorithm that involves tting the solution to a one-dimensional instantaneous energy solution problem to both the sensor data and to the results of a one-dimensional CVFEM code. This algorithm is shown to be able to estimate the surface temperature 20 C.

  18. Determination of Land Surface Temperature (LST) and Potential ...

    African Journals Online (AJOL)

    Determination of Land Surface Temperature (LST) and Potential Urban Heat Island Effect in Parts of Lagos State using Satellite ... Changes in temperature appear to be closely related to concentrations of atmospheric carbon dioxide.

  19. Temperature dependent droplet impact dynamics on flat and textured surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Azar Alizadeh; Vaibhav Bahadur; Sheng Zhong; Wen Shang; Ri Li; James Ruud; Masako Yamada; Liehi Ge; Ali Dhinojwala; Manohar S Sohal (047160)

    2012-03-01

    Droplet impact dynamics determines the performance of surfaces used in many applications such as anti-icing, condensation, boiling and heat transfer. We study impact dynamics of water droplets on surfaces with chemistry/texture ranging from hydrophilic to superhydrophobic and across a temperature range spanning below freezing to near boiling conditions. Droplet retraction shows very strong temperature dependence especially for hydrophilic surfaces; it is seen that lower substrate temperatures lead to lesser retraction. Physics-based analyses show that the increased viscosity associated with lower temperatures can explain the decreased retraction. The present findings serve to guide further studies of dynamic fluid-structure interaction at various temperatures.

  20. Evaluation of an ocean data assimilation system for Chinese marginal seas with a focus on the South China Sea

    Institute of Scientific and Technical Information of China (English)

    XU Dazhi; LI Xichen; ZHU Jiang; QI Yiquan

    2011-01-01

    Data assimilation is a powerful tool to improve ocean forecasting by reducing uncertainties in forecast initial conditions. Recently, an ocean data assimilation system based on the ensemble optimal interpolation (EnOI) scheme and HYbrid Coordinate Ocean Model (HYCOM) for marginal seas around China was developed. This system can assimilate both satellite observations of sea surface temperature (SST) and along-track sea level anomaly (SLA) data. The purpose of this study was to evaluate the performance of the system. Two experiments were performed, which spanned a 3-year period from January 1, 2004 to December 30, 2006, with and without data assimilation. The data assimilation results were promising, with a positive impact on the modeled fields. The SST and SLA were clearly improved in terms of bias and root mean square error over the whole domain. In addition, the assimilations provided improvements in some regions to the surface field where mesoscale processes are not well simulated by the model. Comparisons with surface drifter trajectories showed that assimilated SST and SLA also better represent surface currents, with drifter trajectories fitting better to the contours of SLA field than that without assimilation. The forecasting capacity of this assimilation system was also evaluated through a case study of a birth-and-death process of an anticyclone eddy in the Northern South China Sea (NSCS), in which the anticyclone eddy was successfully hindcasted by the assimilation system. This study suggests the data assimilation system gives reasonable descriptions of the near-surface ocean state and can be applied to forecast mesoscale ocean processes in the marginal seas around China.

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

    Directory of Open Access Journals (Sweden)

    Baojuan Shan

    2013-01-01

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

  2. Assimilation of surface water heat flux using Ensemble Kalman Filter%基于集合卡尔曼滤波的地表水热通量同化研究

    Institute of Scientific and Technical Information of China (English)

    束士杰; 刘朝顺; 施润和; 高炜

    2013-01-01

    from 82.56 W/m2 to 48.56 W/m2 and that of latent heat flux fell from 42.99 W/m2 to 38.92 W/m2, respectively. Tonzi Ranch, a grassland site, RMSE in is also diminished by assimilating in situ observations with decrements of 45.14W/m2 for sensible heat flux and 8.75 W/m2 for latent heat flux. Furthermore, by comparing the results we gained above with mainstream study that focusing on assimilation of surface temperature and humidity to indirectly improve the fluxes prediction, we conclude that under the dynamic framework of community land model the flux outputs from direct assimilation model are better than those from surface state assimilation model. It is noteworthy that the accuracy of observational error estimation will directly affect the assimilation results though errors from initial condition, observation and atmospheric forcing will make contributions simultaneously.

  3. Estimation of Surface Heat Flux and Surface Temperature during Inverse Heat Conduction under Varying Spray Parameters and Sample Initial Temperature

    Directory of Open Access Journals (Sweden)

    Muhammad Aamir

    2014-01-01

    Full Text Available An experimental study was carried out to investigate the effects of inlet pressure, sample thickness, initial sample temperature, and temperature sensor location on the surface heat flux, surface temperature, and surface ultrafast cooling rate using stainless steel samples of diameter 27 mm and thickness (mm 8.5, 13, 17.5, and 22, respectively. Inlet pressure was varied from 0.2 MPa to 1.8 MPa, while sample initial temperature varied from 600°C to 900°C. Beck’s sequential function specification method was utilized to estimate surface heat flux and surface temperature. Inlet pressure has a positive effect on surface heat flux (SHF within a critical value of pressure. Thickness of the sample affects the maximum achieved SHF negatively. Surface heat flux as high as 0.4024 MW/m2 was estimated for a thickness of 8.5 mm. Insulation effects of vapor film become apparent in the sample initial temperature range of 900°C causing reduction in surface heat flux and cooling rate of the sample. A sensor location near to quenched surface is found to be a better choice to visualize the effects of spray parameters on surface heat flux and surface temperature. Cooling rate showed a profound increase for an inlet pressure of 0.8 MPa.

  4. Estimation of surface heat flux and surface temperature during inverse heat conduction under varying spray parameters and sample initial temperature.

    Science.gov (United States)

    Aamir, Muhammad; Liao, Qiang; Zhu, Xun; Aqeel-ur-Rehman; Wang, Hong; Zubair, Muhammad

    2014-01-01

    An experimental study was carried out to investigate the effects of inlet pressure, sample thickness, initial sample temperature, and temperature sensor location on the surface heat flux, surface temperature, and surface ultrafast cooling rate using stainless steel samples of diameter 27 mm and thickness (mm) 8.5, 13, 17.5, and 22, respectively. Inlet pressure was varied from 0.2 MPa to 1.8 MPa, while sample initial temperature varied from 600°C to 900°C. Beck's sequential function specification method was utilized to estimate surface heat flux and surface temperature. Inlet pressure has a positive effect on surface heat flux (SHF) within a critical value of pressure. Thickness of the sample affects the maximum achieved SHF negatively. Surface heat flux as high as 0.4024 MW/m(2) was estimated for a thickness of 8.5 mm. Insulation effects of vapor film become apparent in the sample initial temperature range of 900°C causing reduction in surface heat flux and cooling rate of the sample. A sensor location near to quenched surface is found to be a better choice to visualize the effects of spray parameters on surface heat flux and surface temperature. Cooling rate showed a profound increase for an inlet pressure of 0.8 MPa.

  5. Predicting monsoon rainfall and pressure indices from sea surface temperature

    Digital Repository Service at National Institute of Oceanography (India)

    Sadhuram, Y.

    The relationship between the sea surface temperature (SST) in the Indian Ocean and monsoon rainfall has been examined by using 21 years data set (1967-87) of MOHSST.6 (Met. Office Historical Sea Surface Temperature data set, obtained from U.K. Met...

  6. Metal surface temperature induced by moving laser beams

    NARCIS (Netherlands)

    Römer, G.R.B.E.; Meijer, J.

    1995-01-01

    Whenever a metal is irradiated with a laser beam, electromagnetic energy is transformed into heat in a thin surface layer. The maximum surface temperature is the most important quantity which determines the processing result. Expressions for this maximum temperature are provided by the literature fo

  7. Recent trends in sea surface temperature off Mexico

    NARCIS (Netherlands)

    Lluch-Cota, S.E.; Tripp-Valdéz, M.; Lluch-Cota, D.B.; Lluch-Belda, D.; Verbesselt, J.; Herrera-Cervantes, H.; Bautista-Romero, J.

    2013-01-01

    Changes in global mean sea surface temperature may have potential negative implications for natural and socioeconomic systems; however, measurements to predict trends in different regions have been limited and sometimes contradictory. In this study, an assessment of sea surface temperature change si

  8. Recent trends in sea surface temperature off Mexico

    NARCIS (Netherlands)

    Lluch-Cota, S.E.; Tripp-Valdéz, M.; Lluch-Cota, D.B.; Lluch-Belda, D.; Verbesselt, J.; Herrera-Cervantes, H.; Bautista-Romero, J.

    2013-01-01

    Changes in global mean sea surface temperature may have potential negative implications for natural and socioeconomic systems; however, measurements to predict trends in different regions have been limited and sometimes contradictory. In this study, an assessment of sea surface temperature change

  9. Reintroducing radiometric surface temperature into the Penman-Monteith formulation

    DEFF Research Database (Denmark)

    Mallick, Kaniska; Bøgh, Eva; Trebs, Ivonne;

    2015-01-01

    Here we demonstrate a novel method to physically integrate radiometric surface temperature (TR) into the Penman-Monteith (PM) formulation for estimating the terrestrial sensible and latent heat fluxes (H and λE) in the framework of a modified Surface Temperature Initiated Closure (STIC). It combi...

  10. TEMPERATURE EFFECTS ON MICROALGAL PHOTOSYNTHESIS-LIGHT RESPONSES MEASURED BY O2 PRODUCTION, PULSE-AMPLITUDE-MODULATED FLUORESCENCE, AND (14) C ASSIMILATION(1).

    Science.gov (United States)

    Hancke, Kasper; Hancke, Torunn B; Olsen, Lasse M; Johnsen, Geir; Glud, Ronnie N

    2008-04-01

    Short-term temperature effects on photosynthesis were investigated by measuring O2 production, PSII-fluorescence kinetics, and (14) C-incorporation rates in monocultures of the marine phytoplankton species Prorocentrum minimum (Pavill.) J. Schiller (Dinophyceae), Prymnesium parvum f. patelliferum (J. C. Green, D. J. Hibberd et Pienaar) A. Larsen (Coccolithophyceae), and Phaeodactylum tricornutum Bohlin (Bacillariophyceae), grown at 15°C and 80 μmol photons · m(-2)  · s(-1) . Photosynthesis versus irradiance curves were measured at seven temperatures (0°C-30°C) by all three approaches. The maximum photosynthetic rate (P(C) max ) was strongly stimulated by temperature, reached an optimum for Pro. minimum only (20°C-25°C), and showed a similar relative temperature response for the three applied methods, with Q10 ranging from 1.7 to 3.5. The maximum light utilization coefficient (α(C) ) was insensitive or decreased slightly with increasing temperature. Absolute rates of O2 production were calculated from pulse-amplitude-modulated (PAM) fluorometry measurements in combination with biooptical determination of absorbed quanta in PSII. The relationship between PAM-based O2 production and measured O2 production and (14) C assimilation showed a species-specific correlation, with 1.2-3.3 times higher absolute values of P(C) max and α(C) when calculated from PAM data for Pry. parvum and Ph. tricornutum but equivalent for Pro. minimum. The offset seemed to be temperature insensitive and could be explained by a lower quantum yield for O2 production than the theoretical maximum (due to Mehler-type reactions). Conclusively, the PAM technique can be used to study temperature responses of photosynthesis in microalgae when paying attention to the absorption properties in PSII.

  11. Interferometric measurements of sea surface temperature and emissivity

    Science.gov (United States)

    Fiedler, Lars; Bakan, Stephan

    1997-09-01

    A new multispectral method to derive sea surface emissivity and temperature by using interferometer measurements of the near surface upwelling radiation in the infrared window region is presented. As reflected sky radiation adds substantial spectral variability to the otherwise spectrally smooth surface radiation, an appropriate estimate of surface emissivity allows the measured upwelling radiation to be corrected for the reflected sky component. The remaining radiation, together with the estimated surface emissivity, yields an estimate of the sea surface temperature. Measurements from an ocean pier in the Baltic Sea in October 1995 indicate an accuracy of about 0.1 K for the sea surface temperature thus derived. A strong sea surface skin effect of about 0.6 K is found in that particular case.

  12. Age-surface temperature estimation model: When will oil palm plantation reach the same surface temperature as natural forest?

    Science.gov (United States)

    Rushayati, S. B.; Hermawan, R.; Meilani, R.

    2017-01-01

    Oil palm plantation has often been accused as the cause of global warming. However, along with its growth, it would be able to decrease surface temperature. The question is ‘when will the plantation be able to reach the same surface temperature as natural forest’. This research aimed to estimate the age of oil palm plantation that create similar surface temperature to those in natural forest (land cover before the opening and planting of oil palm). The method used in this research was spatial analysis of land cover and surface temperature distribution. Based on the spatial analysis of surface temperature, five points was randomly taken from each planting age (age 1 15 years). Linear regression was then employed in the analysis. The linear regression formula between surface temperature and age of oil palm plantation was Y = 26.002 – 0.1237X. Surface temperature will decrease as much as 0.1237 ° C with one year age growth oil palm. Surface temperature that was similar to the initial temperature, when the land cover was natural forest (23.04 °C), was estimated to occur when the oil palm plantation reach the age 24 year.

  13. Assimilating soil moisture into an Earth System Model

    Science.gov (United States)

    Stacke, Tobias; Hagemann, Stefan

    2017-04-01

    Several modelling studies reported potential impacts of soil moisture anomalies on regional climate. In particular for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. However, it is not clear yet whether or not soil moisture anomalies affect climate also on larger temporal and spatial scales. In an earlier study, we showed that soil moisture anomalies can persist for several seasons in the deeper soil layers of a land surface model. Additionally, those anomalies can influence root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite for predictability, namely the existence of long term memory, is evident for simulated soil moisture and might be exploited to improve climate predictions. The second prerequisite is the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for decadal simulations, we implemented a soil moisture assimilation scheme into the Max-Planck Institute for Meteorology's Earth System Model (MPI-ESM). The assimilation scheme is based on a simple nudging algorithm and updates the surface soil moisture state once per day. In our experiments, the MPI-ESM is used which includes model components for the interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states. First analyses are focused on the impact of the assimilation on land surface variables and reveal distinct differences in the long-term mean values between wet and dry state simulations. Precipitation, evapotranspiration and runoff are larger in the wet state compared to the dry state, resulting in an increased moisture transport from the land to atmosphere and ocean. Consequently, surface temperatures are lower in the wet state simulations by more than one Kelvin. In terms of spatial pattern

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

    Science.gov (United States)

    Lipton, Alan E.

    1992-03-01

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

  15. DasPy – Open Source Multivariate Land Data Assimilation Framework with High Performance Computing

    Science.gov (United States)

    Han, Xujun; Li, Xin; Montzka, Carsten; Kollet, Stefan; Vereecken, Harry; Hendricks Franssen, Harrie-Jan

    2015-04-01

    Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. Multivariate data assimilation refers to the simultaneous assimilation of observation data for multiple model state variables into a simulation model. Our main motivation was to develop an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with C++ and Fortran language. This system has been evaluated in several soil moisture, L-band brightness temperature and land surface temperature assimilation studies. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be represented by perturbed atmospheric forcings, perturbed soil and vegetation properties and model initial conditions. The CLM4.5 (Community Land Model) was integrated as the model operator. The CMEM (Community Microwave Emission Modelling Platform), COSMIC (COsmic-ray Soil Moisture Interaction Code) and the two source formulation were integrated as observation operators for assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy is parallelized using the hybrid MPI (Message Passing Interface) and OpenMP (Open Multi-Processing) techniques. All the input and output data flow is organized efficiently using the commonly used NetCDF file

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

    Science.gov (United States)

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

    2016-04-01

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

  17. Altimeter data assimilation in the tropical Indian Ocean using water property conserving scheme

    Indian Academy of Sciences (India)

    Bhasha M Mankad; Rashmi Sharma; Sujit Basu; P K Pal

    2012-02-01

    Altimeter data have been assimilated in an ocean general circulation model using the water property conserving scheme. Two runs of the model have been conducted for the year 2004. In one of the runs, altimeter data have been assimilated sequentially, while in another run, assimilation has been suppressed. Assimilation has been restricted to the tropical Indian Ocean. An assessment of the strength of the scheme has been carried out by comparing the sea surface temperature (SST), simulated in the two runs, with in situ derived as well as remotely sensed observations of the same quantity. It has been found that the assimilation exhibits a significant positive impact on the simulation of SST. The subsurface effect of the assimilation could be judged by comparing the model simulated depth of the 20°C isotherm (hereafter referred to as D20), as a proxy of the thermocline depth, with the same quantity estimated from ARGO observations. In this case also, the impact is noteworthy. Effect on the dynamics has been judged by comparison of simulated surface current with observed current at a moored buoy location, and finally the impact on model sea level forecast in a free run after assimilation has been quantified in a representative example.

  18. Evaluation of MODIS Land Surface Temperature with In Situ Snow Surface Temperature from CREST-SAFE

    Science.gov (United States)

    Perez Diaz, C. L.; Lakhankar, T.; Romanov, P.; Munoz, J.; Khanbilvardi, R.; Yu, Y.

    2016-12-01

    This paper presents the procedure and results of a temperature-based validation approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) product provided by the National Aeronautics and Space Administration (NASA) Terra and Aqua Earth Observing System satellites using in situ LST observations recorded at the Cooperative Remote Sensing Science and Technology Center - Snow Analysis and Field Experiment (CREST-SAFE) during the years of 2013 (January-April) and 2014 (February-April). A total of 314 day and night clear-sky thermal images, acquired by the Terra and Aqua satellites, were processed and compared to ground-truth data from CREST-SAFE with a frequency of one measurement every 3 min. Additionally, this investigation incorporated supplementary analyses using meteorological CREST-SAFE in situ variables (i.e. wind speed, cloud cover, incoming solar radiation) to study their effects on in situ snow surface temperature (T-skin) and T-air. Furthermore, a single pixel (1km2) and several spatially averaged pixels were used for satellite LST validation by increasing the MODIS window size to 5x5, 9x9, and 25x25 windows for comparison. Several trends in the MODIS LST data were observed, including the underestimation of daytime values and nighttime values. Results indicate that, although all the data sets (Terra and Aqua, diurnal and nocturnal) showed high correlation with ground measurements, day values yielded slightly higher accuracy ( 1°C), both suggesting that MODIS LST retrievals are reliable for similar land cover classes and atmospheric conditions. Results from the CREST-SAFE in situ variables' analyses indicate that T-air is commonly higher than T-skin, and that a lack of cloud cover results in: lower T-skin and higher T-air minus T-skin difference (T-diff). Additionally, the study revealed that T-diff is inversely proportional to cloud cover, wind speed, and incoming solar radiation. Increasing the MODIS window size

  19. Estimation of minimum surface temperature at stage ll (Short Communication

    Directory of Open Access Journals (Sweden)

    A. P. Dimri

    2001-04-01

    Full Text Available Forecasting minimum surface temperature at a station, Stage II, located in mountainous region requires information on the meteorological fields. An attempt has been made to develop a statistical model for forecasting minimum temperature at ground level using previous years' data. Surface data were collected at StageII (longitude 73 oB, latitude 34 oN, and altitude 2650 m. Atmospheric variables are influenced by complex orography and surface features to a great extent. In the present study, statistical relationship between atmosphere parameters and minimum temperature at the site has been established. Multivariate linear regression analysis has been used to establish the relationship to predict the minimum surface temperature for the following day. A comparison between the observed and the calculated forecast minimum temperature has been made. Most of the cases are well predicted (multiple correlation coefficient of 0.94.

  20. Impact of assimilation window length on diurnal features in a Mars atmospheric analysis

    Directory of Open Access Journals (Sweden)

    Yongjing Zhao

    2015-05-01

    Full Text Available Effective simulation of diurnal variability is an important aspect of many geophysical data assimilation systems. For the Martian atmosphere, thermal tides are particularly prominent and contribute much to the Martian atmospheric circulation, dynamics and dust transport. To study the Mars diurnal variability and Mars thermal tides, the Geophysical Fluid Dynamics Laboratory Mars Global Climate Model with the 4D-local ensemble transform Kalman filter (4D-LETKF is used to perform an analysis assimilating spacecraft temperature retrievals. We find that the use of a ‘traditional’ 6-hr assimilation cycle induces spurious forcing of a resonantly enhanced semi-diurnal Kelvin waves represented in both surface pressure and mid-level temperature by forming a wave 4 pattern in the diurnal averaged analysis increment that acts as a ‘topographic’ stationary forcing. Different assimilation window lengths in the 4D-LETKF are introduced to remove the artificially induced resonance. It is found that short assimilation window lengths not only remove the spurious resonance, but also push the migrating semi-diurnal temperature variation at 50 Pa closer to the estimated ‘true’ tides even in the absence of a radiatively active water ice cloud parameterisation. In order to compare the performance of different assimilation window lengths, short-term to mid-range forecasts based on the hour 00 and 12 assimilation are evaluated and compared. Results show that during Northern Hemisphere summer, it is not the assimilation window length, but the radiatively active water ice clouds that influence the model prediction. A ‘diurnal bias correction’ that includes bias correction fields dependent on the local time is shown to effectively reduce the forecast root mean square differences between forecasts and observations, compensate for the absence of water ice cloud parameterisation and enhance Martian atmosphere prediction. The implications of these results for

  1. North American regional climate reconstruction from ground surface temperature histories

    Science.gov (United States)

    Jaume-Santero, Fernando; Pickler, Carolyne; Beltrami, Hugo; Mareschal, Jean-Claude

    2016-12-01

    Within the framework of the PAGES NAm2k project, 510 North American borehole temperature-depth profiles were analyzed to infer recent climate changes. To facilitate comparisons and to study the same time period, the profiles were truncated at 300 m. Ground surface temperature histories for the last 500 years were obtained for a model describing temperature changes at the surface for several climate-differentiated regions in North America. The evaluation of the model is done by inversion of temperature perturbations using singular value decomposition and its solutions are assessed using a Monte Carlo approach. The results within 95 % confidence interval suggest a warming between 1.0 and 2.5 K during the last two centuries. A regional analysis, composed of mean temperature changes over the last 500 years and geographical maps of ground surface temperatures, show that all regions experienced warming, but this warming is not spatially uniform and is more marked in northern regions.

  2. Ground-based measurement of surface temperature and thermal emissivity

    Science.gov (United States)

    Owe, M.; Van De Griend, A. A.

    1994-01-01

    Motorized cable systems for transporting infrared thermometers have been used successfully during several international field campaigns. Systems may be configured with as many as four thermal sensors up to 9 m above the surface, and traverse a 30 m transect. Ground and canopy temperatures are important for solving the surface energy balance. The spatial variability of surface temperature is often great, so that averaged point measurements result in highly inaccurate areal estimates. The cable systems are ideal for quantifying both temporal and spatial variabilities. Thermal emissivity is also necessary for deriving the absolute physical temperature, and measurements may be made with a portable measuring box.

  3. Data Assimilation and Model Evaluation Experiment Datasets.

    Science.gov (United States)

    Lai, Chung-Chieng A.; Qian, Wen; Glenn, Scott M.

    1994-05-01

    The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMÉE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets.The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: 1)collection of observational data; 2) analysis and interpretation; 3) interpolation using the Optimum Thermal Interpolation System package; 4) quality control and re-analysis; and 5) data archiving and software documentation.The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement.Suggestions for DAMEE data usages include 1) ocean modeling and data assimilation studies, 2) diagnosis and theorectical studies, and 3) comparisons with locally detailed observations.

  4. Effect of milling temperatures on surface area, surface energy and cohesion of pharmaceutical powders.

    Science.gov (United States)

    Shah, Umang V; Wang, Zihua; Olusanmi, Dolapo; Narang, Ajit S; Hussain, Munir A; Tobyn, Michael J; Heng, Jerry Y Y

    2015-11-10

    Particle bulk and surface properties are influenced by the powder processing routes. This study demonstrates the effect of milling temperatures on the particle surface properties, particularly surface energy and surface area, and ultimately on powder cohesion. An active pharmaceutical ingredient (API) of industrial relevance (brivanib alaninate, BA) was used to demonstrate the effect of two different, but most commonly used milling temperatures (cryogenic vs. ambient). The surface energy of powders milled at both cryogenic and room temperatures increased with increasing milling cycles. The increase in surface energy could be related to the generation of surface amorphous regions. Cohesion for both cryogenic and room temperature milled powders was measured and found to increase with increasing milling cycles. For cryogenic milling, BA had a surface area ∼ 5× higher than the one obtained at room temperature. This was due to the brittle nature of this compound at cryogenic temperature. By decoupling average contributions of surface area and surface energy on cohesion by salinization post-milling, the average contribution of surface energy on cohesion for powders milled at room temperature was 83% and 55% at cryogenic temperature.

  5. TEMPERATURE CONTROL CIRCUIT FOR SURFACE ACOUSTIC WAVE (SAW RESONATORS

    Directory of Open Access Journals (Sweden)

    Zainab Mohamad Ashari

    2011-10-01

    Full Text Available Surface Acoustic Wave (SAW resonators are key components in oscillators, frequency synthesizers and transceivers. One of the drawbacks of SAW resonators are that its piezoelectric substrates are highly sensitive to ambient temperature resulting in performance degradation. This work propose a simple circuit design which stabalizes the temperature of the SAW resonator, making it independet of temperature change. This circuit is based on the oven control method which elevates the temperature of the resonator to a high temperature, making it tolerant to minor changes in ambient temperature.This circuit consist of a temperature sensor, heaters and a comparator which turn the heater on or off depending on the ambient temperature. Several SAW resonator were tested using this circuit. Experimental results indicate the temperature coefficient of frequency (TCF decreases from maximum of 130.44/°C to a minimum of -1.11/°C. 

  6. Regional assimilation of CO2 and δ13C surface data to assess terrestrial biosphere models under drought stress

    Science.gov (United States)

    van der Velde, I. R.; Miller, J. B.; Alden, C. B.; Andrews, A. E.; Schaefer, K. M.; Peters, W.; Tans, P. P.; Vaughn, B. H.; White, J. W. C.

    2016-12-01

    Observed atmospheric carbon dioxide (CO2) and the ratios of its stable isotopologue 13CO2/12CO2 (δ13C) contain unique signals of large-scale drought stress that affect the biosphere. When plants experience physiological stress due to heat and drought at leaf level they respond by closing their stomata. This is a safety mechanism that prevents excessive water loss at the expense of carbon uptake, and it changes the overall water-use efficiency. During photosynthesis, 12CO2 is preferentially assimilated over 13CO2, leaving the atmosphere enriched in 13CO2. Water stress slightly changes the ratio of 13CO2 and 12CO2 molecules being removed from the atmosphere, i.e., a reduction of canopy isotope discrimination (Δ), and its changes are evident in atmospheric δ13C.To improve our understanding of the coupled vegetation-atmosphere system we are developing an ensemble Kalman filter assimilation of high precision measurements of CO2 and δ13C from air samples collected over North America. It uses footprints provided by WRF-STILT that allows for efficient atmospheric transport simulations on a much higher horizontal resolution than with a global Eulerian transport model. To force consistency with atmospheric CO2 and δ13C observations we will optimize regional net terrestrial CO2 exchange (NEE) and Δ from a terrestrial biosphere model. We will carefully evaluate the sensitivity of the optimized parameters to uncertainties in the terrestrial biosphere fluxes, observations, time/space aggregation methods, and boundary conditions. Our main questions are: (i) what signal-to-noise in the data, as interpreted by the model, is large enough to robustly estimate Δ and NEE? and (ii) how do the optimized NEE and Δ that are based on the atmospheric constraint compare with the predicted NEE and Δ that are based on biophysical parameterizations? Our ability to accurately predict the responses of the terrestrial biosphere to changing humidity and soil moisture regimes is currently

  7. Snow multivariable data assimilation for hydrological predictions in mountain areas

    Science.gov (United States)

    Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

    2016-04-01

    The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground

  8. Mapping the body surface temperature of cattle by infrared thermography.

    Science.gov (United States)

    Salles, Marcia Saladini Vieira; da Silva, Suelen Corrêa; Salles, Fernando André; Roma, Luiz Carlos; El Faro, Lenira; Bustos Mac Lean, Priscilla Ayleen; Lins de Oliveira, Celso Eduardo; Martello, Luciane Silva

    2016-12-01

    Infrared thermography (IRT) is an alternative non-invasive method that has been studied as a tool for identifying many physiological and pathological processes related to changes in body temperature. The objective of the present study was to evaluate the body surface temperature of Jersey dairy cattle in a thermoneutral environment in order to contribute to the determination of a body surface temperature pattern for animals of this breed in a situation of thermal comfort. Twenty-four Jersey heifers were used over a period of 35 days at APTA Brazil. Measurements were performed on all animals, starting with the physiological parameters. Body surface temperature was measured by IRT collecting images in different body regions: left and right eye area, right and left eye, caudal left foreleg, cranial left foreleg, right and left flank, and forehead. High correlations were observed between temperature and humidity index (THI) and right flank, left flank and forehead temperatures (0.85, 0.81, and 0.81, respectively). The IRT variables that exhibited the five highest correlation coefficients in principal component 1 were, in decreasing order: forehead (0.90), right flank (0.87), left flank (0.84), marker 1 caudal left foreleg (0.83), marker 2 caudal left foreleg (0.74). The THI showed a high correlation coefficient (0.88) and moderate to low correlations were observed for the physiological variables rectal temperature (0.43), and respiratory frequency (0.42). The thermal profile obtained indicates a surface temperature pattern for each region studied in a situation of thermal comfort and may contribute to studies investigating body surface temperature. Among the body regions studied, IRT forehead temperature showed the highest association with rectal temperature, and forehead and right and left flank temperatures are strongly associated with THI and may be adopted in future studies on thermoregulation and body heat production.

  9. eMODIS Global Land Surface Temperature Version 6

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — The EROS Moderate Resolution Imaging Spectroradiometer (eMODIS) Aqua Land Surface Temperature (LST) product is similar to the Land Processes Distributed Active...

  10. 2002 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

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

  11. 2003 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

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

  12. Sea surface temperature anomalies in the Arabian Sea

    Digital Repository Service at National Institute of Oceanography (India)

    RameshKumar, M.R.

    . Further analysis has shown that the sea surface anomalies are well correlated to the anomalies of air temperature and latent heat flux values; whereas they are least correlated to the anomalies of wind stress and net radiation values, except over...

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

    African Journals Online (AJOL)

    Dr-Adeline

    2 National Authority for Remote Sensing and Space Sciences, Cairo, Egypt. 3University of ... Keywords: Urban growth, urban heat Island, land surface temperatures, satellite remote sensing .... observed target includes green vegetation or not.

  14. Global 1-km Sea Surface Temperature (G1SST)

    Data.gov (United States)

    National Aeronautics and Space Administration — JPL OurOcean Portal: A daily, global Sea Surface Temperature (SST) data set is produced at 1-km (also known as ultra-high resolution) by the JPL ROMS (Regional Ocean...

  15. COBE-SST2 Sea Surface Temperature and Ice

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A new sea surface temperature (SST) analysis on a centennial time scale is presented. The dataset starts in 1850 with monthly 1x1 means and is periodically updated....

  16. Surface layer temperature inversion in the Arabian Sea during winter

    Digital Repository Service at National Institute of Oceanography (India)

    Pankajakshan, T.; Ghosh, A.K.

    Surface layer temperature inversion in the south eastern Arabian Sea, during winter has been studied using Bathythermograph data collected from 1132 stations. It is found that the inversion in this area is a stable seasonal feature...

  17. Seasonal Sea Surface Temperature Averages, 1985-2001 - Direct Download

    Data.gov (United States)

    U.S. Geological Survey, Department of the Interior — This data set consists of four images showing seasonal sea surface temperature (SST) averages for the entire earth. Data for the years 1985-2001 are averaged to...

  18. 1996 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

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

  19. 2000 Average Monthly Sea Surface Temperature for California

    Data.gov (United States)

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

  20. OW NOAA Pathfinder/GAC Sea-Surface Temperature

    Data.gov (United States)

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

  1. OW NOAA AVHRR-GAC Sea-Surface Temperature

    Data.gov (United States)

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

  2. NOAA High-Resolution Sea Surface Temperature (SST) Analysis Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This archive covers two high resolution sea surface temperature (SST) analysis products developed using an optimum interpolation (OI) technique. The analyses have a...

  3. Tropical sea surface temperatures and the earth's orbital eccentricity cycles

    Digital Repository Service at National Institute of Oceanography (India)

    Gupta, S.M.; Fernandes, A.A.; Mohan, R.

    The tropical oceanic warm pools are climatologically important regions because their sea surface temperatures (SSTs) are positively related to atmospheric greenhouse effect and the cumulonimbus-cirrus cloud anvil. Such a warm pool is also present...

  4. Temperature Distribution Measurement of The Wing Surface under Icing Conditions

    Science.gov (United States)

    Isokawa, Hiroshi; Miyazaki, Takeshi; Kimura, Shigeo; Sakaue, Hirotaka; Morita, Katsuaki; Japan Aerospace Exploration Agency Collaboration; Univ of Notre Dame Collaboration; Kanagawa Institute of Technology Collaboration; Univ of Electro-(UEC) Team, Comm

    2016-11-01

    De- or anti-icing system of an aircraft is necessary for a safe flight operation. Icing is a phenomenon which is caused by a collision of supercooled water frozen to an object. For the in-flight icing, it may cause a change in the wing cross section that causes stall, and in the worst case, the aircraft would fall. Therefore it is important to know the surface temperature of the wing for de- or anti-icing system. In aerospace field, temperature-sensitive paint (TSP) has been widely used for obtaining the surface temperature distribution on a testing article. The luminescent image from the TSP can be related to the temperature distribution. (TSP measurement system) In icing wind tunnel, we measured the surface temperature distribution of the wing model using the TSP measurement system. The effect of icing conditions on the TSP measurement system is discussed.

  5. Marine ARM GPCI Investigation of Clouds Infrared Sea Surface Temperature Autonomous Radiometer (ISAR) Field Campaign Report

    Energy Technology Data Exchange (ETDEWEB)

    Reynolds, R. Michael [Remote Measurements & Research Company, Seattle, WA (United States); Long, Charles N. [National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.

    2016-01-10

    Sea surface temperature (SST) is one of the most appropriate and important climate parameters: a widespread increase is an indicator of global warming and modifications of the geographical distribution of SST are an extremely sensitive indicator of climate change. There is high demand for accurate, reliable, high-spatial-and-temporal-resolution SST measurements for the parameterization of ocean-atmosphere heat, momentum, and gas (SST is therefore critical to understanding the processes controlling the global carbon dioxide budget) fluxes, for detailed diagnostic and process-orientated studies to better understand the behavior of the climate system, as model boundary conditions, for assimilation into climate models, and for the rigorous validation of climate model output. In order to achieve an overall net flux uncertainty < 10 W/m2 (Bradley and Fairall, 2006), the sea surface (skin) temperature (SSST) must be measured to an error < 0.1 C and a precision of 0.05 C. Anyone experienced in shipboard meteorological measurements will recognize this is a tough specification. These demands require complete confidence in the content, interpretation, accuracy, reliability, and continuity of observational SST data—criteria that can only be fulfilled by the successful implementation of an ongoing data product validation strategy.

  6. High temperature photoelectron emission and surface photovoltage in semiconducting diamond

    Science.gov (United States)

    Williams, G. T.; Cooil, S. P.; Roberts, O. R.; Evans, S.; Langstaff, D. P.; Evans, D. A.

    2014-08-01

    A non-equilibrium photovoltage is generated in semiconducting diamond at above-ambient temperatures during x-ray and UV illumination that is sensitive to surface conductivity. The H-termination of a moderately doped p-type diamond (111) surface sustains a surface photovoltage up to 700 K, while the clean (2 × 1) reconstructed surface is not as severely affected. The flat-band C 1s binding energy is determined from 300 K measurement to be 283.87 eV. The true value for the H-terminated surface, determined from high temperature measurement, is (285.2 ± 0.1) eV, corresponding to a valence band maximum lying 1.6 eV below the Fermi level. This is similar to that of the reconstructed (2 × 1) surface, although this surface shows a wider spread of binding energy between 285.2 and 285.4 eV. Photovoltage quantification and correction are enabled by real-time photoelectron spectroscopy applied during annealing cycles between 300 K and 1200 K. A model is presented that accounts for the measured surface photovoltage in terms of a temperature-dependent resistance. A large, high-temperature photovoltage that is sensitive to surface conductivity and photon flux suggests a new way to use moderately B-doped diamond in voltage-based sensing devices.

  7. Temperature Compensation of Surface Acoustic Waves on Berlinite

    Science.gov (United States)

    Searle, David Michael Marshall

    The surface acoustic wave properties of Berlinite (a-AlPO4) have been investigated theoretically and experimentally, for a variety of crystallographic orientations, to evaluate its possible use as a substrate material for temperature compensated surface acoustic wave devices. A computer program has been developed to calculate the surface wave properties of a material from its elastic, piezoelectric, dielectric and lattice constants and their temperature derivatives. The program calculates the temperature coefficient of delay, the velocity of the surface wave, the direction of power flow and a measure of the electro-mechanical coupling. These calculations have been performed for a large number of orientations using a modified form of the data given by Chang and Barsch for Berlinite and predict several new temperature compensated directions. Experimental measurements have been made of the frequency-temperature response of a surface acoustic wave oscillator on an 80° X axis boule cut which show it to be temperature compensated in qualitative agreement with the theoretical predictions. This orientation shows a cubic frequency-temperature dependence instead of the expected parabolic response. Measurements of the electro-mechanical coupling coefficient k gave a value lower than predicted. Similar measurements on a Y cut plate gave a value which is approximately twice that of ST cut quartz, but again lower than predicted. The surface wave velocity on both these cuts was measured to be slightly higher than predicted by the computer program. Experimental measurements of the lattice parameters a and c are also presented for a range of temperatures from 25°C to just above the alpha-beta transition at 584°C. These results are compared with the values obtained by Chang and Barsch. The results of this work indicate that Berlinite should become a useful substrate material for the construction of temperature compensated surface acoustic wave devices.

  8. SURFACE TEMPERATURES ON TITAN DURING NORTHERN WINTER AND SPRING

    Energy Technology Data Exchange (ETDEWEB)

    Jennings, D. E.; Cottini, V.; Nixon, C. A.; Achterberg, R. K.; Flasar, F. M.; Kunde, V. G.; Romani, P. N.; Samuelson, R. E. [Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Mamoutkine, A. [ADNET Systems, Inc., Bethesda, MD 20817 (United States); Gorius, N. J. P. [The Catholic University of America, Washington, DC 20064 (United States); Coustenis, A. [Laboratoire d’Etudes Spatiales et d’Instrumentation en Astrophysique (LESIA), Observatoire de Paris, CNRS, UPMC Univ. Paris 06, Univ. Paris-Diderot, 5, place Jules Janssen, F-92195 Meudon Cedex (France); Tokano, T., E-mail: donald.e.jennings@nasa.gov [Universität zu Köln, Albertus-Magnus-Platz, D-50923 Köln (Germany)

    2016-01-01

    Meridional brightness temperatures were measured on the surface of Titan during the 2004–2014 portion of the Cassini mission by the Composite Infrared Spectrometer. Temperatures mapped from pole to pole during five two-year periods show a marked seasonal dependence. The surface temperature near the south pole over this time decreased by 2 K from 91.7 ± 0.3 to 89.7 ± 0.5 K while at the north pole the temperature increased by 1 K from 90.7 ± 0.5 to 91.5 ± 0.2 K. The latitude of maximum temperature moved from 19 S to 16 N, tracking the sub-solar latitude. As the latitude changed, the maximum temperature remained constant at 93.65 ± 0.15 K. In 2010 our temperatures repeated the north–south symmetry seen by Voyager one Titan year earlier in 1980. Early in the mission, temperatures at all latitudes had agreed with GCM predictions, but by 2014 temperatures in the north were lower than modeled by 1 K. The temperature rise in the north may be delayed by cooling of sea surfaces and moist ground brought on by seasonal methane precipitation and evaporation.

  9. Temperature dependence of surface enhanced Raman scattering on C70

    Institute of Scientific and Technical Information of China (English)

    GAO Ying; Zhang Zhenlong; DU Yinxiao; DONG Hua; MO Yujun

    2005-01-01

    The temperature dependence of surface enhanced Raman scattering of the C70 molecule is reported.The Raman scattering of C70 molecules adsorbed on the surface of a silver mirror was measured at different temperatures. The experimental results indicate that the relative intensities of the Raman features vary with the temperature of the sample. When the temperature decreases from room temperature to 0℃, the relative intensities of certain Raman bands decrease abruptly. If we take the strongest band 1565cm-1 as a standard value 100, the greatest decrease approaches to 43%. However, with the further decrease in the temperature these relative intensities increase and resume the value at room temperature. And such a temperature dependence is reversible. Our results show that the adsorption state of the C70 molecules on the silver surface around 0℃changes greatly with the temperature, resulting in a decrease in relative intensities for some main Raman features of C70molecule. When the temperature is lower than 0℃, the adsorption state changes continually and more slowly. Synchronously, eight new Raman featu res, which have not ever been reported in literature, are observed in our experiment and this enriches the basic information of the vibrational modes for C70 molecule.

  10. Optimal Spectral Decomposition (OSD) for Ocean Data Assimilation

    Science.gov (United States)

    2015-01-01

    tropical North Atlantic from the Argo float data (Chu et al. 2007), and temporal and spatial variability of global upper-ocean heat content (Chu 2011...been spun up from rest and clima - tological annual mean (temperature and salinity) with the daily climatological surface forcing from the CORE, ver...regions and in the FIG. 7. Comparison between the assimilation and nonassimilation runs of the temporally varying basinwide (a) RMSE and (b) BIAS. 10

  11. Sea Surface Temperature from EUMETSAT Including Sentinel-3 SLSTR

    Science.gov (United States)

    O'Carroll, Anne; Bonekamp, Hans; Montagner, Francois; Santacesaria, Vincenzo; Tomazic, Igor

    2015-12-01

    The paper gives an overview of sea surface temperature (SST) activities at EUMETSAT including information on SST planned from the Sea and Land Surface Temperature Radiometer (SLSTR). Operational oceanography activities within the Marine Applications group at EUMETSAT continue with a focus on SST, sea surface winds, sea-ice products, radiative fluxes, significant wave height and sea surface topography. These are achieved through the mandatory, optional and third-party programmes, and for some products with the EUMETSAT Ocean and Sea-Ice Satellite Application Facility (OSI SAF). Progress towards products from sea-ice surface temperature, ocean colour products, turbidity and aerosol optical depth over water continue. Information on oceanography products from EUMETSAT can be found through the product navigator (http://navigator.eumetsat.int). EUMETSAT have been collaborating with ESA for a number of years on the development of SST for SLSTR.

  12. Assimilation scheme of the Mediterranean Forecasting System: operational implementation

    Directory of Open Access Journals (Sweden)

    E. Demirov

    Full Text Available This paper describes the operational implementation of the data assimilation scheme for the Mediterranean Forecasting System Pilot Project (MFSPP. The assimilation scheme, System for Ocean Forecast and Analysis (SOFA, is a reduced order Optimal Interpolation (OI scheme. The order reduction is achieved by projection of the state vector into vertical Empirical Orthogonal Functions (EOF. The data assimilated are Sea Level Anomaly (SLA and temperature profiles from Expandable Bathy Termographs (XBT. The data collection, quality control, assimilation and forecast procedures are all done in Near Real Time (NRT. The OI is used intermittently with an assimilation cycle of one week so that an analysis is produced once a week. The forecast is then done for ten days following the analysis day. The root mean square (RMS between the model forecast and the analysis (the forecast RMS is below 0.7°C in the surface layers and below 0.2°C in the layers deeper than 200 m for all the ten forecast days. The RMS between forecast and initial condition (persistence RMS is higher than forecast RMS after the first day. This means that the model improves forecast with respect to persistence. The calculation of the misfit between the forecast and the satellite data suggests that the model solution represents well the main space and time variability of the SLA except for a relatively short period of three – four weeks during the summer when the data show a fast transition between the cyclonic winter and anti-cyclonic summer regimes. This occurs in the surface layers that are not corrected by our assimilation scheme hypothesis. On the basis of the forecast skill scores analysis, conclusions are drawn about future improvements.

    Key words. Oceanography; general (marginal and semi-enclosed seas; numerical modeling; ocean prediction

  13. A model of the ground surface temperature for micrometeorological analysis

    Science.gov (United States)

    Leaf, Julian S.; Erell, Evyatar

    2017-07-01

    Micrometeorological models at various scales require ground surface temperature, which may not always be measured in sufficient spatial or temporal detail. There is thus a need for a model that can calculate the surface temperature using only widely available weather data, thermal properties of the ground, and surface properties. The vegetated/permeable surface energy balance (VP-SEB) model introduced here requires no a priori knowledge of soil temperature or moisture at any depth. It combines a two-layer characterization of the soil column following the heat conservation law with a sinusoidal function to estimate deep soil temperature, and a simplified procedure for calculating moisture content. A physically based solution is used for each of the energy balance components allowing VP-SEB to be highly portable. VP-SEB was tested using field data measuring bare loess desert soil in dry weather and following rain events. Modeled hourly surface temperature correlated well with the measured data (r 2 = 0.95 for a whole year), with a root-mean-square error of 2.77 K. The model was used to generate input for a pedestrian thermal comfort study using the Index of Thermal Stress (ITS). The simulation shows that the thermal stress on a pedestrian standing in the sun on a fully paved surface, which may be over 500 W on a warm summer day, may be as much as 100 W lower on a grass surface exposed to the same meteorological conditions.

  14. Determination of temperature of moving surface by sensitivity analysis

    CERN Document Server

    Farhanieh, B

    2002-01-01

    In this paper sensitivity analysis in inverse problem solutions is employed to estimate the temperature of a moving surface. Moving finite element method is used for spatial discretization. Time derivatives are approximated using Crank-Nicklson method. The accuracy of the solution is assessed by simulation method. The convergence domain is investigated for the determination of the temperature of a solid fuel.

  15. A new interpolation method for Antarctic surface temperature

    Institute of Scientific and Technical Information of China (English)

    Yetang Wang; Shugui Hou

    2009-01-01

    We propose a new methodology for the spatial interpolation of annual mean temperature into a regular grid with a geographic resolution of 0.01° for Antarctica by applying a recent compilation of the Antarctic temperature data.A multiple linear regression model of the dependence of temperature on some geographic parameters (i.e.,latitude,longitude,and elevation) is proposed empirically,and the kriging method is used to determine the spatial distribution of regional and local deviations from the temperature calculated from the multiple linear regression model.The modeled value and residual grids are combined to derive a high-resolution map of surface air temperature.The performance of our new methodology is superior to a variety of benchmark methods (e.g.,inverse distance weighting,kriging,and spline methods) via cross-validation techniques.Our simulation resembles well with those distinct spatial features of surface temperature,such as the decrease in annual mean surface temperature with increasing latitude and the distance away from the coast line;and it also reveals the complex topographic effects on the spatial distribution of surface temperature.

  16. Analysis of Anomaly in Land Surface Temperature Using MODIS Products

    Science.gov (United States)

    Yorozu, K.; Kodama, T.; Kim, S.; Tachikawa, Y.; Shiiba, M.

    2011-12-01

    Atmosphere-land surface interaction plays a dominant role on the hydrologic cycle. Atmospheric phenomena cause variation of land surface state and land surface state can affect on atmosphereic conditions. Widely-known article related in atmospheric-land interaction was published by Koster et al. in 2004. The context of this article is that seasonal anomaly in soil moisture or soil surface temperature can affect summer precipitation generation and other atmospheric processes especially in middle North America, Sahel and south Asia. From not only above example but other previous research works, it is assumed that anomaly of surface state has a key factor. To investigate atmospheric-land surface interaction, it is necessary to analyze anomaly field in land surface state. In this study, soil surface temperature should be focused because it can be globally and continuously observed by satellite launched sensor. To land surface temperature product, MOD11C1 and MYD11C1 products which are kinds of MODIS products are applied. Both of them have 0.05 degree spatial resolution and daily temporal resolution. The difference of them is launched satellite, MOD11C1 is Terra and MYD11C1 is Aqua. MOD11C1 covers the latter of 2000 to present and MYD11C1 covers the early 2002 to present. There are unrealistic values on provided products even if daily product was already calibrated or corrected. For pre-analyzing, daily data is aggregated into 8-days data to remove irregular values for stable analysis. It was found that there are spatial and temporal distribution of 10-years average and standard deviation for each 8-days term. In order to point out extreme anomaly in land surface temperature, standard score for each 8-days term is applied. From the analysis of standard score, it is found there are large anomaly in land surface temperature around north China plain in early April 2005 and around Bangladesh in early May 2009.

  17. Radar Backscatter Across the Gulf Stream Sea Surface Temperature Front

    Science.gov (United States)

    Nghiem, S. V.; Li, F. K.; Walsh, E. J.; Lou, S. H.

    1998-01-01

    Ocean backscatter signatures were measured by the Jet Propulsion Laboratory airborne NUSCAT K(sub u)-band scatterometer across the Gulf Stream sea surface temperature front. The measurements were made during the Surface Wave Dynamics Experiment (SWADE) off the coast of Virginia and Maryland in the winter of 1991.

  18. estimation of land surface temperature of kaduna metropolis, nigeria

    African Journals Online (AJOL)

    Zaharaddeen et. al

    Understanding the spatial variation of Land Surface Temperature. (LST), will be ... positive correlation between mean of surface emissivity with date and ... deviation of 1.92 of LST and coefficient determinant R2 (0.46) show a ... (LST), as the prime and basic physical parameter of the earth's ..... thorough review of the paper.

  19. Indian Ocean sea surface temperature variability and change since 1960s: forcing and process

    Science.gov (United States)

    Han, W.; Meehl, G. A.; Hu, A.

    2005-12-01

    Indian Ocean sea surface temperature (SST) variability and change since 1960s are investigated using global coupled models,the Community Climate System Model version 3 (CCSM3) and parallel climate model (PCM). Results from the CCSM3 and a series of PCM experiments are analyzed in order to understand the roles played by internal variability, human-induced warming, and external forcing in causing the SST variations. To consolidate the model results, the simple Ocean model Data Assimilation (SODA) products are also analyzed. The results suggest that the SST in both the south and north Indian Ocean (IO) has an increasing trend. Overlying on this trend is decadal variability. Consistent with previous studies, the warming trend results mainly from the human-induced increased green house gases, which increase downward longwave fluxes. Interestingly, warming of the upper tropical and subtropical basins is accomanied by cooling in higher-latitudes in the Antarctic Circumpolar Current (ACC) region, which results from the reduced southward heat transports by weakened the subtropical cells (STCs). This colder, ACC water can enter the IO via deep layers in the south and then shoals upward to the thermocline layer in the tropical Indian Ocean, causing a distinct vertical structrure: with warming in the near surface and below the thermocline and cooling in the thermocline. The SST decadal variability, however, is caused primarily by external forcing, due to a combined effect of surface heat flux and lateral heat transport. Internal variability of the coupled system also plays a role.

  20. The room temperature preservation of filtered environmental DNA samples and assimilation into a phenol–chloroform–isoamyl alcohol DNA extraction

    Science.gov (United States)

    Renshaw, Mark A; Olds, Brett P; Jerde, Christopher L; McVeigh, Margaret M; Lodge, David M

    2015-01-01

    Current research targeting filtered macrobial environmental DNA (eDNA) often relies upon cold ambient temperatures at various stages, including the transport of water samples from the field to the laboratory and the storage of water and/or filtered samples in the laboratory. This poses practical limitations for field collections in locations where refrigeration and frozen storage is difficult or where samples must be transported long distances for further processing and screening. This study demonstrates the successful preservation of eDNA at room temperature (20 °C) in two lysis buffers, CTAB and Longmire's, over a 2-week period of time. Moreover, the preserved eDNA samples were seamlessly integrated into a phenol–chloroform–isoamyl alcohol (PCI) DNA extraction protocol. The successful application of the eDNA extraction to multiple filter membrane types suggests the methods evaluated here may be broadly applied in future eDNA research. Our results also suggest that for many kinds of studies recently reported on macrobial eDNA, detection probabilities could have been increased, and at a lower cost, by utilizing the Longmire's preservation buffer with a PCI DNA extraction. PMID:24834966

  1. The room temperature preservation of filtered environmental DNA samples and assimilation into a phenol-chloroform-isoamyl alcohol DNA extraction.

    Science.gov (United States)

    Renshaw, Mark A; Olds, Brett P; Jerde, Christopher L; McVeigh, Margaret M; Lodge, David M

    2015-01-01

    Current research targeting filtered macrobial environmental DNA (eDNA) often relies upon cold ambient temperatures at various stages, including the transport of water samples from the field to the laboratory and the storage of water and/or filtered samples in the laboratory. This poses practical limitations for field collections in locations where refrigeration and frozen storage is difficult or where samples must be transported long distances for further processing and screening. This study demonstrates the successful preservation of eDNA at room temperature (20 °C) in two lysis buffers, CTAB and Longmire's, over a 2-week period of time. Moreover, the preserved eDNA samples were seamlessly integrated into a phenol-chloroform-isoamyl alcohol (PCI) DNA extraction protocol. The successful application of the eDNA extraction to multiple filter membrane types suggests the methods evaluated here may be broadly applied in future eDNA research. Our results also suggest that for many kinds of studies recently reported on macrobial eDNA, detection probabilities could have been increased, and at a lower cost, by utilizing the Longmire's preservation buffer with a PCI DNA extraction. © 2014 The Authors. Molecular Ecology Resources Published by John Wiley & Sons Ltd.

  2. ESTIMATION OF PV MODULE SURFACE TEMPERATURE USING ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Can Coskun

    2016-12-01

    Full Text Available This study aimed to use the artificial neural network (ANN method to estimate the surface temperature of a photovoltaic (PV panel. Using the experimentally obtained PV data, the accuracy of the ANN model was evaluated. To train the artificial neural network (ANN, outer temperature solar radiation and wind speed values were inputs and surface temperature was an output. The ANN was used to estimate PV panel surface temperature. Using the Levenberg-Marquardt (LM algorithm the feed forward artificial neural network was trained. Two back propagation type ANN algorithms were used and their performance was compared with the estimate from the LM algorithm. To train the artificial neural network, experimental data were used for two thirds with the remaining third used for testing. Additionally scaled conjugate gradient (SCG back propagation and resilient back propagation (RB type ANN algorithms were used for comparison with the LM algorithm. The performances of these three types of artificial neural network were compared and mean error rates of between 0.005962 and 0.012177% were obtained. The best estimate was produced by the LM algorithm. Estimation of PV surface temperature with artificial neural networks provides better results than conventional correlation methods. This study showed that artificial neural networks may be effectively used to estimate PV surface temperature.

  3. Spatial Surface PM2.5 Concentration Estimates for Wildfire Smoke Plumes in the Western U.S. Using Satellite Retrievals and Data Assimilation Techniques

    Science.gov (United States)

    Loria Salazar, S. M.; Holmes, H.

    2015-12-01

    Health effects studies of aerosol pollution have been extended spatially using data assimilation techniques that combine surface PM2.5 concentrations and Aerosol Optical Depth (AOD) from satellite retrievals. While most of these models were developed for the dark-vegetated eastern U.S. they are being used in the semi-arid western U.S. to remotely sense atmospheric aerosol concentrations. These models are helpful to understand the spatial variability of surface PM2.5concentrations in the western U.S. because of the sparse network of surface monitoring stations. However, the models developed for the eastern U.S. are not robust in the western U.S. due to different aerosol formation mechanisms, transport phenomena, and optical properties. This region is a challenge because of complex terrain, anthropogenic and biogenic emissions, secondary organic aerosol formation, smoke from wildfires, and low background aerosol concentrations. This research concentrates on the use and evaluation of satellite remote sensing to estimate surface PM2.5 concentrations from AOD satellite retrievals over California and Nevada during the summer months of 2012 and 2013. The aim of this investigation is to incorporate a spatial statistical model that uses AOD from AERONET as well as MODIS, surface PM2.5 concentrations, and land-use regression to characterize spatial surface PM2.5 concentrations. The land use regression model uses traditional inputs (e.g. meteorology, population density, terrain) and non-traditional variables (e.g. FIre Inventory from NCAR (FINN) emissions and MODIS albedo product) to account for variability related to smoke plume trajectories and land use. The results will be used in a spatially resolved health study to determine the association between wildfire smoke exposure and cardiorespiratory health endpoints. This relationship can be used with future projections of wildfire emissions related to climate change and droughts to quantify the expected health impact.

  4. Mathematical model of the metal mould surface temperature optimization

    Energy Technology Data Exchange (ETDEWEB)

    Mlynek, Jaroslav, E-mail: jaroslav.mlynek@tul.cz; Knobloch, Roman, E-mail: roman.knobloch@tul.cz [Department of Mathematics, FP Technical University of Liberec, Studentska 2, 461 17 Liberec, The Czech Republic (Czech Republic); Srb, Radek, E-mail: radek.srb@tul.cz [Institute of Mechatronics and Computer Engineering Technical University of Liberec, Studentska 2, 461 17 Liberec, The Czech Republic (Czech Republic)

    2015-11-30

    The article is focused on the problem of generating a uniform temperature field on the inner surface of shell metal moulds. Such moulds are used e.g. in the automotive industry for artificial leather production. To produce artificial leather with uniform surface structure and colour shade the temperature on the inner surface of the mould has to be as homogeneous as possible. The heating of the mould is realized by infrared heaters located above the outer mould surface. The conceived mathematical model allows us to optimize the locations of infrared heaters over the mould, so that approximately uniform heat radiation intensity is generated. A version of differential evolution algorithm programmed in Matlab development environment was created by the authors for the optimization process. For temperate calculations software system ANSYS was used. A practical example of optimization of heaters locations and calculation of the temperature of the mould is included at the end of the article.

  5. Influence of Annealing Temperature on CZTS Thin Film Surface Properties

    Science.gov (United States)

    Feng, Wenmei; Han, Junfeng; Ge, Jun; Peng, Xianglin; Liu, Yunong; Jian, Yu; Yuan, Lin; Xiong, Xiaolu; Cha, Limei; Liao, Cheng

    2017-01-01

    In this work, copper zinc tin sulfide (CZTS) films were deposited by direct current sputtering and the samples were annealed in different oven-set temperatures and atmosphere (Ar and H2S). The surface evolution was investigated carefully by using scanning electron microscopy (SEM), Raman spectroscopy and x-ray photoelectron spectroscopy. The surface of the as-sputtered precursor contained little Cu and large amounts of Zn and Sn. The metallic precursor was continuous and compact without pinholes or cracks. With the increase of the temperature from room temperature to 250°C, Cu atoms diffused to the film surface to form Cu1- x S and covered other compounds. Some small platelets were smaller than 500 nm spreading randomly in the holes of the film surfaces. When the temperature reached 350°C, Zn and Sn atoms began to diffuse to the surface and react with S or Cu1- x S. At 400°C, SEM showed the melting of large particles and small particles with a size from 100 nm to 200 nm in the background of the film surface. Excess Zn segregated towards the surface regions and formed ZnS phase on the surface. In addition, the signal of sodium in the CZTS surface was observed above 400°C. At 600°C, a large amount of regular structures with clear edges and corners were observed in the film surface in SEM images. A clear recrystallized process on the surface was assumed from those observations.

  6. Climate Change Signal Analysis for Northeast Asian Surface Temperature

    Institute of Scientific and Technical Information of China (English)

    Jeong-Hyeong LEE; Byungsoo KIM; Keon-Tae SOHN; Won-Tae KOWN; Seung-Ki MIN

    2005-01-01

    Climate change detection, attribution, and prediction were studied for the surface temperature in the Northeast Asian region using NCEP/NCAR reanalysis data and three coupled-model simulations from ECHAM4/OPYC3, HadCM3, and CCCma GCMs (Canadian Centre for Climate Modeling and Analysis general circulation model). The Bayesian fingerprint approach was used to perform the detection and attribution test for the anthropogenic climate change signal associated with changes in anthropogenic carbon dioxide (CO2) and sulfate aerosol (SO42-) concentrations for the Northeast Asian temperature. It was shown that there was a weak anthropogenic climate change signal in the Northeast Asian temperature change. The relative contribution of CO2 and SOl- effects to total temperature change in Northeast Asia was quantified from ECHAM4/OPYC3 and CCCma GCM simulations using analysis of variance. For the observed temperature change for the period of 1959-1998, the CO2 effect contributed 10%-21% of the total variance and the direct cooling effect of SO42- played a less important role (0% 7%) than the CO2effect. The prediction of surface temperature change was estimated from the second CO2+SO24- scenario run of ECHAM4/OPYC3 which has the least error in the simulation of the present-day temperature field near the Korean Peninsula. The result shows that the area-mean surface temperature near the Korean Peninsula will increase by about 1.1° by the 2040s relative to the 1990s.

  7. How can we use MODIS land surface temperature to validate long-term urban model simulations?

    Science.gov (United States)

    Hu, Leiqiu; Brunsell, Nathaniel A.; Monaghan, Andrew J.; Barlage, Michael; Wilhelmi, Olga V.

    2014-03-01

    High spatial resolution urban climate modeling is essential for understanding urban climatology and predicting the human health impacts under climate change. Satellite thermal remote-sensing data are potential observational sources for urban climate model validation with comparable spatial scales, temporal consistency, broad coverage, and long-term archives. However, sensor view angle, cloud distribution, and cloud-contaminated pixels can confound comparisons between satellite land surface temperature (LST) and modeled surface radiometric temperature. The impacts of sensor view angles on urban LST values are investigated and addressed. Three methods to minimize the confounding factors of clouds are proposed and evaluated using 10years of Moderate Resolution Imaging Spectroradiometer (MODIS) data and simulations from the High-Resolution Land Data Assimilation System (HRLDAS) over Greater Houston, Texas, U.S. For the satellite cloud mask (SCM) method, prior to comparison, the cloud mask for each MODIS scene is applied to its concurrent HRLDAS simulation. For the max/min temperature (MMT) method, the 50 warmest days and coolest nights for each data set are selected and compared to avoid cloud impacts. For the high clear-sky fraction (HCF) method, only those MODIS scenes that have a high percentage of clear-sky pixels are compared. The SCM method is recommended for validation of long-term simulations because it provides the largest sample size as well as temporal consistency with the simulations. The MMT method is best for comparison at the extremes. And the HCF method gives the best absolute temperature comparison due to the spatial and temporal consistency between simulations and observations.

  8. A method for the determination of the hydraulic properties of soil from MODIS surface temperature for use in land-surface models

    Science.gov (United States)

    Gutmann, Ethan D.; Small, Eric E.

    2010-06-01

    Soil hydraulic properties (SHPs) play an important role in land-surface models, but their spatial distribution is poorly known, and it is not feasible to make field measurements of SHPs everywhere they are needed. In addition, the scale SHPs are measured on (10 cm) is substantially smaller than the scale at which land-surface models are run (>1 km). As a result, land-surface models need landscape hydraulic properties (LHPs), not SHPs. We present a method for identifying LHPs from MODIS surface temperatures. We calibrated LHPs in the Noah land-surface model using MODIS surface temperatures in 2005 at 14 sites from the Atmospheric Radiation Measurement Program (ARM) using locally observed forcing data from 2005. We then used observed flux data during this same time period for model verification. Next, we determined LHPs from MODIS surface temperature at five sites using High Resolution Land Data Assimilation forcing data from 2002. We then used these LHPS to run Noah with 2005 ARM forcing data and compared the output to the same observed 2005 fluxes. Fitting LHPs to MODIS data decreases the error in modeled latent heat flux from 98 W/m2 to 67 W/m2. Fitting LHPs to these same latent heat flux measurements decreases the error to 50 W/m2. Therefore, two thirds of the parameter estimation improvement from calibration to in situ flux data can be achieved using remotely sensed surface temperature. These results are insensitive to errors in other parameters. For example, changing albedo by 0.1 changes the saturated conductivity (Ks) by 10% and the van Genuchten "m" parameter by 1%. However, changing minimum canopy resistance by 40 s/m produced a significant but mutually compensating change in both Ks and "m."

  9. Comparison of MODIS Land Surface Temperature and Air Temperature over the Continental USA Meteorological Stations

    Science.gov (United States)

    Zhang, Ping; Bounoua, Lahouari; Imhoff, Marc L.; Wolfe, Robert E.; Thome, Kurtis

    2014-01-01

    The National Land Cover Database (NLCD) Impervious Surface Area (ISA) and MODIS Land Surface Temperature (LST) are used in a spatial analysis to assess the surface-temperature-based urban heat island's (UHIS) signature on LST amplitude over the continental USA and to make comparisons to local air temperatures. Air-temperature-based UHIs (UHIA), calculated using the Global Historical Climatology Network (GHCN) daily air temperatures, are compared with UHIS for urban areas in different biomes during different seasons. NLCD ISA is used to define urban and rural temperatures and to stratify the sampling for LST and air temperatures. We find that the MODIS LST agrees well with observed air temperature during the nighttime, but tends to overestimate it during the daytime, especially during summer and in nonforested areas. The minimum air temperature analyses show that UHIs in forests have an average UHIA of 1 C during the summer. The UHIS, calculated from nighttime LST, has similar magnitude of 1-2 C. By contrast, the LSTs show a midday summer UHIS of 3-4 C for cities in forests, whereas the average summer UHIA calculated from maximum air temperature is close to 0 C. In addition, the LSTs and air temperatures difference between 2006 and 2011 are in agreement, albeit with different magnitude.

  10. A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. Part 1; Overview

    Science.gov (United States)

    Crosson, William L.; Laymon, Charles A.; Inguva, Ramarao; Schamschula, Marius; Caulfield, John

    1998-01-01

    advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean

  11. Fiber-Optic Surface Temperature Sensor Based on Modal Interference

    Directory of Open Access Journals (Sweden)

    Frédéric Musin

    2016-07-01

    Full Text Available Spatially-integrated surface temperature sensing is highly useful when it comes to controlling processes, detecting hazardous conditions or monitoring the health and safety of equipment and people. Fiber-optic sensing based on modal interference has shown great sensitivity to temperature variation, by means of cost-effective image-processing of few-mode interference patterns. New developments in the field of sensor configuration, as described in this paper, include an innovative cooling and heating phase discrimination functionality and more precise measurements, based entirely on the image processing of interference patterns. The proposed technique was applied to the measurement of the integrated surface temperature of a hollow cylinder and compared with a conventional measurement system, consisting of an infrared camera and precision temperature probe. As a result, the optical technique is in line with the reference system. Compared with conventional surface temperature probes, the optical technique has the following advantages: low heat capacity temperature measurement errors, easier spatial deployment, and replacement of multiple angle infrared camera shooting and the continuous monitoring of surfaces that are not visually accessible.

  12. Assessment of broiler surface temperature variation when exposed to different air temperatures

    Directory of Open Access Journals (Sweden)

    GR Nascimento

    2011-12-01

    Full Text Available This study was conducted to determine the effect of the air temperature variation on the mean surface temperature (MST of 7- to 35-day-old broiler chickens using infrared thermometry to estimate MST, and to study surface temperature variation of the wings, head, legs, back and comb as affected by air temperature and broiler age. One hundred Cobb® broilers were used in the experiment. Starting on day 7, 10 birds were weekly selected at random, housed in an environmental chamber and reared under three distinct temperatures (18, 25 and 32 ºC to record their thermal profile using an infrared thermal camera. The recorded images were processed to estimate MST by selecting the whole area of the bird within the picture and comparing it with the values obtained using selected equations in literature, and to record the surface temperatures of the body parts. The MST estimated by infrared images were not statistically different (p > 0.05 from the values obtained by the equations. MST values significantly increased (p < 0.05 when the air temperature increased, but were not affected by bird age. However, age influenced the difference between MST and air temperature, which was highest on day 14. The technique of infrared thermal image analysis was useful to estimate the mean surface temperature of broiler chickens.

  13. Investigating the effect of surface water - groundwater interactions on stream temperature using Distributed temperature sensing and instream temperature model

    DEFF Research Database (Denmark)

    Karthikeyan, Matheswaran; Blemmer, Morten; Mortensen, Julie Flor;

    2011-01-01

    Surface water–groundwater interactions at the stream interface influences, and at times controls the stream temperature, a critical water property driving biogeochemical processes. This study investigates the effects of these interactions on temperature of Stream Elverdamsåen in Denmark using...... the Distributed Temperature Sensing (DTS) system and instream temperature modelling. Locations of surface water–groundwater interactions were identified from the temperature data collected over a 2-km stream reach using a DTS system with 1-m spatial and 5-min temporal resolution. The stream under consideration...... exhibits three distinct thermal regimes within a 2 km reach length due to two major interactions. An energy balance model is used to simulate the instream temperature and to quantify the effect of these interactions on the stream temperature. This research demonstrates the effect of reach level small scale...

  14. Uncertainties and shortcomings of ground surface temperature histories derived from inversion of temperature logs

    OpenAIRE

    Hartmann, Andreas; Rath, Volker

    2008-01-01

    Analysing borehole temperature data in terms of ground surface history can add useful information to reconstructions of past climates. Therefore, a rigorous assessment of uncertainties and error sources is a necessary prerequisite for the meaningful interpretation of such ground surface temperature histories. This study analyses the most prominent sources of uncertainty. The diffusive nature of the process makes the inversion relatively robust against incomplete knowledge of the thermal diffu...

  15. Effective Assimilation of Global Precipitation

    Science.gov (United States)

    Lien, G.; Kalnay, E.; Miyoshi, T.; Huffman, G. J.

    2012-12-01

    Assimilating precipitation observations by modifying the moisture and sometimes temperature profiles has been shown successful in forcing the model precipitation to be close to the observed precipitation, but only while the assimilation is taking place. After the forecast start, the model tends to "forget" the assimilation changes and lose their extra skill after few forecast hours. This suggests that this approach is not an efficient way to modify the potential vorticity field, since this is the variable that the model would remember. In this study, the ensemble Kalman filter (EnKF) method is used to effectively change the potential vorticity field by allowing ensemble members with better precipitation to receive higher weights. In addition to using an EnKF, two other changes in the precipitation assimilation process are proposed to solve the problems related to the highly non-Gaussian nature of the precipitation variable: a) transform precipitation into a Gaussian distribution based on its climatological distribution, and b) only assimilate precipitation at the location where some ensemble members have positive precipitation. The idea is first tested by the observing system simulation experiments (OSSEs) using SPEEDY, a simplified but realistic general circulation model. When the global precipitation is assimilated in addition to conventional rawinsonde observations, both the analyses and the medium range forecasts are significantly improved as compared to only having rawinsonde observations. The improvement is much reduced when only modifying the moisture field with the same approach, which shows the importance of the error covariance between precipitation and all other model variables. The effect of precipitation assimilation is larger in the Southern Hemisphere than that in the Northern Hemisphere because the Northern Hemisphere analyses are already accurate as a result of denser rawinsonde stations. Assimilation of precipitation using a more comprehensive

  16. TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic

    Directory of Open Access Journals (Sweden)

    P. Sakov

    2012-08-01

    Full Text Available We present a detailed description of TOPAZ4, the latest version of TOPAZ – a coupled ocean-sea ice data assimilation system for the North Atlantic Ocean and Arctic. It is the only operational, large-scale ocean data assimilation system that uses the ensemble Kalman filter. This means that TOPAZ features a time-evolving, state-dependent estimate of the state error covariance. Based on results from the pilot MyOcean reanalysis for 2003–2008, we demonstrate that TOPAZ4 produces a realistic estimate of the ocean circulation in the North Atlantic and the sea-ice variability in the Arctic. We find that the ensemble spread for temperature and sea-level remains fairly constant throughout the reanalysis demonstrating that the data assimilation system is robust to ensemble collapse. Moreover, the ensemble spread for ice concentration is well correlated with the actual errors. This indicates that the ensemble statistics provide reliable state-dependent error estimates – a feature that is unique to ensemble-based data assimilation systems. We demonstrate that the quality of the reanalysis changes when different sea surface temperature products are assimilated, or when in-situ profiles below the ice in the Arctic Ocean are assimilated. We find that data assimilation improves the match to independent observations compared to a free model. Improvements are particularly noticeable for ice thickness, salinity in the Arctic, and temperature in the Fram Strait, but not for transport estimates or underwater temperature. At the same time, the pilot reanalysis has revealed several flaws in the system that have degraded its performance. Finally, we show that a simple bias estimation scheme can effectively detect the seasonal or constant bias in temperature and sea-level.

  17. TOPAZ4: an ocean-sea ice data assimilation system for the North Atlantic and Arctic

    Directory of Open Access Journals (Sweden)

    P. Sakov

    2012-04-01

    Full Text Available We present a detailed description of TOPAZ4, the latest version of TOPAZ – a coupled ocean-sea ice data assimilation system for the North Atlantic Ocean and Arctic. It is the only operational, large-scale ocean data assimilation system that uses the ensemble Kalman filter. This means that TOPAZ features a time-evolving, state-dependent estimate of the state error covariance. Based on results from the pilot MyOcean reanalysis for 2003–2008, we demonstrate that TOPAZ4 produces a realistic estimate of the ocean circulation and the sea ice. We find that the ensemble spread for temperature and sea-level remains fairly constant throughout the reanalysis demonstrating that the data assimilation system is robust to ensemble collapse. Moreover, the ensemble spread for ice concentration is well correlated with the actual errors. This indicates that the ensemble statistics provide reliable state-dependent error estimates – a feature that is unique to ensemble-based data assimilation systems. We demonstrate that the quality of the reanalysis changes when different sea surface temperature products are assimilated, or when in situ profiles below the ice in the Arctic Ocean are assimilated. We find that data assimilation improves the match to independent observations compared to a free model. Improvements are particularly noticeable for ice thickness, salinity in the Arctic, and temperature in the Fram Strait, but not for transport estimates or underwater temperature. At the same time, the pilot reanalysis has revealed several flaws in the system that have degraded its performance. Finally, we show that a simple bias estimation scheme can effectively detect the seasonal or constant bias in temperature and sea-level.

  18. Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

    KAUST Repository

    Toye, Habib

    2017-05-26

    We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.

  19. Ensemble data assimilation in the Red Sea: sensitivity to ensemble selection and atmospheric forcing

    Science.gov (United States)

    Toye, Habib; Zhan, Peng; Gopalakrishnan, Ganesh; Kartadikaria, Aditya R.; Huang, Huang; Knio, Omar; Hoteit, Ibrahim

    2017-07-01

    We present our efforts to build an ensemble data assimilation and forecasting system for the Red Sea. The system consists of the high-resolution Massachusetts Institute of Technology general circulation model (MITgcm) to simulate ocean circulation and of the Data Research Testbed (DART) for ensemble data assimilation. DART has been configured to integrate all members of an ensemble adjustment Kalman filter (EAKF) in parallel, based on which we adapted the ensemble operations in DART to use an invariant ensemble, i.e., an ensemble Optimal Interpolation (EnOI) algorithm. This approach requires only single forward model integration in the forecast step and therefore saves substantial computational cost. To deal with the strong seasonal variability of the Red Sea, the EnOI ensemble is then seasonally selected from a climatology of long-term model outputs. Observations of remote sensing sea surface height (SSH) and sea surface temperature (SST) are assimilated every 3 days. Real-time atmospheric fields from the National Center for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) are used as forcing in different assimilation experiments. We investigate the behaviors of the EAKF and (seasonal-) EnOI and compare their performances for assimilating and forecasting the circulation of the Red Sea. We further assess the sensitivity of the assimilation system to various filtering parameters (ensemble size, inflation) and atmospheric forcing.

  20. Predicting East African spring droughts using Pacific and Indian Ocean sea surface temperature indices

    Directory of Open Access Journals (Sweden)

    C. Funk

    2014-03-01

    Full Text Available In southern Ethiopia, Eastern Kenya, and southern Somalia, poor boreal spring rains in 1999, 2000, 2004, 2007, 2008, 2009, and 2011 contributed to severe food insecurity and high levels of malnutrition. Predicting rainfall deficits in this region on seasonal and decadal time frames can help decision makers implement disaster risk reduction measures while guiding climate-smart adaptation and agricultural development. Building on recent research that links more frequent droughts in that region to a stronger Walker Circulation, warming in the Indo-Pacific warm pool, and an increased western Pacific sea surface temperature (SST gradient, we show that the two dominant modes of East African boreal spring rainfall variability are tied, respectively, to western-central Pacific and central Indian Ocean SST. Variations in these rainfall modes can be predicted using two previously defined SST indices – the West Pacific Gradient (WPG and Central Indian Ocean index (CIO, with the WPG and CIO being used, respectively, to predict the first and second rainfall modes. These simple indices can be used in concert with more sophisticated coupled modeling systems and land surface data assimilations to help inform early warning and guide climate outlooks.

  1. The statistical inhomogeneity of surface air temperature in global atmospheric reanalyses

    Science.gov (United States)

    Ferguson, C. R.; Lee, M. H.

    2015-12-01

    Recently, a new generation of so-called climate reanalyses has emerged, including the 161-year NOAA—Cooperative Institute for Research in Environmental Sciences (NOAA-CIRES) Twentieth Century Reanalysis Version 2c (20CR V2c), the 111-year ECMWF pilot reanalysis of the twentieth century (ERA-20C), and the 55-year JMA conventional reanalysis (JRA-55C). These reanalyses were explicitly designed to achieve improved homogeneity through assimilation of a fixed subset of (mostly surface) observations. We apply structural breakpoint analysis to evaluate inhomogeneity of the surface air temperature in these reanalyses (1851-2011). For the modern satellite era (1979-2013), we intercompare their inhomogeneity to that of all eleven available satellite reanalyses. Where possible, we distinguish between breakpoints that are likely linked to climate variability and those that are likely due to an artificial observational network shift. ERA-20C is found to be the most homogenous reanalysis, with 40% fewer artificial breaks than 20CR V2c. Despite its gains in homogeneity, continued improvements to ERA-20C are needed. In this presentation, we highlight the most spatially extensive artificial break events in ERA-20C.

  2. A study on WRF radar data assimilation for hydrological rainfall prediction

    Directory of Open Access Journals (Sweden)

    J. Liu

    2013-08-01

    Full Text Available Mesoscale numerical weather prediction (NWP models are gaining more attention in providing high-resolution rainfall forecasts at the catchment scale for real-time flood forecasting. The model accuracy is however negatively affected by the "spin-up" effect and errors in the initial and lateral boundary conditions. Synoptic studies in the meteorological area have shown that the assimilation of operational observations, especially the weather radar data, can improve the reliability of the rainfall forecasts from the NWP models. This study aims at investigating the potential of radar data assimilation in improving the NWP rainfall forecasts that have direct benefits for hydrological applications. The Weather Research and Forecasting (WRF model is adopted to generate 10 km rainfall forecasts for a 24 h storm event in the Brue catchment (135.2 km2 located in southwest England. Radar reflectivity from the lowest scan elevation of a C-band weather radar is assimilated by using the three-dimensional variational (3D-Var data-assimilation technique. Considering the unsatisfactory quality of radar data compared to the rain gauge observations, the radar data are assimilated in both the original form and an improved form based on a real-time correction ratio developed according to the rain gauge observations. Traditional meteorological observations including the surface and upper-air measurements of pressure, temperature, humidity and wind speed are also assimilated as a bench mark to better evaluate and test the potential of radar data assimilation. Four modes of data assimilation are thus carried out on different types/combinations of observations: (1 traditional meteorological data; (2 radar reflectivity; (3 corrected radar reflectivity; (4 a combination of the original reflectivity and meteorological data; and (5 a combination of the corrected reflectivity and meteorological data. The WRF rainfall forecasts before and after different modes of data

  3. A study on weather radar data assimilation for numerical rainfall prediction

    Directory of Open Access Journals (Sweden)

    J. Liu

    2012-09-01

    Full Text Available Mesoscale NWP model is gaining more attention in providing high-resolution rainfall forecasts at the catchment scale for real-time flood forecasting. The model accuracy is however negatively affected by the "spin-up" effect and errors in the initial and lateral boundary conditions. Synoptic studies in the meteorological area have shown that the assimilation of operational observations especially the weather radar data can improve the reliability of the rainfall forecasts from the NWP models. This study aims at investigating the potential of radar data assimilation in improving the NWP rainfall forecasts that have direct benefits for hydrological applications. The Weather Research and Forecasting (WRF model is adopted to generate 10 km rainfall forecasts for a 24 h storm event in the Brue catchment (135.2 km2 located in Southwest England. Radar reflectivity from the lowest scan elevation of a C-band weather radar is assimilated by using the three dimensional variational (3D-Var data assimilation technique. Considering the unsatisfactory quality of radar data compared to the rain gauges, the radar data is assimilated in both the original form and an improved form based on a real-time correction ratio developed according to the rain gauge observations. Traditional meteorological observations including the surface and upper-air measurements of pressure, temperature, humidity and wind speed are also assimilated as a bench mark to better evaluate and test the potential of radar data assimilation. Four modes of data assimilation are thus carried out on different types or combinations of observations: (1 traditional meteorological data; (2 radar reflectivity; (3 corrected radar reflectivity; (4 a combination of the original reflectivity and meteorological data; and (5 a combination of the corrected reflectivity and meteorological data. The WRF rainfall forecasts before and after different modes of data assimilation is evaluated by examining

  4. High-Temperature Surface-Acoustic-Wave Transducer

    Science.gov (United States)

    Zhao, Xiaoliang; Tittmann, Bernhard R.

    2010-01-01

    Aircraft-engine rotating equipment usually operates at high temperature and stress. Non-invasive inspection of microcracks in those components poses a challenge for the non-destructive evaluation community. A low-profile ultrasonic guided wave sensor can detect cracks in situ. The key feature of the sensor is that it should withstand high temperatures and excite strong surface wave energy to inspect surface/subsurface cracks. As far as the innovators know at the time of this reporting, there is no existing sensor that is mounted to the rotor disks for crack inspection; the most often used technology includes fluorescent penetrant inspection or eddy-current probes for disassembled part inspection. An efficient, high-temperature, low-profile surface acoustic wave transducer design has been identified and tested for nondestructive evaluation of structures or materials. The development is a Sol-Gel bismuth titanate-based surface-acoustic-wave (SAW) sensor that can generate efficient surface acoustic waves for crack inspection. The produced sensor is very thin (submillimeter), and can generate surface waves up to 540 C. Finite element analysis of the SAW transducer design was performed to predict the sensor behavior, and experimental studies confirmed the results. One major uniqueness of the Sol-Gel bismuth titanate SAW sensor is that it is easy to implement to structures of various shapes. With a spray coating process, the sensor can be applied to surfaces of large curvatures. Second, the sensor is very thin (as a coating) and has very minimal effect on airflow or rotating equipment imbalance. Third, it can withstand temperatures up to 530 C, which is very useful for engine applications where high temperature is an issue.

  5. Investigation of surface properties of high temperature nitrided titanium alloys

    Directory of Open Access Journals (Sweden)

    E. Koyuncu

    2009-12-01

    Full Text Available Purpose: The purpose of paper is to investigate surface properties of high temperature nitrided titanium alloys.Design/methodology/approach: In this study, surface modification of Ti6Al4V titanium alloy was made at various temperatures by plasma nitriding process. Plasma nitriding treatment was performed in 80% N2-20% H2 gas mixture, for treatment times of 2-15 h at the temperatures of 700-1000°C. Surface properties of plasma nitrided Ti6Al4V alloy were examined by metallographic inspection, X-Ray diffraction and Vickers hardness.Findings: Two layers were determined by optic inspection on the samples that were called the compound and diffusion layers. Compound layer contain TiN and Ti2N nitrides, XRD results support in this formations. Maximum hardness was obtained at 10h treatment time and 1000°C treatment temperature. Micro hardness tests showed that hardness properties of the nitrided samples depend on treatment time and temperature.Practical implications: Titanium and its alloys have very attractive properties for many industries. But using of titanium and its alloys is of very low in mechanical engineering applications because of poor tribological properties.Originality/value: The nitriding of titanium alloy surfaces using plasma processes has already reached the industrial application stage in the biomedical field.

  6. Surface Intermediates on Metal Electrodes at High Temperature

    DEFF Research Database (Denmark)

    Zachau-Christiansen, Birgit; Jacobsen, Torben; Bay, Lasse

    1997-01-01

    The mechanisms widely suggested for the O2-reduc-tion or H2-oxidation SOFC reactions involve inter-mediate O/H species adsorbed on the electrode surface. The presence of these intermediates is investigated by linear sweep voltammetry. In airat moderate temperatures (500øC) Pt in contact with YSZ ...... is covered with adsorbed oxygen which vanishes at high temperature (1000øC). On Ni (YSZ) a specific layer of NiO is observed abovethe equilibrium potential while no surface species can identified at SOFC anode conditions....

  7. Determination of sea surface temperatures from microwave and IR data

    Science.gov (United States)

    Rangaswamy, S.; Grover, J.

    1982-01-01

    Microwave measurements from the Nimbus 7 SMMR were used to derive the atmospheric precipitable water, which was then used to obtain the atmospheric correction for use with AVHRR thermal IR measurements to obtain sea surface temperature (SST). The resulting SST's were compared with the NOAA operational sea surface temperature measurements, and the two sets of measurements were found to be in reasonable agreement. The average residuals between the two sets of measurements was 0.15 K with the NOAA operational SST's being slightly greater.

  8. Surface intermediates on metal electrodes at high temperatures

    DEFF Research Database (Denmark)

    Zachau-Christiansen, Birgit; Jacobsen, Torben; Bay, Lasse;

    1998-01-01

    in contact with YSZ is covered with adsorbed oxygen which vanishes at high temperature (1000 degrees C). On Ni (YSZ) a specific layer of NiO is observed above the equilibrium potential while no surface species involving hydrogen can be identified at SOFC anode conditions. (C) 1998 Published by Elsevier......The mechanisms widely conceived for the O(2)-reduction or H(2)-oxidation reactions in SOFC's involve intermediate O/H species adsorbed on the electrode surface. The presence of these intermediates is investigated by linear sweep voltammetry. In air at moderate temperatures (500 degrees C) Pt...

  9. Surface air temperature variability in global climate models

    CERN Document Server

    Davy, Richard

    2012-01-01

    New results from the Coupled Model Inter-comparison Project phase 5 (CMIP5) and multiple global reanalysis datasets are used to investigate the relationship between the mean and standard deviation in the surface air temperature. A combination of a land-sea mask and orographic filter were used to investigate the geographic region with the strongest correlation and in all cases this was found to be for low-lying over-land locations. This result is consistent with the expectation that differences in the effective heat capacity of the atmosphere are an important factor in determining the surface air temperature response to forcing.

  10. The Global Structure of UTLS Ozone in GEOS-5: A Multi-Year Assimilation of EOS Aura Data

    Science.gov (United States)

    Wargan, Krzysztof; Pawson, Steven; Olsen, Mark A.; Witte, Jacquelyn C.; Douglass, Anne R.; Ziemke, Jerald R.; Strahan, Susan E.; Nielsen, J. Eric

    2015-01-01

    Eight years of ozone measurements retrieved from the Ozone Monitoring Instrument (OMI) and the Microwave Limb Sounder, both on the EOS Aura satellite, have been assimilated into the Goddard Earth Observing System version 5 (GEOS-5) data assimilation system. This study thoroughly evaluates this assimilated product, highlighting its potential for science. The impact of observations on the GEOS-5 system is explored by examining the spatial distribution of the observation-minus-forecast statistics. Independent data are used for product validation. The correlation coefficient of the lower-stratospheric ozone column with ozonesondes is 0.99 and the bias is 0.5%, indicating the success of the assimilation in reproducing the ozone variability in that layer. The upper-tropospheric assimilated ozone column is about 10% lower than the ozonesonde column but the correlation is still high (0.87). The assimilation is shown to realistically capture the sharp cross-tropopause gradient in ozone mixing ratio. Occurrence of transport-driven low ozone laminae in the assimilation system is similar to that obtained from the High Resolution Dynamics Limb Sounder (HIRDLS) above the 400 K potential temperature surface but the assimilation produces fewer laminae than seen by HIRDLS below that surface. Although the assimilation produces 5 - 8 fewer occurrences per day (up to approximately 20%) during the three years of HIRDLS data, the interannual variability is captured correctly. This data-driven assimilated product is complementary to ozone fields generated from chemistry and transport models. Applications include study of the radiative forcing by ozone and tracer transport near the tropopause.

  11. Observing the Agulhas Current with sea surface temperature and altimetry data: challenges and perspectives

    CSIR Research Space (South Africa)

    Krug, Marjolaine, J

    2014-06-01

    Full Text Available -Red Sea Surface Temperature datasets still suffer from inadequate cloud masking algorithms, particularly in regions of strong temperature gradient. Despite both Sea Surface Height and Sea Surface Temperature observations being severely compromised...

  12. The Land Surface Temperature Impact to Land Cover Types

    Science.gov (United States)

    Ibrahim, I.; Abu Samah, A.; Fauzi, R.; Noor, N. M.

    2016-06-01

    Land cover type is an important signature that is usually used to understand the interaction between the ground surfaces with the local temperature. Various land cover types such as high density built up areas, vegetation, bare land and water bodies are areas where heat signature are measured using remote sensing image. The aim of this study is to analyse the impact of land surface temperature on land cover types. The objectives are 1) to analyse the mean temperature for each land cover types and 2) to analyse the relationship of temperature variation within land cover types: built up area, green area, forest, water bodies and bare land. The method used in this research was supervised classification for land cover map and mono window algorithm for land surface temperature (LST) extraction. The statistical analysis of post hoc Tukey test was used on an image captured on five available images. A pixel-based change detection was applied to the temperature and land cover images. The result of post hoc Tukey test for the images showed that these land cover types: built up-green, built up-forest, built up-water bodies have caused significant difference in the temperature variation. However, built up-bare land did not show significant impact at p<0.05. These findings show that green areas appears to have a lower temperature difference, which is between 2° to 3° Celsius compared to urban areas. The findings also show that the average temperature and the built up percentage has a moderate correlation with R2 = 0.53. The environmental implications of these interactions can provide some insights for future land use planning in the region.

  13. Daytime sensible heat flux estimation over heterogeneous surfaces using multitemporal land-surface temperature observations

    Science.gov (United States)

    Castellví, F.; Cammalleri, C.; Ciraolo, G.; Maltese, A.; Rossi, F.

    2016-05-01

    Equations based on surface renewal (SR) analysis to estimate the sensible heat flux (H) require as input the mean ramp amplitude and period observed in the ramp-like pattern of the air temperature measured at high frequency. A SR-based method to estimate sensible heat flux (HSR-LST) requiring only low-frequency measurements of the air temperature, horizontal mean wind speed, and land-surface temperature as input was derived and tested under unstable conditions over a heterogeneous canopy (olive grove). HSR-LST assumes that the mean ramp amplitude can be inferred from the difference between land-surface temperature and mean air temperature through a linear relationship and that the ramp frequency is related to a wind shear scale characteristic of the canopy flow. The land-surface temperature was retrieved by integrating in situ sensing measures of thermal infrared energy emitted by the surface. The performance of HSR-LST was analyzed against flux tower measurements collected at two heights (close to and well above the canopy top). Crucial parameters involved in HSR-LST, which define the above mentioned linear relationship, were explained using the canopy height and the land surface temperature observed at sunrise and sunset. Although the olive grove can behave as either an isothermal or anisothermal surface, HSR-LST performed close to H measured using the eddy covariance and the Bowen ratio energy balance methods. Root mean square differences between HSR-LST and measured H were of about 55 W m-2. Thus, by using multitemporal thermal acquisitions, HSR-LST appears to bypass inconsistency between land surface temperature and the mean aerodynamic temperature. The one-source bulk transfer formulation for estimating H performed reliable after calibration against the eddy covariance method. After calibration, the latter performed similar to the proposed SR-LST method.

  14. New indexing and surface temperature analysis of exoplanets

    CERN Document Server

    Kashyap, J M; Safonova, M

    2016-01-01

    Study of exoplanets is the holy grail of present research in planetary sciences and astrobiology. Analysis of huge planetary data from space missions such as CoRoT and Kepler is directed ultimately at finding a planet similar to Earth\\-the Earth's twin, and answering the question of potential exo-habitability. The Earth Similarity Index (ESI) is a first step in this quest, ranging from 1 (Earth) to 0 (totally dissimilar to Earth). It was defined for the four physical parameters of a planet: radius, density, escape velocity and surface temperature. The ESI is further sub-divided into interior ESI (geometrical mean of radius and density) and surface ESI (geometrical mean of escape velocity and surface temperature). The challenge here is to determine which exoplanet parameter(s) is important in finding this similarity; how exactly the individual parameters entering the interior ESI and surface ESI are contributing to the global ESI. Since the surface temperature entering surface ESI is a non-observable quantity,...

  15. INVESTIGATION OF SURFACE TEMPERATURE IN HIGH-EFFICIENCY DEEP GRINDING

    Institute of Scientific and Technical Information of China (English)

    Zhao Henghua; Cai Guangqi; Jin Tan

    2005-01-01

    A new thermal model with triangular heat flux distribution is given in high-efficiency deep grinding. The mathematical expressions are driven to calculate the surface temperature. The transient behavior of the maximum temperature on contact area is investigated in different grinding conditions with a J-type thermocouple. The maximum contact temperatures measured in different conditions are found to be between 1 000 ℃ and 1 500 ℃ in burn-out conditions. The experiment results show good agreement with the new thermal model.

  16. The Remote Sensing of Surface Radiative Temperature over Barbados.

    Science.gov (United States)

    remote sensing of surface radiative temperature over Barbados was undertaken using a PRT-5 attached to a light aircraft. Traverses across the centre of the island, over the rugged east coast area, and the urban area of Bridgetown were undertaken at different times of day and night in the last week of June and the first week of December, 1969. These traverses show that surface variations in long-wave radiation emission lie within plus or minus 5% of the observations over grass at a representative site. The quick response of the surface to sunset and sunrise was

  17. Impact on the short-term forecast using radar data assimilation on the South and Southeast region of Brazil

    Science.gov (United States)

    Herdies, Dirceu; Viana, Liviany; Souza, Diego; Vendrasco, Eder

    2017-04-01

    The objective of this study was to analyze the behavior of the precipitation related to the numerical weather forecast employing the Atmospheric Weather Research and Forecasting model (WRF) and the Data assimilation Weather Research and Forecasting model Data Assimilation Three Dimensional-Variational (WRFDA / 3D-VAR) system for a Convective system occurred in the summer of 2015/2016 on the southern and southeastern regions of Brazil. The datasets used were radar data in the region of interest and observational data from the Global Telecommunications System (GTS). The data assimilated were radial velocity (directly) and reflectivity (indirectly) and variables of the state - air temperature, surface pressure, wind speed and direction, among others. Three experiments were performed to evaluate the weather forecast for the selected case: i) without any type of assimilation, (ii) assimilated GTS data, and (iii) assimilated data from available radars. The prediction until to 6 hours of convective system intensity was evaluated, which were validated with the combined precipitation data from satellites and surface. The results showed the positive impact of the short-term forecast using experiments with the radar and GTS data when compared to the experiment without using them. Thus, this study is expected to contribute to the development of modeling and the operation of the assimilation of radar data in the numerical weather prediction over the regions of study.

  18. A comparison of all-weather land surface temperature products

    Science.gov (United States)

    Martins, Joao; Trigo, Isabel F.; Ghilain, Nicolas; Goettche, Frank-M.; Ermida, Sofia; Olesen, Folke-S.; Gellens-Meulenberghs, Françoise; Arboleda, Alirio

    2017-04-01

    The Satellite Application Facility on Land Surface Analysis (LSA-SAF, http://landsaf.ipma.pt) has been providing land surface temperature (LST) estimates using SEVIRI/MSG on an operational basis since 2006. The LSA-SAF service has since been extended to provide a wide range of satellite-based quantities over land surfaces, such as emissivity, albedo, radiative fluxes, vegetation state, evapotranspiration, and fire-related variables. Being based on infra-red measurements, the SEVIRI/MSG LST product is limited to clear-sky pixels only. Several all-weather LST products have been proposed by the scientific community either based on microwave observations or using Soil-Vegetation-Atmosphere Transfer models to fill the gaps caused by clouds. The goal of this work is to provide a nearly gap-free operational all-weather LST product and compare these approaches. In order to estimate evapotranspiration and turbulent energy fluxes, the LSA-SAF solves the surface energy budget for each SEVIRI pixel, taking into account the physical and physiological processes occurring in vegetation canopies. This task is accomplished with an adapted SVAT model, which adopts some formulations and parameters of the Tiled ECMWF Scheme for Surface Exchanges over Land (TESSEL) model operated at the European Center for Medium-range Weather Forecasts (ECMWF), and using: 1) radiative inputs also derived by LSA-SAF, which includes surface albedo, down-welling fluxes and fire radiative power; 2) a land-surface characterization obtained by combining the ECOCLIMAP database with both LSA-SAF vegetation products and the H(ydrology)-SAF snow mask; 3) meteorological fields from ECMWF forecasts interpolated to SEVIRI pixels, and 4) soil moisture derived by the H-SAF and LST from LSA-SAF. A byproduct of the SVAT model is surface skin temperature, which is needed to close the surface energy balance. The model skin temperature corresponds to the radiative temperature of the interface between soil and atmosphere

  19. Assimilation of gridded GRACE terrestrial water storage estimates in the North American Land Data Assimilation System

    Science.gov (United States)

    The objective of the North American Land Data Assimilation System (NLDAS) is to provide best-available estimates of near surface meteorological conditions and soil hydrological status for the Continental United States. The first two phases of NLDAS, however, have not included the assimilation of rem...

  20. Enzyme surface rigidity tunes the temperature dependence of catalytic rates.

    Science.gov (United States)

    Isaksen, Geir Villy; Åqvist, Johan; Brandsdal, Bjørn Olav

    2016-07-12

    The structural origin of enzyme adaptation to low temperature, allowing efficient catalysis of chemical reactions even near the freezing point of water, remains a fundamental puzzle in biocatalysis. A remarkable universal fingerprint shared by all cold-active enzymes is a reduction of the activation enthalpy accompanied by a more negative entropy, which alleviates the exponential decrease in chemical reaction rates caused by lowering of the temperature. Herein, we explore the role of protein surface mobility in determining this enthalpy-entropy balance. The effects of modifying surface rigidity in cold- and warm-active trypsins are demonstrated here by calculation of high-precision Arrhenius plots and thermodynamic activation parameters for the peptide hydrolysis reaction, using extensive computer simulations. The protein surface flexibility is systematically varied by applying positional restraints, causing the remarkable effect of turning the cold-active trypsin into a variant with mesophilic characteristics without changing the amino acid sequence. Furthermore, we show that just restraining a key surface loop causes the same effect as a point mutation in that loop between the cold- and warm-active trypsin. Importantly, changes in the activation enthalpy-entropy balance of up to 10 kcal/mol are almost perfectly balanced at room temperature, whereas they yield significantly higher rates at low temperatures for the cold-adapted enzyme.

  1. Temperature limit values for touching cold surfaces with the fingertip

    NARCIS (Netherlands)

    Geng, Q.; Holme, I.; Hartog, E.A. den; Havenith, G.; Jay, O.; Malchaires, J.; Piette, A.; Rintama, H.; Rissanen, S.

    2006-01-01

    Objectives: At the request of the European Commission and in the framework of the European Machinery Directive, research was performed in five different laboratories to develop specifications for surface temperature limit values for the short-term accidental touching of the fingertip with cold

  2. Temperature limit values for touching cold surfaces with the fingertip

    NARCIS (Netherlands)

    Geng, Q.; Holme, I.; Hartog, E.A. den; Havenith, G.; Jay, O.; Malchaires, J.; Piette, A.; Rintama, H.; Rissanen, S.

    2006-01-01

    Objectives: At the request of the European Commission and in the framework of the European Machinery Directive, research was performed in five different laboratories to develop specifications for surface temperature limit values for the short-term accidental touching of the fingertip with cold surfa

  3. Climate Prediction Center (CPC) Global Land Surface Air Temperature Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A station observation-based global land monthly mean surface air temperature dataset at 0.5 x 0.5 latitude-longitude resolution for the period from 1948 to the...

  4. Quantifying and specifying the solar influence on terrestrial surface temperature

    NARCIS (Netherlands)

    de Jager, C.; Duhau, S.; van Geel, B.

    2010-01-01

    This investigation is a follow-up of a paper in which we showed that both major magnetic components of the solar dynamo, viz. the toroidal and the poloidal ones, are correlated with average terrestrial surface temperatures. Here, we quantify, improve and specify that result and search for their caus

  5. A physically based model of global freshwater surface temperature

    NARCIS (Netherlands)

    Beek, van L.P.H.; Eikelboom, T.; Vliet, van M.T.H.; Bierkens, M.F.P.

    2012-01-01

    Temperature determines a range of physical properties of water and exerts a strong control on surface water biogeochemistry. Thus, in freshwater ecosystems the thermal regime directly affects the geographical distribution of aquatic species through their growth and metabolism and indirectly through

  6. Climate Prediction Center (CPC) Global Land Surface Air Temperature Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A station observation-based global land monthly mean surface air temperature dataset at 0.5 0.5 latitude-longitude resolution for the period from 1948 to the present...

  7. Processes of India's offshore summer intraseasonal sea surface temperature variability

    Digital Repository Service at National Institute of Oceanography (India)

    Kurian, N.; Lengaigne, M.; Gopalakrishna, V.V.; Vialard, J.; Pous, S.; Peter, A-C.; Durand; Naik, Shweta

    ., vol.63; 2013; 329-346 Processes of India’s offshore summer intraseasonal sea surface temperature variability K. Nisha1, M. Lengaigne1,2, V.V. Gopalakrishna,1 J. Vialard2, S. Pous2, A.-C. Peter2, F. Durand3, S.Naik1 1. NIO, CSIR, Goa, India 2...

  8. A physically based model of global freshwater surface temperature

    NARCIS (Netherlands)

    Beek, van L.P.H.; Eikelboom, T.; Vliet, van M.T.H.; Bierkens, M.F.P.

    2012-01-01

    Temperature determines a range of physical properties of water and exerts a strong control on surface water biogeochemistry. Thus, in freshwater ecosystems the thermal regime directly affects the geographical distribution of aquatic species through their growth and metabolism and indirectly through

  9. Surface temperature maps for II Peg during 1999-2002

    CERN Document Server

    Lindborg, M; Tuominen, I; Hackman, T; Ilyin, I; Piskunov, N

    2009-01-01

    The active RS CVn star II Peg has been spectroscopically monitored for almost 18 years with the SOFIN spectrograph at NOT, La Palma, Spain. In this paper we present five new surface temperature maps of the object for the years 1999 (two maps), 2001 (one map) and 2002 (two maps).

  10. Satellite Data Assimilation within KIAPS-LETKF system

    Science.gov (United States)

    Jo, Y.; Lee, S., Sr.; Cho, K.

    2016-12-01

    Korea Institute of Atmospheric Prediction Systems (KIAPS) has been developing an ensemble data assimilation system using four-dimensional local ensemble transform kalman filter (LETKF; Hunt et al., 2007) within KIAPS Integrated Model (KIM), referred to as "KIAPS-LETKF". KIAPS-LETKF system was successfully evaluated with various Observing System Simulation Experiments (OSSEs) with NCAR Community Atmospheric Model - Spectral Element (Kang et al., 2013), which has fully unstructured quadrilateral meshes based on the cubed-sphere grid as the same grid system of KIM. Recently, assimilation of real observations has been conducted within the KIAPS-LETKF system with four-dimensional covariance functions over the 6-hr assimilation window. Then, conventional (e.g., sonde, aircraft, and surface) and satellite (e.g., AMSU-A, IASI, GPS-RO, and AMV) observations have been provided by the KIAPS Package for Observation Processing (KPOP). Wind speed prediction was found most beneficial due to ingestion of AMV and for the temperature prediction the improvement in assimilation is mostly due to ingestion of AMSU-A and IASI. However, some degradation in the simulation of the GPS-RO is presented in the upper stratosphere, even though GPS-RO leads positive impacts on the analysis and forecasts. We plan to test the bias correction method and several vertical localization strategies for radiance observations to improve analysis and forecast impacts.

  11. Assimilating host model information into a limited area model

    Directory of Open Access Journals (Sweden)

    Nils Gustafsson

    2012-01-01

    Full Text Available We propose to add an extra source of information to the data-assimilation of the regional HIgh Resolution Limited Area Model (HIRLAM model, constraining larger scales to the host model providing the lateral boundary conditions. An extra term, Jk, measuring the distance to the large-scale vorticity of the host model, is added to the cost-function of the variational data-assimilation. Vorticity is chosen because it is a good representative of the large-scale flow and because vorticity is a basic control variable of the HIRLAM variational data-assimilation. Furthermore, by choosing only vorticity, the remaining model variables, divergence, temperature, surface pressure and specific humidity will be allowed to adapt to the modified vorticity field in accordance with the internal balance constraints of the regional model. The error characteristics of the Jk term are described by the horizontal spectral densities and the vertical eigenmodes (eigenvectors and eigenvalues of the host model vorticity forecast error fields, expressed in the regional model geometry. The vorticity field, provided by the European Centre for Medium-range Weather Forecasts (ECMWF operational model, was assimilated into the HIRLAM model during an experiment period of 33 d in winter with positive impact on forecast verification statistics for upper air variables and mean sea level pressure.The review process was handled by Editor-in-Cheif Harald Lejenäs

  12. A Microring Temperature Sensor Based on the Surface Plasmon Wave

    Directory of Open Access Journals (Sweden)

    Wenchao Li

    2015-01-01

    Full Text Available A structure of microring sensor suitable for temperature measurement based on the surface plasmon wave is put forward in this paper. The sensor uses surface plasmon multilayer waveguiding structure in the vertical direction and U-shaped microring structure in the horizontal direction and utilizes SOI as the thermal material. The transfer function derivation of the structure of surface plasmon microring sensor is according to the transfer matrix method. While the change of refractive index of Si is caused by the change of ambient temperature, the effective refractive index of the multilayer waveguiding structure is changed, resulting in the drifting of the sensor output spectrum. This paper focuses on the transmission characteristics of multilayer waveguide structure and the impact on the output spectrum caused by refractive index changes in temperature parts. According to the calculation and simulation, the transmission performance of the structure is stable and the sensitivity is good. The resonance wavelength shift can reach 0.007 μm when the temperature is increased by 100 k and FSR can reach about 60 nm. This structure achieves a high sensitivity in the temperature sense taking into account a wide range of filter frequency selections, providing a theoretical basis for the preparation of microoptics.

  13. Modeling the surface temperature of Earth-like planets

    CERN Document Server

    Vladilo, G; Murante, G; Filippi, L; Provenzale, A

    2015-01-01

    We introduce a novel Earth-like planet surface temperature model (ESTM) for habitability studies based on the spatial-temporal distribution of planetary surface temperatures. The ESTM adopts a surface Energy Balance Model complemented by: radiative-convective atmospheric column calculations, a set of physically-based parameterizations of meridional transport, and descriptions of surface and cloud properties more refined than in standard EBMs. The parameterization is valid for rotating terrestrial planets with shallow atmospheres and moderate values of axis obliquity (epsilon >= 45^o). Comparison with a 3D model of atmospheric dynamics from the literature shows that the equator-to-pole temperature differences predicted by the two models agree within ~5K when the rotation rate, insolation, surface pressure and planet radius are varied in the intervals 0.5 <= Omega/Omega_o <= 2, 0.75 <= S/S_o <= 1.25, 0.3 <= p/(1 bar) <= 10, and 0.5 <= R/R_o <= 2, respectively. The ESTM has an extremely l...

  14. Modeling Apple Surface Temperature Dynamics Based on Weather Data

    Directory of Open Access Journals (Sweden)

    Lei Li

    2014-10-01

    Full Text Available The exposure of fruit surfaces to direct sunlight during the summer months can result in sunburn damage. Losses due to sunburn damage are a major economic problem when marketing fresh apples. The objective of this study was to develop and validate a model for simulating fruit surface temperature (FST dynamics based on energy balance and measured weather data. A series of weather data (air temperature, humidity, solar radiation, and wind speed was recorded for seven hours between 11:00–18:00 for two months at fifteen minute intervals. To validate the model, the FSTs of “Fuji” apples were monitored using an infrared camera in a natural orchard environment. The FST dynamics were measured using a series of thermal images. For the apples that were completely exposed to the sun, the RMSE of the model for estimating FST was less than 2.0 °C. A sensitivity analysis of the emissivity of the apple surface and the conductance of the fruit surface to water vapour showed that accurate estimations of the apple surface emissivity were important for the model. The validation results showed that the model was capable of accurately describing the thermal performances of apples under different solar radiation intensities. Thus, this model could be used to more accurately estimate the FST relative to estimates that only consider the air temperature. In addition, this model provides useful information for sunburn protection management.

  15. A model of the tropical Pacific sea surface temperature climatology

    Science.gov (United States)

    Seager, Richard; Zebiak, Stephen E.; Cane, Mark A.

    1988-01-01

    A model for the climatological mean sea surface temperature (SST) of the tropical Pacific Ocean is developed. The upper ocean response is computed using a time dependent, linear, reduced gravity model, with the addition of a constant depth frictional surface layer. The full three-dimensional temperature equation and a surface heat flux parameterization that requires specification of only wind speed and total cloud cover are used to evaluate the SST. Specification of atmospheric parameters, such as air temperature and humidity, over which the ocean has direct influence, is avoided. The model simulates the major features of the observed tropical Pacific SST. The seasonal evolution of these features is generally captured by the model. Analysis of the results demonstrates the control the ocean has over the surface heat flux from ocean to atmosphere and the crucial role that dynamics play in determining the mean SST in the equatorial Pacific. The sensitivity of the model to perturbations in the surface heat flux, cloud cover specification, diffusivity, and mixed layer depth is discussed.

  16. Temperature maps measurements on 3D surfaces with infrared thermography

    Energy Technology Data Exchange (ETDEWEB)

    Cardone, Gennaro; Ianiro, Andrea [University of Naples Federico II, Department of Aerospace Engineering (DIAS), Naples (Italy); Ioio, Gennaro dello [University of Cambridge, BP Institute for Multiphase Flow, Cambridge, England (United Kingdom); Passaro, Andrea [Alta SpA, Ospedaletto, PI (Italy)

    2012-02-15

    The use of the infrared camera as a temperature transducer in wind tunnel applications is convenient and widespread. Nevertheless, the infrared data are available in the form of 2D images while the observed surfaces are often not planar and the reconstruction of temperature maps over them is a critical task. In this work, after recalling the principles of IR thermography, a methodology to rebuild temperature maps on the surfaces of 3D object is proposed. In particular, an optical calibration is applied to the IR camera by means of a novel target plate with control points. The proposed procedure takes also into account the directional emissivity by estimating the viewing angle. All the needed steps are described and analyzed. The advantages given by the proposed method are shown with an experiment in a hypersonic wind tunnel. (orig.)

  17. Development of KIAPS Observation Processing Package for Data Assimilation System

    Science.gov (United States)

    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.

  18. A Surface Temperature Initiated Closure (STIC) for surface energy balance fluxes

    DEFF Research Database (Denmark)

    Mallick, Kaniska; Jarvis, Andrew J.; Boegh, Eva;

    2014-01-01

    of four state equations. Taking advantage of the psychrometric relationship between temperature and vapor pressure, the present method also estimates the near surface moisture availability (M) from TS, air temperature (TA) and relative humidity (RH), thereby being capable of decomposing λ...

  19. A generalized Gaussian distribution based uncertainty sampling approach and its application in actual evapotranspiration assimilation

    Science.gov (United States)

    Chen, Shaohui

    2017-09-01

    It is extremely important for ensemble based actual evapotranspiration assimilation (AETA) to accurately sample the uncertainties. Traditionally, the perturbing ensemble is sampled from one prescribed multivariate normal distribution (MND). However, MND is under-represented in capturing the non-MND uncertainties caused by the nonlinear integration of land surface models while these hypernormal uncertainties can be better characterized by generalized Gaussian distribution (GGD) which takes MND as the special case. In this paper, one novel GGD based uncertainty sampling approach is outlined to create one hypernormal ensemble for the purpose of better improving land surface models with observation. With this sampling method, various assimilation methods can be tested in a common equation form. Experimental results on Noah LSM show that the outlined method is more powerful than MND in reducing the misfit between model forecasts and observations in terms of actual evapotranspiration, skin temperature, and soil moisture/ temperature in the 1st layer, and also indicate that the energy and water balances constrain ensemble based assimilation to simultaneously optimize all state and diagnostic variables. Overall evaluation expounds that the outlined approach is a better alternative than the traditional MND method for seizing assimilation uncertainties, and it can serve as a useful tool for optimizing hydrological models with data assimilation.

  20. Designing high-temperature steels via surface science and thermodynamics

    Science.gov (United States)

    Gross, Cameron T.; Jiang, Zilin; Mathai, Allan; Chung, Yip-Wah

    2016-06-01

    Electricity in many countries such as the US and China is produced by burning fossil fuels in steam-turbine-driven power plants. The efficiency of these power plants can be improved by increasing the operating temperature of the steam generator. In this work, we adopted a combined surface science and computational thermodynamics approach to the design of high-temperature, corrosion-resistant steels for this application. The result is a low-carbon ferritic steel with nanosized transition metal monocarbide precipitates that are thermally stable, as verified by atom probe tomography. High-temperature Vickers hardness measurements demonstrated that these steels maintain their strength for extended periods at 700 °C. We hypothesize that the improved strength of these steels is derived from the semi-coherent interfaces of these thermally stable, nanosized precipitates exerting drag forces on impinging dislocations, thus maintaining strength at elevated temperatures.

  1. Surface layer temperature inversion in the Bay of Bengal

    Science.gov (United States)

    Thadathil, Pankajakshan; Gopalakrishna, V. V.; Muraleedharan, P. M.; Reddy, G. V.; Araligidad, Nilesh; Shenoy, Shrikant

    2002-10-01

    Surface layer temperature inversion occurring in the Bay of Bengal has been addressed. Hydrographic data archived in the Indian Oceanographic Data Center are used to understand various aspects of the temperature inversion of surface layer in the Bay of Bengal, such as occurrence time, characteristics, stability, inter-annual variability and generating mechanisms. Spatially organized temperature inversion occurs in the coastal waters of the western and northeastern Bay during winter (November-February). Although the inversion in the northeastern Bay is sustained until February (with remnants seen even in March), in the western Bay it becomes less organized in January and almost disappears by February. Inversion is confined to the fresh water induced seasonal halocline of the surface layer. Inversions of large temperature difference (of the order of 1.6-2.4°C) and thin layer thickness (10-20 m) are located adjacent to major fresh water inputs from the Ganges, Brahmaputra, Irrawaddy, Krishna and Godavari rivers. The inversion is stable with a mean stability of 3600×10 -8 m -1. Inter-annual variability of the inversion is significantly high and it is caused by the inter-annual variability of fresh water flux and surface cooling in the northern Bay. Fresh water flux leads the occurrence process in association with surface heat flux and advection. The leading role of fresh water flux is understood from the observation that the two occurrence regions of inversion (the western and northeastern Bay) have proximity to the two low salinity (with values about 28-29‰) zones. In the western Bay, the East India Coastal Current brings less saline and cold water from the head of the Bay to the south-west Bay, where it advects over warm, saline water, promoting temperature inversion in this region in association with the surface heat loss. For inversion occurring in the northeastern Bay (where the surface water gains heat from atmosphere), surface advection of the less saline

  2. New Measurements from Old Boreholes: A Look at Interaction Between Surface Air Temperature and Ground Surface Temperature

    Science.gov (United States)

    Heinle, S. M.; Gosnold, W. D.

    2007-12-01

    We recently logged new field measurements of several boreholes throughout the Midwest, including North Dakota, South Dakota, and Nebraska. We then compared these new measurements against measurements previously obtained. Our comparisons included inverse modeling of past and recent measurements as well as climate modeling based on past surface air temperatures obtained from the weather stations. The data show a good correlation between climate warming in the last century and ground surface warming. Of particular importance is that cooling of air temperatures beginning in the mid 1990s reflects in the ground surface temperatures. The boreholes included in the study consist of three boreholes located in north central North Dakota, including two deeper than 200 meters. Two boreholes in the southwestern part of South Dakota, and two from southeastern South Dakota, all approximately 180 meters deep. Also included, were two boreholes (135 meters and over 200 meters deep) located in southwestern Nebraska, and two boreholes in the panhandle of Nebraska, each over 100 meters deep. We obtained historical surface air temperature from climate stations located near the boreholes, both from the United States Historical Climatology Network and from the Western Regional Climate Center.

  3. Assimilation of Mode-S EHS aircraft observations with a local EnKF

    Science.gov (United States)

    Lange, Heiner; Janjic, Tijana

    2016-04-01

    Aircraft observations of wind and temperature collected by airport surveillance radars (Mode-S EHS) were assimilated in COSMO-KENDA (Kilometre-scale ENsemble Data Assimilation) which couples an Ensemble Kalman Filter to a 40 member ensemble of the convection permitting COSMO-DE (Consortium for Small-Scale Modelling) model. The number of observing aircrafts in Mode-S EHS was about 15 times larger than in the AMDAR system. Between both aircraft observation systems, comparable observation error standard deviations in wind and a larger error in temperature were diagnosed a posteriori using analysis/forecast residuals in observation space (Desrozier's method). With the high density of Mode-S EHS observations, a reduction of temperature and wind error in forecasts of one and three hours was found mainly in the flight level and less near the surface. The amount of Mode-S EHS data was reduced by random thinning to test the effect of a varying observation density. With the current data assimilation setup, a saturation of the forecast error reduction was apparent when more than 50 percent of the Mode-S EHS data were assimilated. Forecast kinetic energy spectra indicated that the reduction in error is related to analysis updates on all scales resolved by COSMO-DE. Evolution (every 15 minutes) of forecast kinetic energy spectra compared to the control experiment showed different behavior of COSMO-DE model depending on amount of data assimilated.

  4. Surface emissivity and temperature retrieval for a hyperspectral sensor

    Energy Technology Data Exchange (ETDEWEB)

    Borel, C.C.

    1998-12-01

    With the growing use of hyper-spectral imagers, e.g., AVIRIS in the visible and short-wave infrared there is hope of using such instruments in the mid-wave and thermal IR (TIR) some day. The author believes that this will enable him to get around using the present temperature-emissivity separation algorithms using methods which take advantage of the many channels available in hyper-spectral imagers. A simple fact used in coming up with a novel algorithm is that a typical surface emissivity spectrum are rather smooth compared to spectral features introduced by the atmosphere. Thus, a iterative solution technique can be devised which retrieves emissivity spectra based on spectral smoothness. To make the emissivities realistic, atmospheric parameters are varied using approximations, look-up tables derived from a radiative transfer code and spectral libraries. One such iterative algorithm solves the radiative transfer equation for the radiance at the sensor for the unknown emissivity and uses the blackbody temperature computed in an atmospheric window to get a guess for the unknown surface temperature. By varying the surface temperature over a small range a series of emissivity spectra are calculated. The one with the smoothest characteristic is chosen. The algorithm was tested on synthetic data using MODTRAN and the Salisbury emissivity database.

  5. Sea-surface temperature and salinity mapping from remote microwave radiometric measurements of brightness temperature

    Science.gov (United States)

    Hans-Juergen, C. B.; Kendall, B. M.; Fedors, J. C.

    1977-01-01

    A technique to measure remotely sea surface temperature and salinity was demonstrated with a dual frequency microwave radiometer system. Accuracies in temperature of 1 C and in salinity of part thousand for salinity greater than 5 parts per thousand were attained after correcting for the influence of extraterrestrial background radiation, atmospheric radiation and attenuation, sea-surface roughness, and antenna beamwidth. The radiometers, operating at 1.43 and 2.65 GHz, comprise a third-generation system using null balancing and feedback noise injection. Flight measurements from an aircraft at an altitude of 1.4 km over the lower Chesapeake Bay and coastal areas of the Atlantic Ocean resulted in contour maps of sea-surface temperature and salinity with a spatial resolution of 0.5 km.

  6. A 4D-variational ocean data assimilation application for Santos Basin, Brazil

    Science.gov (United States)

    da Rocha Fragoso, Mauricio; de Carvalho, Gabriel Vieira; Soares, Felipe Lobo Mendes; Faller, Daiane Gracieli; de Freitas Assad, Luiz Paulo; Toste, Raquel; Sancho, Lívia Maria Barbosa; Passos, Elisa Nóbrega; Böck, Carina Stefoni; Reis, Bruna; Landau, Luiz; Arango, Hernan G.; Moore, Andrew M.

    2016-03-01

    Aiming to achieve systematic ocean forecasting for the southeastern Brazilian coast, an incremental 4D-Var data assimilation system is applied to a regional ocean model focused mainly in the Santos Basin region. This implementation is performed within the scope of The Santos Basin Ocean Observing System (or Project Azul), a pilot project designed to collect oceanographic data with enough frequency and spatial coverage so to improve regional forecasts through data assimilation. The ocean modeling and data assimilation system of Project Azul is performed with the Regional Ocean Modeling System (ROMS). The observations used in the assimilation cycles include the following: 1-day gridded, 0.1° resolution SST from POES AVHRR; 1-day gridded, 0.3° composite of the MDT SSH from AVISO; and surface and subsurface hydrographic measurements of temperature and salinity collected with gliders and ARGO floats from Project Azul and from UK Met-Office EN3 project dataset. The assimilative model results are compared to forward model results and independent observations, both from remote sensing and in situ sources. The results clearly show that 4D-Var data assimilation leads to an improvement in the skill of ocean hindcast in the studied region.

  7. Ensemble Kalman Filter data assimilation and storm surge experiments of tropical cyclone Nargis

    Directory of Open Access Journals (Sweden)

    Le Duc

    2015-07-01

    Full Text Available Data assimilation experiments on Myanmar tropical cyclone (TC, Nargis, using the Local Ensemble Transform Kalman Filter (LETKF method and the Japan Meteorological Agency (JMA non-hydrostatic model (NHM were performed to examine the impact of LETKF on analysis performance in real cases. Although the LETKF control experiment using NHM as its driving model (NHM–LETKF produced a weak vortex, the subsequent 3-day forecast predicted Nargis’ track and intensity better than downscaling from JMA's global analysis. Some strategies to further improve the final analysis were considered. They were sea surface temperature (SST perturbations and assimilation of TC advisories. To address SST uncertainty, SST analyses issued by operational forecast centres were used in the assimilation window. The use of a fixed source of SST analysis for each ensemble member was more effective in practice. SST perturbations were found to have slightly positive impact on the track forecasts. Assimilation of TC advisories could have a positive impact with a reasonable choice of its free parameters. However, the TC track forecasts exhibited northward displacements, when the observation error of intensities was underestimated in assimilation of TC advisories. The use of assimilation of TC advisories was considered in the final NHM–LETKF by choosing an appropriate set of free parameters. The extended forecast based on the final analysis provided meteorological forcings for a storm surge simulation using the Princeton Ocean Model. Probabilistic forecasts of the water levels at Irrawaddy and Yangon significantly improved the results in the previous studies.

  8. Ultraviolet surface plasmon-mediated low temperature hydrazine decomposition

    Energy Technology Data Exchange (ETDEWEB)

    Peng, Siying; Sheldon, Matthew T.; Atwater, Harry A. [Thomas J. Watson Laboratories of Applied Physics, California Institute of Technology, Pasadena, California 91125 (United States); Liu, Wei-Guang; Jaramillo-Botero, Andres; Goddard, William Andrew [Materials and Process Simulation Center, California Institute of Technology, Pasadena, California 91125 (United States)

    2015-01-12

    Conventional methods require elevated temperatures in order to dissociate high-energy nitrogen bonds in precursor molecules such as ammonia or hydrazine used for nitride film growth. We report enhanced photodissociation of surface-absorbed hydrazine (N{sub 2}H{sub 4}) molecules at low temperature by using ultraviolet surface plasmons to concentrate the exciting radiation. Plasmonic nanostructured aluminum substrates were designed to provide resonant near field concentration at λ = 248 nm (5 eV), corresponding to the maximum optical cross section for hydrogen abstraction from N{sub 2}H{sub 4}. We employed nanoimprint lithography to fabricate 1 mm × 1 mm arrays of the resonant plasmonic structures, and ultraviolet reflectance spectroscopy confirmed resonant extinction at 248 nm. Hydrazine was cryogenically adsorbed to the plasmonic substrate in a low-pressure ambient, and 5 eV surface plasmons were resonantly excited using a pulsed KrF laser. Mass spectrometry was used to characterize the photodissociation products and indicated a 6.2× overall enhancement in photodissociation yield for hydrazine adsorbed on plasmonic substrates compared with control substrates. The ultraviolet surface plasmon enhanced photodissociation demonstrated here may provide a valuable method to generate reactive precursors for deposition of nitride thin film materials at low temperatures.

  9. The dependence of surface temperature on IGBTs load and ambient temperature

    Science.gov (United States)

    Alexander, Čaja; Marek, Patsch

    2015-05-01

    Currently, older power electronics and electrotechnics are improvement and at the same time developing new and more efficient devices. These devices produce in their activities a significant part of the heat which, if not effectively drained, causing damage to these elements. In this case, it is important to develop new and more efficient cooling system. The most widespread of modern methods of cooling is the cooling by heat pipe. This contribution is aimed at cooling the insulated-gate bipolar transistor (IGBT) elements by loop heat pipe (LHP). IGBTs are very prone to damage due to high temperatures, and therefore is the important that the surface temperature was below 100°C. It was therefore created a model that examined what impact of surface temperature on the IGBT element and heat removal at different load and constant ambient temperature.

  10. The dependence of surface temperature on IGBTs load and ambient temperature

    Directory of Open Access Journals (Sweden)

    Alexander Čaja

    2015-01-01

    Full Text Available Currently, older power electronics and electrotechnics are improvement and at the same time developing new and more efficient devices. These devices produce in their activities a significant part of the heat which, if not effectively drained, causing damage to these elements. In this case, it is important to develop new and more efficient cooling system. The most widespread of modern methods of cooling is the cooling by heat pipe. This contribution is aimed at cooling the insulated-gate bipolar transistor (IGBT elements by loop heat pipe (LHP. IGBTs are very prone to damage due to high temperatures, and therefore is the important that the surface temperature was below 100°C. It was therefore created a model that examined what impact of surface temperature on the IGBT element and heat removal at different load and constant ambient temperature.

  11. Reconstruction of MODIS daily land surface temperature under clouds

    Science.gov (United States)

    Sun, L.; Gao, F.; Chen, Z.; Song, L.; Xie, D.

    2015-12-01

    Land surface temperature (LST), generally defined as the skin temperature of the Earth's surface, controls the process of evapotranspiration, surface energy balance, soil moisture change and climate change. Moderate Resolution Imaging Spectrometer (MODIS) is equipped with 1km resolution thermal sensor andcapable of observing the earth surface at least once per day.Thermal infrared bands cannot penetrate cloud, which means we cannot get consistency drought monitoring condition at one area. However, the cloudy-sky conditions represent more than half of the actual day-to-day weather around the global. In this study, we developed an LST filled model based on the assumption that under good weather condition, LST difference between two nearby pixels are similar among the closest 8 days. We used all the valid pixels covered by a 9*9 window to reconstruct the gap LST. Each valid pixel is assigned a weight which is determined by the spatial distance and the spectral similarity. This model is applied in the Middle-East of China including Gansu, Ningxia, Shaanxi province. The terrain is complicated in this area including plain and hill. The MODIS daily LST product (MOD11A3) from 2000 to 2004 is tested. Almost all the gap pixels are filled, and the terrain information is reconstructed well and smoothly. We masked two areas in order to validate the model, one located in the plain, another located in the hill. The correlation coefficient is greater than 0.8, even up to 0.92 in a few days. We also used ground measured day maximum and mean surface temperature to valid our model. Although both the temporal and spatial scale are different between ground measured temperature and MODIS LST, they agreed well in all the stations. This LST filled model is operational because it only needs LST and reflectance, and does not need other auxiliary information such as climate factors. We will apply this model to more regions in the future.

  12. Piglets’ Surface Temperature Change at Different Weights at Birth

    Science.gov (United States)

    Caldara, Fabiana Ribeiro; dos Santos, Luan Sousa; Machado, Sivanilza Teixeira; Moi, Marta; de Alencar Nääs, Irenilza; Foppa, Luciana; Garcia, Rodrigo Garófallo; de Kássia Silva dos Santos, Rita

    2014-01-01

    The study was carried out in order to verify the effects of piglets’ weight at birth on their surface temperature change (ST) after birth, and its relationship with ingestion time of colostrum. Piglets from four different sows were weighed at birth and divided into a totally randomized design with three treatments according to birth weight (PBW): T1 - less than 1.00 kg, T2 - 1.00 to 1.39 kg, and T3 - higher than or equal to 1.40 kg. The time spent for the first colostrum ingestion was recorded (TFS). Images of piglets’ surface by thermal imaging camera were recorded at birth (STB) and 15, 30, 45, 60, and 120 min after birth. The air temperature and relative humidity were recorded every 30 min and the indexes of temperature and humidity (THI) were calculated. A ST drop after 15 min from birth was observed, increasing again after sixty minutes. Positive correlations were found between the PBW and the ST at 30 and 45 min after birth. The PBW was negatively correlated with the TFS. The THI showed high negative correlations (−0.824 and −0.815) with STB and after 15 min from birth. The piglet’s surface temperature at birth was positively correlated with temperature thereof to 15 min, influencing therefore the temperatures in the interval of 45 to 120 min. The birth weight contributes significantly to postnatal hypothermia and consequently to the time it takes for piglets ingest colostrum, requiring special attention to those of low birth weight. PMID:25049971

  13. Piglets' surface temperature change at different weights at birth.

    Science.gov (United States)

    Caldara, Fabiana Ribeiro; Dos Santos, Luan Sousa; Machado, Sivanilza Teixeira; Moi, Marta; de Alencar Nääs, Irenilza; Foppa, Luciana; Garcia, Rodrigo Garófallo; de Kássia Silva Dos Santos, Rita

    2014-03-01

    The study was carried out in order to verify the effects of piglets' weight at birth on their surface temperature change (ST) after birth, and its relationship with ingestion time of colostrum. Piglets from four different sows were weighed at birth and divided into a totally randomized design with three treatments according to birth weight (PBW): T1 - less than 1.00 kg, T2 - 1.00 to 1.39 kg, and T3 - higher than or equal to 1.40 kg. The time spent for the first colostrum ingestion was recorded (TFS). Images of piglets' surface by thermal imaging camera were recorded at birth (STB) and 15, 30, 45, 60, and 120 min after birth. The air temperature and relative humidity were recorded every 30 min and the indexes of temperature and humidity (THI) were calculated. A ST drop after 15 min from birth was observed, increasing again after sixty minutes. Positive correlations were found between the PBW and the ST at 30 and 45 min after birth. The PBW was negatively correlated with the TFS. The THI showed high negative correlations (-0.824 and -0.815) with STB and after 15 min from birth. The piglet's surface temperature at birth was positively correlated with temperature thereof to 15 min, influencing therefore the temperatures in the interval of 45 to 120 min. The birth weight contributes significantly to postnatal hypothermia and consequently to the time it takes for piglets ingest colostrum, requiring special attention to those of low birth weight.

  14. Piglets’ Surface Temperature Change at Different Weights at Birth

    Directory of Open Access Journals (Sweden)

    Fabiana Ribeiro Caldara

    2014-03-01

    Full Text Available The study was carried out in order to verify the effects of piglets’ weight at birth on their surface temperature change (ST after birth, and its relationship with ingestion time of colostrum. Piglets from four different sows were weighed at birth and divided into a totally randomized design with three treatments according to birth weight (PBW: T1 - less than 1.00 kg, T2 - 1.00 to 1.39 kg, and T3 - higher than or equal to 1.40 kg. The time spent for the first colostrum ingestion was recorded (TFS. Images of piglets’ surface by thermal imaging camera were recorded at birth (STB and 15, 30, 45, 60, and 120 min after birth. The air temperature and relative humidity were recorded every 30 min and the indexes of temperature and humidity (THI were calculated. A ST drop after 15 min from birth was observed, increasing again after sixty minutes. Positive correlations were found between the PBW and the ST at 30 and 45 min after birth. The PBW was negatively correlated with the TFS. The THI showed high negative correlations (−0.824 and −0.815 with STB and after 15 min from birth. The piglet’s surface temperature at birth was positively correlated with temperature thereof to 15 min, influencing therefore the temperatures in the interval of 45 to 120 min. The birth weight contributes significantly to postnatal hypothermia and consequently to the time it takes for piglets ingest colostrum, requiring special attention to those of low birth weight.

  15. Lessons Learned from Assimilating Altimeter Data into a Coupled General Circulation Model with the GMAO Augmented Ensemble Kalman Filter

    Science.gov (United States)

    Keppenne, Christian; Vernieres, Guillaume; Rienecker, Michele; Jacob, Jossy; Kovach, Robin

    2011-01-01

    Satellite altimetry measurements have provided global, evenly distributed observations of the ocean surface since 1993. However, the difficulties introduced by the presence of model biases and the requirement that data assimilation systems extrapolate the sea surface height (SSH) information to the subsurface in order to estimate the temperature, salinity and currents make it difficult to optimally exploit these measurements. This talk investigates the potential of the altimetry data assimilation once the biases are accounted for with an ad hoc bias estimation scheme. Either steady-state or state-dependent multivariate background-error covariances from an ensemble of model integrations are used to address the problem of extrapolating the information to the sub-surface. The GMAO ocean data assimilation system applied to an ensemble of coupled model instances using the GEOS-5 AGCM coupled to MOM4 is used in the investigation. To model the background error covariances, the system relies on a hybrid ensemble approach in which a small number of dynamically evolved model trajectories is augmented on the one hand with past instances of the state vector along each trajectory and, on the other, with a steady state ensemble of error estimates from a time series of short-term model forecasts. A state-dependent adaptive error-covariance localization and inflation algorithm controls how the SSH information is extrapolated to the sub-surface. A two-step predictor corrector approach is used to assimilate future information. Independent (not-assimilated) temperature and salinity observations from Argo floats are used to validate the assimilation. A two-step projection method in which the system first calculates a SSH increment and then projects this increment vertically onto the temperature, salt and current fields is found to be most effective in reconstructing the sub-surface information. The performance of the system in reconstructing the sub-surface fields is particularly

  16. Assimilating atmosphere reanalysis in coupled data assimilation

    Science.gov (United States)

    Liu, Huaran; Lu, Feiyu; Liu, Zhengyu; Liu, Yun; Zhang, Shaoqing

    2016-06-01

    This paper tests the idea of substituting the atmospheric observations with atmospheric reanalysis when setting up a coupled data assimilation system. The paper focuses on the quantification of the effects on the oceanic analysis resulted from this substitution and designs four different assimilation schemes for such a substitution. A coupled Lorenz96 system is constructed and an ensemble Kalman filter is adopted. The atmospheric reanalysis and oceanic observations are assimilated into the system and the analysis quality is compared to a benchmark experiment where both atmospheric and oceanic observations are assimilated. Four schemes are designed for assimilating the reanalysis and they differ in the generation of the perturbed observation ensemble and the representation of the error covariance matrix. The results show that when the reanalysis is assimilated directly as independent observations, the root-mean-square error increase of oceanic analysis relative to the benchmark is less than 16% in the perfect model framework; in the biased model case, the increase is less than 22%. This result is robust with sufficient ensemble size and reasonable atmospheric observation quality (e.g., frequency, noisiness, and density). If the observation is overly noisy, infrequent, sparse, or the ensemble size is insufficiently small, the analysis deterioration caused by the substitution is less severe since the analysis quality of the benchmark also deteriorates significantly due to worse observations and undersampling. The results from different assimilation schemes highlight the importance of two factors: accurate representation of the error covariance of the reanalysis and the temporal coherence along each ensemble member, which are crucial for the analysis quality of the substitution experiment.

  17. Data assimilation experiments with MPIESM climate model

    Directory of Open Access Journals (Sweden)

    Belyaev Konstantin

    2016-01-01

    Full Text Available Further development of data assimilation technique and its application in numerical experiments with state-of-the art Max Plank Institute Earth System model have been carried out. In particularly, the stability problem of assimilation is posed and discussed In the experiments the sea surface height data from archive Archiving, Validating and Interpolating Satellite Ocean have been used. All computations have been realized on cluster system of German Climate Computing Center. The results of numerical experiments with and without assimilation were recorded and analyzed. A special attention has been focused on the Arctic zone. It is shown that there is a good coincidence of model tendencies and independent data.

  18. Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

    Directory of Open Access Journals (Sweden)

    C. L. Pérez Díaz

    2015-08-01

    Full Text Available Land Surface Temperature (LST is a key variable (commonly studied to understand the hydrological cycle that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air and snow skin temperature (T-skin helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

  19. Near-surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

    Science.gov (United States)

    Pérez Díaz, C. L.; Lakhankar, T.; Romanov, P.; Muñoz, J.; Khanbilvardi, R.; Yu, Y.

    2015-08-01

    Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

  20. Thermospheric Data Assimilation

    Science.gov (United States)

    2016-05-05

    Thermospheric Data Assimilation 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-13-1-0058 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Dr. Tomoko...unlimited 13. SUPPLEMENTARY NOTES Program Manager: Dr. Julie J Moses, AFOSR, 703-696-9586, Julie.moses@us.af.mil 14. ABSTRACT This project...thermosphere-ionosphere first- principles model. An ensemble data assimilation procedure, constructed with the NCAR Data Assimilation Research Testbed

  1. Multiscale Data Assimilation

    Science.gov (United States)

    2014-09-30

    1 Multiscale Data Assimilation Dr. Pierre F.J. Lermusiaux Department of Mechanical Engineering, Center for Ocean Science and Engineering...concerned with next-generation multiscale data assimilation , with a focus on shelfbreak regions, including non-hydrostatic effects. Our long-term...goals are to: - Develop and utilize GMM-DO data assimilation schemes for rigorous multiscale inferences, where observations provide information on

  2. Temperature-dependent photoluminescence of surface-engineered silicon nanocrystals

    Science.gov (United States)

    Mitra, Somak; Švrček, Vladimir; Macias-Montero, Manual; Velusamy, Tamilselvan; Mariotti, Davide

    2016-01-01

    In this work we report on temperature-dependent photoluminescence measurements (15–300 K), which have allowed probing radiative transitions and understanding of the appearance of various transitions. We further demonstrate that transitions associated with oxide in SiNCs show characteristic vibronic peaks that vary with surface characteristics. In particular we study differences and similarities between silicon nanocrystals (SiNCs) derived from porous silicon and SiNCs that were surface-treated using a radio-frequency (RF) microplasma system. PMID:27296771

  3. Biological control of surface temperature in the Arabian Sea

    Science.gov (United States)

    Sathyendranath, Shubha; Gouveia, Albert D.; Shetye, Satish R.; Ravindran, P.; Platt, Trevor

    1991-01-01

    In the Arabian Sea, the southwest monsoon promotes seasonal upwelling of deep water, which supplies nutrients to the surface layer and leads to a marked increase in phytoplankton growth. Remotely sensed data on ocean color are used here to show that the resulting distribution of phytoplankton exerts a controlling influence on the seasonal evolution of sea surface temperature. This results in a corresponding modification of ocean-atmosphere heat exchange on regional and seasonal scales. It is shown that this biological mechanism may provide an important regulating influence on ocean-atmosphere interactions.

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  6. Estimating Temperature Fields from MODIS Land Surface Temperature and Air Temperature Observations in a Sub-Arctic Alpine Environment

    Directory of Open Access Journals (Sweden)

    Scott N. Williamson

    2014-01-01

    Full Text Available Spatially continuous satellite infrared temperature measurements are essential for understanding the consequences and drivers of change, at local and regional scales, especially in northern and alpine environments dominated by a complex cryosphere where in situ observations are scarce. We describe two methods for producing daily temperature fields using MODIS “clear-sky” day-time Land Surface Temperatures (LST. The Interpolated Curve Mean Daily Surface Temperature (ICM method, interpolates single daytime Terra LST values to daily means using the coincident diurnal air temperature curves. The second method calculates daily mean LST from daily maximum and minimum LST (MMM values from MODIS Aqua and Terra. These ICM and MMM models were compared to daily mean air temperatures recorded between April and October at seven locations in southwest Yukon, Canada, covering characteristic alpine land cover types (tundra, barren, glacier at elevations between 1,408 m and 2,319 m. Both methods for producing mean daily surface temperatures have advantages and disadvantages. ICM signals are strongly correlated with air temperature (R2 = 0.72 to 0.86, but have relatively large variability (RMSE = 4.09 to 4.90 K, while MMM values had a stronger correlation to air temperature (R2 = 0.90 and smaller variability (RMSE = 2.67 K. Finally, when comparing 8-day LST averages, aggregated from the MMM method, to air temperature, we found a high correlation (R2 = 0.84 with less variability (RMSE = 1.54 K. Where the trend was less steep and the y-intercept increased by 1.6 °C compared to the daily correlations. This effect is likely a consequence of LST temperature averages being differentially affected by cloud cover over warm and cold surfaces. We conclude that satellite infrared skin temperature (e.g., MODIS LST, which is often aggregated into multi-day composites to mitigate data reductions caused by cloud cover, changes in its relationship to air temperature

  7. Calibration plan for the sea and land surface temperature radiometer

    Science.gov (United States)

    Smith, David L.; Nightingale, Tim J.; Mortimer, Hugh; Middleton, Kevin; Edeson, Ruben; Cox, Caroline V.; Mutlow, Chris T.; Maddison, Brian J.

    2013-10-01

    The Sea and Land Surface Temperature Radiometer (SLSTR) to be flown on ESA's Sentinel-3 mission is a multichannel scanning radiometer that will continue the 21-year datasets of the Along Track Scanning Radiometer (ATSR) series. As its name implies, measurements from SLSTR will be used to retrieve global sea surface temperatures to an uncertainty of SLSTR instrument, infrared calibration sources and alignment equipment. The calibration rig has been commissioned and results of these tests will be presented. Finally the authors will present the planning for the on-orbit monitoring and calibration activities to ensure that calibration is maintained. These activities include vicarious calibration techniques that have been developed through previous missions, and the deployment of ship-borne radiometers.

  8. A surface acoustic wave ICP sensor with good temperature stability.

    Science.gov (United States)

    Zhang, Bing; Hu, Hong; Ye, Aipeng; Zhang, Peng

    2017-07-20

    Intracranial pressure (ICP) monitoring is very important for assessing and monitoring hydrocephalus, head trauma and hypertension patients, which could lead to elevated ICP or even devastating neurological damage. The mortality rate due to these diseases could be reduced through ICP monitoring, because precautions can be taken against the brain damage. This paper presents a surface acoustic wave (SAW) pressure sensor to realize ICP monitoring, which is capable of wireless and passive transmission with antenna attached. In order to improve the temperature stability of the sensor, two methods were adopted. First, the ST cut quartz was chosen as the sensor substrate due to its good temperature stability. Then, a differential temperature compensation method was proposed to reduce the effects of temperature. Two resonators were designed based on coupling of mode (COM) theory and the prototype was fabricated and verified using a system established for testing pressure and temperature. The experiment result shows that the sensor has a linearity of 2.63% and hysteresis of 1.77%. The temperature stability of the sensor has been greatly improved by using the differential compensation method, which validates the effectiveness of the proposed method.

  9. A New Estimate of the Earth's Land Surface Temperature History

    Science.gov (United States)

    Muller, R. A.; Curry, J. A.; Groom, D.; Jacobsen, B.; Perlmutter, S.; Rohde, R. A.; Rosenfeld, A.; Wickham, C.; Wurtele, J.

    2011-12-01

    The Berkeley Earth Surface Temperature team has re-evaluated the world's atmospheric land surface temperature record using a linear least-squares method that allow the use of all the digitized records back to 1800, including short records that had been excluded by prior groups. We use the Kriging method to estimate an optimal weighting of stations to give a world average based on uniform weighting of the land surface. We have assembled a record of the available data by merging 1.6 billion temperature reports from 16 pre-existing data archives; this data base will be made available for public use. The former Global Historic Climatology Network (GHCN) monthly data base shows a sudden drop in the number of stations reporting monthly records from 1980 to the present; we avoid this drop by calculating monthly averages from the daily records. By using all the data, we reduce the effects of potential data selection bias. We make an independent estimate of the urban heat island effect by calculating the world land temperature trends based on stations chosen to be far from urban sites. We calculate the effect of poor station quality, as documented in the US by the team led by Anthony Watts by estimating the temperature trends based solely on the stations ranked good (1,2 or 1,2,3 in the NOAA ranking scheme). We avoid issues of homogenization bias by using raw data; at times when the records are discontinuous (e.g. due to station moves) we break the record into smaller segments and analyze those, rather than attempt to correct the discontinuity. We estimate the uncertainties in the final results using the jackknife procedure developed by J. Tukey. We calculate spatial uncertainties by measuring the effects of geographical exclusion on recent data that have good world coverage. The results we obtain are compared to those published by the groups at NOAA, NASA-GISS, and Hadley-CRU in the UK.

  10. Effect of floor surface temperature on blood flow and skin temperature in the foot.

    Science.gov (United States)

    Song, G-S

    2008-12-01

    A total of 16 healthy college students participated as subjects to elucidate the hypothesis that blood flow and skin temperature in foot are affected by the floor surface temperature. The floor surface temperature was controlled by varying the temperature of water (tw) flowing underneath the floor, and it ranged from tw 15 to 40 degrees C at 5 degrees C intervals. The blood flow rate was measured in the dorsal right toe, and skin temperatures were measured for 60 min at 8 points: the neck, right scapular, left hand, right shin, left bottom of the toe, right instep, left finger, and rectum. The blood flow rate in the foot tissue was increased until the foot skin temperature warmed up to 34 degrees C (P = 0.000). The final skin temperatures on the bottom of the toe were 19.4 +/- 2.44 degrees C for tw 15 degrees C, 22.4 +/- 2.45 degrees C for tw 20 degrees C, 24.8 +/- 2.80 degrees C for tw 25 degrees C, 27.7 +/- 2.13 degrees C for tw 30 degrees C, 30.6 +/- 2.06 degrees C for tw 35 degrees C, 33.2 +/- 1.45 degrees C for tw 40 degrees C, 34.2 +/- 1.55 degrees C for tw 45 degrees C, and 35.2 +/- 1.65 degrees C for tw 50 degrees C. Considering blood flow and comfort, the partial floor heating system is suggested and the recommended floor surface temperature range is 27-33 degrees C. A warm floor surface can serve to satisfy occupants when the ambient temperature maintained at 20 degrees C which represents an energy conscious temperature. A warm floor can induce high blood perfusion in the feet and consequently improve an occupant's health by treating many vascular-related disorders. Even in a well-insulated residential building, a partially heated floor system could prevent overheating while providing surface warmth.

  11. Actual evaporation estimation from infrared measurement of soil surface temperature

    Directory of Open Access Journals (Sweden)

    Davide Pognant

    2013-09-01

    Full Text Available Within the hydrological cycle, actual evaporation represents the second most important process in terms of volumes of water transported, second only to the precipitation phenomena. Several methods for the estimation of the Ea were proposed by researchers in scientific literature, but the estimation of the Ea from potential evapotranspiration often requires the knowledge of hard-to-find parameters (e.g.: vegetation morphology, vegetation cover, interception of rainfall by the canopy, evaporation from the canopy surface and uptake of water by plant roots and many existing database are characterized by missing or incomplete information that leads to a rough estimation of the actual evaporation amount. Starting from the above considerations, the aim of this study is to develop and validate a method for the estimation of the Ea based on two steps: i the potential evaporation estimation by using the meteorological data (i.e. Penman-Monteith; ii application of a correction factor based on the infrared soil surface temperature measurements. The dataset used in this study were collected during two measurement campaigns conducted both in a plain testing site (Grugliasco, Italy, and in a mountain South-East facing slope (Cogne, Italy. During those periods, hourly measurement of air temperature, wind speed, infrared surface temperature, soil heat flux, and soil water content were collected. Results from the dataset collected in the two testing sites show a good agreement between the proposed method and reference methods used for the Ea estimation.

  12. Land surface temperature shaped by urban fractions in megacity region

    Science.gov (United States)

    Zhang, Xiaoxuan; Hu, Yonghong; Jia, Gensuo; Hou, Meiting; Fan, Yanguo; Sun, Zhongchang; Zhu, Yuxiang

    2017-02-01

    Large areas of cropland and natural vegetation have been replaced by impervious surfaces during the recent rapid urbanization in China, which has resulted in intensified urban heat island effects and modified local or regional warming trends. However, it is unclear how urban expansion contributes to local temperature change. In this study, we investigated the relationship between land surface temperature (LST) change and the increase of urban land signals. The megacity of Tianjin was chosen for the case study because it is representative of the urbanization process in northern China. A combined analysis of LST and urban land information was conducted based on an urban-rural transect derived from Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectrometer (MODIS), and QuickBird images. The results indicated that the density of urban land signals has intensified within a 1-km2 grid in the urban center with an impervious land fraction >60 %. However, the construction on urban land is quite different with low-/mid-rise buildings outnumbering high-rise buildings in the urban-rural transect. Based on a statistical moving window analysis, positive correlation ( R 2 > 0.9) is found between LST and urban land signals. Surface temperature change (ΔLST) increases by 0.062 °C, which was probably caused by the 1 % increase of urbanized land (ΔIF) in this case region.

  13. High temperature surface degradation of III-V nitrides

    Energy Technology Data Exchange (ETDEWEB)

    Vartuli, C.B.; Pearton, S.J.; Abernathy, C.R.; MacKenzie, J.D.; Lambers, E.S. [Univ. of Florida, Gainesville, FL (United States). Dept. of Materials Science and Engineering; Zolper, J.C. [Sandia National Labs., Albuquerque, NM (United States)

    1996-05-01

    The surface stoichiometry, surface morphology and electrical conductivity of AlN, GaN, InN, InGaN and InAlN was examined at rapid thermal annealing temperatures up to 1,150 C. The sheet resistance of the AlN dropped steadily with annealing, but the surface showed signs of roughening only above 1,000 C. Auger Electronic Spectroscopy (AES) analysis showed little change in the surface stoichiometry even at 1,150 C. GaN root mean square (RMS) surface roughness showed an overall improvement with annealing, but the surface became pitted at 1,000 C, at which point the sheet resistance also dropped by several orders of magnitude, and AES confirmed a loss of N from the surface. The InN surface had roughened considerably even at 650 C, and scanning electron microscopy (SEM) showed significant degradation. In contrast to the binary nitrides the sheet resistance of InAlN was found to increase by {approximately} 10{sup 2} from the as grown value after annealing at 800 C and then remain constant up to 1,000 C, while that of InGaN increased rapidly above 700 C. The RMS roughness increased above 800 C and 700 C respectively for InAlN and InGaN samples. In droplets began to form on the surface at 900 C for InAlN and at 800 C for InGaN, and then evaporate at 1,000 C leaving pits. AES analysis showed a decrease in the N concentration in the top 500 {angstrom} of the sample for annealing {ge} 800 C in both materials.

  14. Surface Tensions and Their Variations with Temperature and Impurities

    Science.gov (United States)

    Hardy, S. C.; Fine, J.

    1985-01-01

    The surface tensions in this work were determined using the sessile drop technique. This method is based on a comparison of the profile of a liquid drop with the profile calculated by solving the Young-Laplace equation. The comparison can be made in several ways; the traditional Bashforth-Adams procedure was used in conjunction with recently calculated drop shape tables which virtually eliminate interpolation errors. Although previous study has found little difference in measurements with pure and oxygen doped silicon, there is other evidence suggesting that oxygen in dilute concentrations severely depresses the surface tension of silicon. The surface tension of liquid silicon in purified argon atmospheres was measured. A temperature coefficient near -0.28 mJ/square meters K was found. The experiments show a high sensitivity of the surface tension to what is believed are low concentrations of oxygen. Thus one cannot rule out some effect of low levels of oxygen in the results. However, the highest surface tension values obtained in conditions which minimized the residual oxygen pressure are in good agreement with a previous measurement in pure hydrogen. Therefore, depression of the surface tension by oxygen is insignificant in these measurements.

  15. A New Approach to Data Assimilation

    Institute of Scientific and Technical Information of China (English)

    Wang Bin; ZHAO Ying

    2006-01-01

    A significant attempt to design a timesaving and efficient four-dimensional variational data assimilation dimensional variational data assimilation of mapped observation (3DVM)' is proposed, based on the new concept of mapped observation and the new idea of backward 4DVar. Like the available 4DVar, 3DVM produces an optimal initial condition (IC) that is consistent with the prediction model due to the inclusion of model constraints and best fits the observations in the assimilation window through the model solution trajectory. Different from the 4DVar, the IC derived from 3DVM is located at the end of the assimilation window rather than at the beginning conventionally. This change greatly reduces the computing cost for the new approach, which is almost the same as that of the three-dimensional variational data assimilation (3DVar). Especially, such a change is able to improve assimilation accuracy because it does not need the tangential linear and adjoint approximations to calculate the gradient of cost function. Therefore,in numerical test, the new approach produces better IC than 4DVar does for 72-h simulation of TY9914(Dan), by assimilating the three-dimensional fields of temperature and wind retrieved from the Advanced Microwave Sounding Unit-A (AMSU-A) observations. Meanwhile, it takes only 1/7 of the computing cost that the 4DVar requires for the same initialization with the same retrieved data.

  16. The Impact of "Bad" Argo Profiles on Ocean Data Assimilation

    Institute of Scientific and Technical Information of China (English)

    YAN Chang-Xiang; ZHU Jiang

    2010-01-01

    Recent studies have found cold biases in a fraction of Argo profiles (hereinafter referred to as bad Array for Real-time Geostrophic Oceanography (Argo) profiles) due to the pressure drifts during 2003 and 2006. These bad Argo profiles have had an important impact on in situ observation-based global ocean heat content estimates. This study investigated the impact of bad Argo profiles on ocean data assimilation results that were based on observations from diverse ocean observation systems, such as in situ profiles (e.g., Argo, expendable bathythermograph (XBT), and Tropical Atmosphere Ocean (TAO), remote-sensing sea surface temperature products and satellite altimetry between 2004 and 2006. Results from this work show that the upper ocean heat content analysis is vulnerable to bad Argo profiles and demonstrate a cooling trend in the studied period despite the multiple independent data types that were assimilated. When the bad Argo profiles were excluded from the assimilation, the decreased heat content disappeared and a warming occurred. Combination of satellite altimetry and mass variation data from gravity satellite demonstrated an increase, which agrees well with the increased heat content. Additionally, when an additional Argo profile quality control procedure was utilized that simply removed the profiles that presented static unstable water columns, the results were very similar to those obtained when the bad Argo profiles were excluded from the assimilation. This indicates that an ocean data assimilation that uses multiple data sources with improved quality control could be less vulnerable to a major observation system failure, such as a bad Argo event.

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

    Science.gov (United States)

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

    2012-04-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2015-01-01

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

  19. A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

    Science.gov (United States)

    Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

    2011-01-01

    Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

  20. Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines

    Directory of Open Access Journals (Sweden)

    Alfonso F. Torres-Rua

    2016-04-01

    Full Text Available Spatial surface soil moisture can be an important indicator of crop conditions on farmland, but its continuous estimation remains challenging due to coarse spatial and temporal resolution of existing remotely-sensed products. Furthermore, while preceding research on soil moisture using remote sensing (surface energy balance, weather parameters, and vegetation indices has demonstrated a relationship between these factors and soil moisture, practical continuous spatial quantification of the latter is still unavailable for use in water and agricultural management. In this study, a methodology is presented to estimate volumetric surface soil moisture by statistical selection from potential predictors that include vegetation indices and energy balance products derived from satellite (Landsat imagery and weather data as identified in scientific literature. This methodology employs a statistical learning machine called a Relevance Vector Machine (RVM to identify and relate the potential predictors to soil moisture by means of stratified cross-validation and forward variable selection. Surface soil moisture measurements from irrigated agricultural fields in Central Utah in the 2012 irrigation season were used, along with weather data, Landsat vegetation indices, and energy balance products. The methodology, data collection, processing, and estimation accuracy are presented and discussed.

  1. Decadal trends in Red Sea maximum surface temperature

    KAUST Repository

    Chaidez, Veronica

    2017-08-09

    Ocean warming is a major consequence of climate change, with the surface of the ocean having warmed by 0.11 °C decade-1 over the last 50 years and is estimated to continue to warm by an additional 0.6 - 2.0 °C before the end of the century1. However, there is considerable variability in the rates experienced by different ocean regions, so understanding regional trends is important to inform on possible stresses for marine organisms, particularly in warm seas where organisms may be already operating in the high end of their thermal tolerance. Although the Red Sea is one of the warmest ecosystems on earth, its historical warming trends and thermal evolution remain largely understudied. We characterized the Red Sea\\'s thermal regimes at the basin scale, with a focus on the spatial distribution and changes over time of sea surface temperature maxima, using remotely sensed sea surface temperature data from 1982 - 2015. The overall rate of warming for the Red Sea is 0.17 ± 0.07 °C decade-1, while the northern Red Sea is warming between 0.40 and 0.45 °C decade-1, all exceeding the global rate. Our findings show that the Red Sea is fast warming, which may in the future challenge its organisms and communities.

  2. An adaptive ensemble Kalman filter for soil moisture data assimilation

    Science.gov (United States)

    In a 19-year twin experiment for the Red-Arkansas river basin we assimilate synthetic surface soil moisture retrievals into the NASA Catchment land surface model. We demonstrate how poorly specified model and observation error parameters affect the quality of the assimilation products. In particul...

  3. On the accuracy of the simple ocean data assimilation analysis for estimating heat Budgets of the Near-Surface Arabian Sea and Bay of Bengal

    Digital Repository Service at National Institute of Oceanography (India)

    Shenoi, S.S.C.; Shankar, D.; Shetye, S.R.

    The accuracy of data from the Simple Ocean Data Assimilation (SODA) model for estimating the heat budget of the upper ocean is tested in the Arabian Sea and the Bay of Bengal. SODA is able to reproduce the changes in heat content when...

  4. Temperature-mediated transition from Dyakonov-Tamm surface waves to surface-plasmon-polariton waves

    Science.gov (United States)

    Chiadini, Francesco; Fiumara, Vincenzo; Mackay, Tom G.; Scaglione, Antonio; Lakhtakia, Akhlesh

    2017-08-01

    The effect of changing the temperature on the propagation of electromagnetic surface waves (ESWs), guided by the planar interface of a homogeneous isotropic temperature-sensitive material (namely, InSb) and a temperature-insensitive structurally chiral material (SCM) was numerically investigated in the terahertz frequency regime. As the temperature rises, InSb transforms from a dissipative dielectric material to a dissipative plasmonic material. Correspondingly, the ESWs transmute from Dyakonov-Tamm surface waves into surface-plasmon-polariton waves. The effects of the temperature change are clearly observed in the phase speeds, propagation distances, angular existence domains, multiplicity, and spatial profiles of energy flow of the ESWs. Remarkably large propagation distances can be achieved; in such instances the energy of an ESW is confined almost entirely within the SCM. For certain propagation directions, simultaneous excitation of two ESWs with (i) the same phase speeds but different propagation distances or (ii) the same propagation distances but different phase speeds are also indicated by our results.

  5. Gaia FGK Benchmark Stars: Effective temperatures and surface gravities

    CERN Document Server

    Heiter, U; Gustafsson, B; Korn, A J; Soubiran, C; Thévenin, F

    2015-01-01

    Large Galactic stellar surveys and new generations of stellar atmosphere models and spectral line formation computations need to be subjected to careful calibration and validation and to benchmark tests. We focus on cool stars and aim at establishing a sample of 34 Gaia FGK Benchmark Stars with a range of different metallicities. The goal was to determine the effective temperature and the surface gravity independently from spectroscopy and atmospheric models as far as possible. Fundamental determinations of Teff and logg were obtained in a systematic way from a compilation of angular diameter measurements and bolometric fluxes, and from a homogeneous mass determination based on stellar evolution models. The derived parameters were compared to recent spectroscopic and photometric determinations and to gravity estimates based on seismic data. Most of the adopted diameter measurements have formal uncertainties around 1%, which translate into uncertainties in effective temperature of 0.5%. The measurements of bol...

  6. Global Surface Temperature Response Explained by Multibox Energy Balance Models

    Science.gov (United States)

    Fredriksen, H. B.; Rypdal, M.

    2016-12-01

    We formulate a multibox energy balance model, from which global temperature evolution can be described by convolving a linear response function and a forcing record. We estimate parameters in the response function from instrumental data and historic forcing, such that our model can produce a response to both deterministic forcing and stochastic weather forcing consistent with observations. Furthermore, if we make separate boxes for upper ocean layer and atmosphere over land, we can also make separate response functions for global land and sea surface temperature. By describing internal variability as a linear response to white noise, we demonstrate that the power-law form of the observed temperature spectra can be described by linear dynamics, contrary to a common belief that these power-law spectra must arise from nonlinear processes. In our multibox model, the power-law form can arise due to the multiple response times. While one of our main points is that the climate system responds over a wide range of time scales, we cannot find one set of time scales that can be preferred compared to other choices. Hence we think the temperature response can best be characterized as something that is scale-free, but still possible to approximate by a set of well separated time scales.

  7. Geostatistical Solutions for Downscaling Remotely Sensed Land Surface Temperature

    Science.gov (United States)

    Wang, Q.; Rodriguez-Galiano, V.; Atkinson, P. M.

    2017-09-01

    Remotely sensed land surface temperature (LST) downscaling is an important issue in remote sensing. Geostatistical methods have shown their applicability in downscaling multi/hyperspectral images. In this paper, four geostatistical solutions, including regression kriging (RK), downscaling cokriging (DSCK), kriging with external drift (KED) and area-to-point regression kriging (ATPRK), are applied for downscaling remotely sensed LST. Their differences are analyzed theoretically and the performances are compared experimentally using a Landsat 7 ETM+ dataset. They are also compared to the classical TsHARP method.

  8. Effect of surface nanostructure on temperature programmed reaction spectroscopy

    Science.gov (United States)

    Rieger, Michael; Rogal, Jutta; Reuter, Karsten

    2008-03-01

    Using the catalytic CO oxidation at RuO2(110) as a showcase, we employ first-principles kinetic Monte Carlo simulations to illustrate the intricate effects on temperature programmed reaction (TPR) spectroscopy data brought about by the mere correlations between the locations of the active sites at a nanostructured surface. Even in the absence of lateral interactions, this nanostructure alone can cause inhomogeneities that cannot be grasped by prevalent mean-field data analysis procedures, which thus lead to wrong conclusions on the reactivity of the different surface species. The RuO2(110) surface studied here exhibits only two prominent active sites, arranged in simple alternating rows. Yet, the mere neglection of this still quite trivial nanostructure leads mean-field TPR data analysis [1] to extract kinetic parameters that are in error by several orders of magnitude and that do not even reflect the relative reactivity of the different surface species correctly [2].[1] S. Wendt, M. Knapp, and H. Over, JACS 126, 1537 (2004).[2] M. Rieger, J. Rogal, and K. Reuter, Phys. Rev. Lett (in press).

  9. Satellite radiance data assimilation for rainfall prediction in Java Region

    Science.gov (United States)

    Sagita, Novvria; Hidayati, Rini; Hidayat, Rahmat; Gustari, Indra

    2017-01-01

    This study examined the influence of satellite radiance data assimilation for predicting two days of heavy rainfall in the Java region. The first case occurred from 22 to 23 on January 2015 while the second case occurred from 1 to 2 on February 2015. The analysis examined before and after data assimilation in the two cases study. The Global Forecast System (GFS) data were used as initial condition which was assimilated with several data such as surface observation data, radiance data from AMSUA sensor, radiance data from HIRS sensor, and radiance data from MHS sensor. Weather Research and Forecasting Data Assimilation (WRFDA) is a tool which is used in this study for assimilating process with Three Dimensional Variation (3D-Var) method. The Quantitative Precipitation Forecast (QPF) skill was used to evaluate influence data assimilation for rainfall prediction. The result of the study obtained different rainfall prediction with different data assimilation. In general, the surface observation data assimilation has lower QPF skill than the satellite radiance data assimilation. Even thought radiance data assimilation has slightly contribution on rainfall prediction, but it gave better accuracy on rainfall prediction for two heavy rainfall cases.

  10. Detection and attribution of near surface temperature changes over homogenous temperature zones in India

    Science.gov (United States)

    Achutarao, K. M.; R, D.

    2015-12-01

    The IPCC Fifth Assessment Report concluded, "More than half of the observed increase in global mean surface temperature (GMST) from 1951 to 2010 is very likely due to the observed anthropogenic increase in greenhouse gas (GHG) concentrations." Detecting and attributing the changes over regional scales can provide more relevant information to policymakers at the national level but the low signal-to-noise ratios at smaller spatial scales make this a harder problem. In this study, we analyze changes in temperature (annual and seasonal means of mean, minimum, and maximum temperatures) over 7 homogeneous temperature zones of India from 1901 -2005 using models from the CMIP5 database and multiple observational datasets (CRU-3.22, and IITM). We perform Detection and Attribution (D&A) analysis using fingerprint methods by defining a signal that concisely express both spatial and temporal changes found in the model runs with the CMIP5 individual forcing runs; greenhouse (historicalGHG), natural (historicalNat), anthropogenic (historicalAnthro), and anthropogenic aerosols (historicalAA). We are able to detect changes in annual mean temperature over many of the homogenous temperature zones as well as seasonal means in some of the homogenous zones. We quantify the contributions resulting from individual forcings in these cases. Preliminary results indicate large contributions from anthropogenic, forcings with a negligible contribution from natural forcings.

  11. Customer-oriented Data Formats and Services for Global Land Data Assimilation System (GLDAS) Products at the NASA GES DISC

    Science.gov (United States)

    Fang, Hongliang; Beaudoing, Hiroko; Rodell, Matthew; Teng, BIll; Vollmer, Bruce

    2008-01-01

    The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface Models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of NASA Goddard Earth Sciences Data and Information Services Center (GESDISC).

  12. Theoretical study of cathode surfaces and high-temperature superconductors

    Science.gov (United States)

    Mueller, Wolfgang

    1995-01-01

    Calculations are presented for the work functions of BaO on W, Os, Pt, and alloys of Re-W, Os-W, and Ir-W that are in excellent agreement with experiment. The observed emission enhancement for alloy relative to tungsten dispenser cathodes is attributed to properties of the substrate crystal structure and explained by the smaller depolarization of the surface dipole on hexagonal as compared to cubic substrates. For Ba and BaO on W(100), the geometry of the adsorbates has been determined by a comparison of inverse photoemission spectra with calculated densities of unoccupied states based on the fully relativistic embedded cluster approach. Results are also discussed for models of scandate cathodes and the electronic structure of oxygen on W(100) at room and elevated temperatures. A detailed comparison is made for the surface electronic structure of the high-temperature superconductor YBa2Cu3O7 as obtained with non-, quasi-, and fully relativistic cluster calculations.

  13. Afforestation in China cools local land surface temperature.

    Science.gov (United States)

    Peng, Shu-Shi; Piao, Shilong; Zeng, Zhenzhong; Ciais, Philippe; Zhou, Liming; Li, Laurent Z X; Myneni, Ranga B; Yin, Yi; Zeng, Hui

    2014-02-25

    China has the largest afforested area in the world (∼62 million hectares in 2008), and these forests are carbon sinks. The climatic effect of these new forests depends on how radiant and turbulent energy fluxes over these plantations modify surface temperature. For instance, a lower albedo may cause warming, which negates the climatic benefits of carbon sequestration. Here, we used satellite measurements of land surface temperature (LST) from planted forests and adjacent grasslands or croplands in China to understand how afforestation affects LST. Afforestation is found to decrease daytime LST by about 1.1 ± 0.5 °C (mean ± 1 SD) and to increase nighttime LST by about 0.2 ± 0.5 °C, on average. The observed daytime cooling is a result of increased evapotranspiration. The nighttime warming is found to increase with latitude and decrease with average rainfall. Afforestation in dry regions therefore leads to net warming, as daytime cooling is offset by nighttime warming. Thus, it is necessary to carefully consider where to plant trees to realize potential climatic benefits in future afforestation projects.

  14. A New Global Climatology of Annual Land Surface Temperature

    Directory of Open Access Journals (Sweden)

    Benjamin Bechtel

    2015-03-01

    Full Text Available Land surface temperature (LST is an important parameter in various fields including hydrology, climatology, and geophysics. Its derivation by thermal infrared remote sensing has long tradition but despite substantial progress there remain limited data availability and challenges like emissivity estimation, atmospheric correction, and cloud contamination. The annual temperature cycle (ATC is a promising approach to ease some of them. The basic idea to fit a model to the ATC and derive annual cycle parameters (ACP has been proposed before but so far not been tested on larger scale. In this study, a new global climatology of annual LST based on daily 1 km MODIS/Terra observations was processed and evaluated. The derived global parameters were robust and free of missing data due to clouds. They allow estimating LST patterns under largely cloud-free conditions at different scales for every day of year and further deliver a measure for its accuracy respectively variability. The parameters generally showed low redundancy and mostly reflected real surface conditions. Important influencing factors included climate, land cover, vegetation phenology, anthropogenic effects, and geology which enable numerous potential applications. The datasets will be available at the CliSAP Integrated Climate Data Center pending additional processing.

  15. MEaSUREs Land Surface Temperature from GOES Satellites

    Science.gov (United States)

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

    2017-04-01

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

  16. DasPy 1.0 – the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5

    Directory of Open Access Journals (Sweden)

    X. Han

    2015-08-01

    Full Text Available Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM, COsmic-ray Soil Moisture Interaction Code (COSMIC and the Two-Source Formulation (TSF were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture, L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized

  17. DasPy 1.0 - the Open Source Multivariate Land Data Assimilation Framework in combination with the Community Land Model 4.5

    Science.gov (United States)

    Han, X.; Li, X.; He, G.; Kumbhar, P.; Montzka, C.; Kollet, S.; Miyoshi, T.; Rosolem, R.; Zhang, Y.; Vereecken, H.; Franssen, H.-J. H.

    2015-08-01

    Data assimilation has become a popular method to integrate observations from multiple sources with land surface models to improve predictions of the water and energy cycles of the soil-vegetation-atmosphere continuum. Multivariate data assimilation refers to the simultaneous assimilation of observation data from multiple model state variables into a simulation model. In recent years, several land data assimilation systems have been developed in different research agencies. Because of the software availability or adaptability, these systems are not easy to apply for the purpose of multivariate land data assimilation research. We developed an open source multivariate land data assimilation framework (DasPy) which is implemented using the Python script language mixed with the C++ and Fortran programming languages. LETKF (Local Ensemble Transform Kalman Filter) is implemented as the main data assimilation algorithm, and uncertainties in the data assimilation can be introduced by perturbed atmospheric forcing data, and represented by perturbed soil and vegetation parameters and model initial conditions. The Community Land Model (CLM) was integrated as the model operator. The implementation allows also parameter estimation (soil properties and/or leaf area index) on the basis of the joint state and parameter estimation approach. The Community Microwave Emission Modelling platform (CMEM), COsmic-ray Soil Moisture Interaction Code (COSMIC) and the Two-Source Formulation (TSF) were integrated as observation operators for the assimilation of L-band passive microwave, cosmic-ray soil moisture probe and land surface temperature measurements, respectively. DasPy has been evaluated in several assimilation studies of neutron count intensity (soil moisture), L-band brightness temperature and land surface temperature. DasPy is parallelized using the hybrid Message Passing Interface and Open Multi-Processing techniques. All the input and output data flows are organized efficiently

  18. A protocol for validating Land Surface Temperature from Sentinel-3

    Science.gov (United States)

    Ghent, D.

    2015-12-01

    One of the main objectives of the Sentinel-3 mission is to measure sea- and land-surface temperature with high-end accuracy and reliability in support of environmental and climate monitoring in an operational context. Calibration and validation are thus key criteria for operationalization within the framework of the Sentinel-3 Mission Performance Centre (S3MPC).Land surface temperature (LST) has a long heritage of satellite observations which have facilitated our understanding of land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. These observations have been acquired from a variety of satellite instruments on platforms in both low-earth orbit and in geostationary orbit. Retrieval accuracy can be a challenge though; surface emissivities can be highly variable owing to the heterogeneity of the land, and atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. As such, a rigorous validation is critical in order to assess the quality of the data and the associated uncertainties. The Sentinel-3 Cal-Val Plan for evaluating the level-2 SL_2_LST product builds on an established validation protocol for satellite-based LST. This set of guidelines provides a standardized framework for structuring LST validation activities, and is rapidly gaining international recognition. The protocol introduces a four-pronged approach which can be summarised thus: i) in situ validation where ground-based observations are available; ii) radiance-based validation over sites that are homogeneous in emissivity; iii) intercomparison with retrievals from other satellite sensors; iv) time-series analysis to identify artefacts on an interannual time-scale. This multi-dimensional approach is a necessary requirement for assessing the performance of the LST algorithm for SLSTR which is designed around biome-based coefficients, thus emphasizing the importance of

  19. Assimilation of satellite altimetry data in hydrological models for improved inland surface water information: Case studies from the "Sentinel-3 Hydrologic Altimetry Processor prototypE" project (SHAPE)

    Science.gov (United States)

    Gustafsson, David; Pimentel, Rafael; Fabry, Pierre; Bercher, Nicolas; Roca, Mónica; Garcia-Mondejar, Albert; Fernandes, Joana; Lázaro, Clara; Ambrózio, Américo; Restano, Marco; Benveniste, Jérôme

    2017-04-01

    This communication is about the Sentinel-3 Hydrologic Altimetry Processor prototypE (SHAPE) project, with a focus on the components dealing with assimilation of satellite altimetry data into hydrological models. The SHAPE research and development project started in September 2015, within the Scientific Exploitation of Operational Missions (SEOM) programme of the European Space Agency. The objectives of the project are to further develop and assess recent improvement in altimetry data, processing algorithms and methods for assimilation in hydrological models, with the overarching goal to support improved scientific use of altimetry data and improved inland water information. The objective is also to take scientific steps towards a future Inland Water dedicated processor on the Sentinel-3 ground segment. The study focuses on three main variables of interest in hydrology: river stage, river discharge and lake level. The improved altimetry data from the project is used to estimate river stage, river discharge and lake level information in a data assimilation framework using the hydrological dynamic and semi-distributed model HYPE (Hydrological Predictions for the Environment). This model has been developed by SMHI and includes data assimilation module based on the Ensemble Kalman filter method. The method will be developed and assessed for a number of case studies with available in situ reference data and satellite altimetry data based on mainly the CryoSat-2 mission on which the new processor will be run; Results will be presented from case studies on the Amazon and Danube rivers and Lake Vänern (Sweden). The production of alti-hydro products (water level time series) are improved thanks to the use of water masks. This eases the geo-selection of the CryoSat-2 altimetric measurements since there are acquired from a geodetic orbit and are thus spread along the river course in space and and time. The specific processing of data from this geodetic orbit space

  20. A Preliminary Study of Surface Temperature Cold Bias in COAMPS

    Energy Technology Data Exchange (ETDEWEB)

    Chin, H-N S; Leach, M J; Sugiyama, G A; Aluzzi, F J

    2001-04-27

    It is well recognized that the model predictability is more or less hampered by the imperfect representations of atmospheric state and model physics. Therefore, it is a common problem for any numerical models to exhibit some sorts of biases in the prediction. In this study, the emphasis is focused on the cold bias of surface temperature forecast in Naval Research Laboratory's three-dimensional mesoscale model, COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System). Based on the comparison with the ground station data, there were two types of ground temperature cold biases identified in LLNL (Lawrence Livermore National Laboratory) operational forecasts of COAMPS over the California and Nevada regions during the 1999 winter and the 2000 spring. The first type of cold bias appears at high elevation regions covered by snow, and its magnitude can be as large as 30 F - 40 F lower than observed. The second type of cold bias mainly exists in the snow-free clear-sky regions, where the surface temperature is above the freezing point, and its magnitude can be up to 5 F - 10 F lower than observed. These cold biases can affect the low-level stratification, and even the diurnal variation of winds in the mountain regions, and therefore impact the atmospheric dispersion forecast. The main objective of this study is to explore the causes of such cold bias, and to further the improvement of the forecast performance in COAMPS. A series of experiments are performed to gauge the sensitivity of the model forecast due to the physics changes and large-scale data with various horizontal and vertical resolutions.

  1. Reevaluation of mid-Pliocene North Atlantic sea surface temperatures

    Science.gov (United States)

    Robinson, Marci M.; Dowsett, Harry J.; Dwyer, Gary S.; Lawrence, Kira T.

    2008-01-01

    Multiproxy temperature estimation requires careful attention to biological, chemical, physical, temporal, and calibration differences of each proxy and paleothermometry method. We evaluated mid-Pliocene sea surface temperature (SST) estimates from multiple proxies at Deep Sea Drilling Project Holes 552A, 609B, 607, and 606, transecting the North Atlantic Drift. SST estimates derived from faunal assemblages, foraminifer Mg/Ca, and alkenone unsaturation indices showed strong agreement at Holes 552A, 607, and 606 once differences in calibration, depth, and seasonality were addressed. Abundant extinct species and/or an unrecognized productivity signal in the faunal assemblage at Hole 609B resulted in exaggerated faunal-based SST estimates but did not affect alkenone-derived or Mg/Ca–derived estimates. Multiproxy mid-Pliocene North Atlantic SST estimates corroborate previous studies documenting high-latitude mid-Pliocene warmth and refine previous faunal-based estimates affected by environmental factors other than temperature. Multiproxy investigations will aid SST estimation in high-latitude areas sensitive to climate change and currently underrepresented in SST reconstructions.

  2. Martian Surface Temperature and Spectral Response from the MSL REMS Ground Temperature Sensor

    Science.gov (United States)

    Martin-Torres, Javier; Martínez-Frías, Jesús; Zorzano, María-Paz; Serrano, María; Mendaza, Teresa; Hamilton, Vicky; Sebastián, Eduardo; Armiens, Carlos; Gómez-Elvira, Javier; REMS Team

    2013-04-01

    The Rover Environmental Monitoring Station (REMS) on the Mars Science Laboratory (MSL) offers the opportunity to explore the near surface atmospheric conditions and, in particular will shed new light into the heat budget of the Martian surface. This is important for studies of the atmospheric boundary layer (ABL), as the ground and air temperatures measured directly by REMS control the coupling of the atmosphere with the surface [Zurek et al., 1992]. This coupling is driven by solar insolation. The ABL plays an important role in the general circulation and the local atmospheric dynamics of Mars. One of the REMS sensors, the ground temperature sensor (GTS), provides the data needed to study the thermal inertia properties of the regolith and rocks beneath the MSL rover. The GTS includes thermopile detectors, with infrared bands of 8-14 µm and 16-20 µm [Gómez-Elvira et al., 2012]. These sensors are clustered in a single location on the MSL mast and the 8-14 µm thermopile sounds the surface temperature. The infrared radiation reaching the thermopile is proportional to the emissivity of the surface minerals across these thermal wavelengths. We have developed a radiative transfer retrieval method for the REMS GTS using a database of thermal infrared laboratory spectra of analogue minerals and their mixtures. [Martín Redondo et al. 2009, Martínez-Frías et al. 2012 - FRISER-IRMIX database]. This method will be used to assess the perfomance of the REMS GTS as well as determine, through the error analysis, the surface temperature and emissivity values where MSL is operating. Comparisons with orbiter data will be performed. References Gómez-Elvira et al. [2012], REMS: The Environmental Sensor Suite for the Mars Science Laboratory Rover, Space Science Reviews, Volume 170, Issue 1-4, pp. 583-640. Martín-Redondo et al. [2009] Journal of Environmental Monitoring 11:, pp. 1428-1432. Martínez-Frías et al. [2012] FRISER-IRMIX database http

  3. Multiproxy summer and winter surface air temperature field reconstructions for southern South America covering the past centuries

    Energy Technology Data Exchange (ETDEWEB)

    Neukom, R.; Grosjean, M.; Wanner, H. [University of Bern, Oeschger Centre for Climate Change Research (OCCR), Bern (Switzerland); University of Bern, Institute of Geography, Climatology and Meteorology, Bern (Switzerland); Luterbacher, J. [Justus Liebig University of Giessen, Department of Geography, Climatology, Climate Dynamics and Climate Change, Giessen (Germany); Villalba, R.; Morales, M.; Srur, A. [CONICET, Instituto Argentino de Nivologia, Glaciologia y Ciencias Ambientales (IANIGLA), Mendoza (Argentina); Kuettel, M. [University of Bern, Oeschger Centre for Climate Change Research (OCCR), Bern (Switzerland); University of Bern, Institute of Geography, Climatology and Meteorology, Bern (Switzerland); University of Washington, Department of Earth and Space Sciences, Seattle (United States); Frank, D. [Swiss Federal Research Institute WSL, Birmensdorf (Switzerland); Jones, P.D. [University of East Anglia, Climatic Research Unit, School of Environmental Sciences, Norwich (United Kingdom); Aravena, J.-C. [Centro de Estudios Cuaternarios de Fuego Patagonia y Antartica (CEQUA), Punta Arenas (Chile); Black, D.E. [Stony Brook University, School of Marine and Atmospheric Sciences, Stony Brook (United States); Christie, D.A.; Urrutia, R. [Universidad Austral de Chile Valdivia, Laboratorio de Dendrocronologia, Facultad de Ciencias Forestales y Recursos Naturales, Valdivia (Chile); D' Arrigo, R. [Earth Institute at Columbia University, Tree-Ring Laboratory, Lamont-Doherty Earth Observatory, Palisades, NY (United States); Lara, A. [Universidad Austral de Chile Valdivia, Laboratorio de Dendrocronologia, Facultad de Ciencias Forestales y Recursos Naturales, Valdivia (Chile); Nucleo Cientifico Milenio FORECOS, Fundacion FORECOS, Valdivia (Chile); Soliz-Gamboa, C. [Utrecht Univ., Inst. of Environmental Biology, Utrecht (Netherlands); Gunten, L. von [Univ. of Bern (Switzerland); Univ. of Massachusetts, Climate System Research Center, Amherst (United States)

    2011-07-15

    We statistically reconstruct austral summer (winter) surface air temperature fields back to ad 900 (1706) using 22 (20) annually resolved predictors from natural and human archives from southern South America (SSA). This represents the first regional-scale climate field reconstruction for parts of the Southern Hemisphere at this high temporal resolution. We apply three different reconstruction techniques: multivariate principal component regression, composite plus scaling, and regularized expectation maximization. There is generally good agreement between the results of the three methods on interannual and decadal timescales. The field reconstructions allow us to describe differences and similarities in the temperature evolution of different sub-regions of SSA. The reconstructed SSA mean summer temperatures between 900 and 1350 are mostly above the 1901-1995 climatology. After 1350, we reconstruct a sharp transition to colder conditions, which last until approximately 1700. The summers in the eighteenth century are relatively warm with a subsequent cold relapse peaking around 1850. In the twentieth century, summer temperatures reach conditions similar to earlier warm periods. The winter temperatures in the eighteenth and nineteenth centuries were mostly below the twentieth century average. The uncertainties of our reconstructions are generally largest in the eastern lowlands of SSA, where the coverage with proxy data is poorest. Verifications with independent summer temperature proxies and instrumental measurements suggest that the interannual and multi-decadal variations of SSA temperatures are well captured by our reconstructions. This new dataset can be used for data/model comparison and data assimilation as well as for detection and attribution studies at sub-continental scales. (orig.)

  4. Displacement Data Assimilation

    CERN Document Server

    Rosenthal, W Steven; Mariano, Arthur J; Restrepo, Juan M

    2016-01-01

    We show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially observed state vectors in a setting where feature information important. While the displacement transformation is not tied to any particular assimilation scheme, here we implement it within an ensemble Kalman Filter and demonstrate its effectiveness in tracking stochastically perturbed vortices.

  5. A parsimonious land data assimilation system for the SMAP/GPM satellite era

    Science.gov (United States)

    Land data assimilation systems typically require complex parameterizations in order to: define required observation operators, quantify observing/forecasting errors and calibrate a land surface assimilation model. These parameters are commonly defined in an arbitrary manner and, if poorly specified,...

  6. A dual-pass data assimilation scheme for estimating turbulent fluxes with FY3A data

    Directory of Open Access Journals (Sweden)

    T. R. Xu

    2012-07-01

    Full Text Available A dual-pass data assimilation scheme is developed to improve predictions of turbulent fluxes with FY3A land surface temperature (LST data. This scheme is constructed based on the ensemble Kalman filter (EnKF and common land model (CoLM. Pass 1 of the dual-pass data assimilation scheme optimizes model vegetation parameters at a long temporal scale and pass 2 optimizes soil moisture at a short temporal scale. Four sites are selected for the data assimilation experiments, namely Arou, BJ, Guantao, and Miyun in the People's Republic of China (PRC that include grass, alpine meadow, crop, and orchard land cover types. The results are compared with data generated by a multi-scale turbulent flux observation system that includes an eddy covariance (EC and a large aperture scintillometer (LAS system. Results indicate that the CoLM can simulate the diurnal variations of turbulent flux, but usually underestimates the latent heat flux and evaporation fraction (EF and overestimates sensible heat flux. With the assimilation of FY3A LST data, the dual-pass data assimilation scheme can improve the predictions of turbulent flux. The average root mean square error (RMSE values drop from 81.2 to 39.6 W m−2 and from 101.7 to 58.9 W m−2 (the RMSE values drop 51.2% and 42.1% for sensible and latent heat fluxes, respectively. To compare the results with LAS measurements, the source areas are calculated using a footprint model and overlaid with FY3A pixels since the LAS cover more than one FY3A pixel. The comparisons show that the assimilation results are closer to LAS measurements. With the dual-pass data assimilation scheme, the estimated soil moistures are generally closer to observations. Furthermore, the vegetation parameters are retrieved and incorporated into CoLM which enhanced the model's predictive abilities.

  7. Eddy-Induced Ekman Pumping from Sea-Surface Temperature and Surface Current Effects

    Science.gov (United States)

    Gaube, P.; Chelton, D. B.; O'Neill, L. W.

    2011-12-01

    Numerous past studies have discussed the biological importance of upwelling of nutrients into the interiors of nonlinear eddies. Such upwelling can occur during the transient stages of formation of cyclones from shoaling of the thermocline. In their mature stages, upwelling can occur from Ekman pumping driven by eddy-induced wind stress curl. Previous investigations of ocean-atmosphere interaction in regions of persistent sea-surface temperature (SST) frontal features have shown that the wind field is locally stronger over warm water and weaker over cold water. Spatial variability of the SST field thus results in a wind stress curl and an associated Ekman pumping in regions of crosswind temperature gradients. It can therefore be anticipated that any SST anomalies associated with eddies can generate Ekman pumping in the eddy interiors. Another mechanism for eddy-induced Ekman pumping is the curl of the stress on the sea surface that arises from the difference between the surface wind velocity and the surface ocean velocity. While SST-induced Ekman upwelling can occur over eddies of either polarity surface current effects on Ekman upwelling occur only over anticyclonic eddies The objective of this study is to determine the spatial structures and relative magnitudes of the two mechanisms for eddy-induced Ekman pumping within the interiors of mesoscale eddies. This is achieved by collocating satellite-based measurements of SST, surface winds and wind stress curl to the interiors of eddies identified and tracked with an automated procedure applied to the sea-surface height (SSH) fields in the Reference Series constructed by AVISO from the combined measurements by two simultaneously operating altimeters. It is shown that, on average, the wind stress curl from eddy-induced surface currents is largest at the eddy center, resulting in Ekman pumping velocities of order 10 cm day-1. While this surface current-induced Ekman pumping depends only weakly on the wind direction

  8. Assimilation of IRS-P4 (MSMR) meteorological data in the NCMRWF global data assimilation system

    Indian Academy of Sciences (India)

    Rupa Kamineni; S R H Rizvi; S C Kar; U C Mohanty; R K Paliwal

    2002-09-01

    Oceansat-1 was successfully launched by India in 1999, with two payloads, namely Multi-frequency Scanning Microwave Radiometer (MSMR) and Ocean Color Monitor (OCM) to study the biological and physical parameters of the ocean. The MSMR sensor is configured as an eight-channel radiometer using four frequencies with dual polarization. The MSMR data at 75km resolution from the Oceansat-I have been assimilated in the National Centre for Medium Range Weather Forecasting (NCMRWF) data assimilation forecast system. The operational analysis and forecast system at NCMRWF is based on a T80L18 global spectral model and Spectral Statistical Inter-polation (SSI) scheme for data analysis. The impact of the MSMR data is seen globally, however it is significant over the oceanic region where conventional data are rare. The dry-nature of the control analyses have been removed by utilizing the MSMR data. Therefore, the total precipitable water data from MSMR has been identified as a very crucial parameter in this study. The impact of surface wind speed from MSMR is to increase easterlies over the tropical Indian Ocean. Shifting of the positions of westerly troughs and ridges in the south Indian Ocean has contributed to reduction of temperature to around 30°S.

  9. Data Assimilation: Making Sense of Earth Observation

    Directory of Open Access Journals (Sweden)

    William Albert Lahoz

    2014-05-01

    Full Text Available Climate change, air quality and environmental degradation are important societal challenges for the 21st Century. These challenges require an intelligent response from society, which in turn requires access to information about the Earth System. This information comes from observations and prior knowledge, the latter typically embodied in a model describing relationships between variables of the Earth System. Data assimilation provides an objective methodology to combine observational and model information to provide an estimate of the most likely state and its uncertainty for the whole Earth System. This approach adds value to the observations – by filling in the spatio-temporal gaps in observations; and to the model – by constraining it with the observations. In this review paper we motivate data assimilation as a methodology to fill in the gaps in observational information; illustrate the data assimilation approach with examples that span a broad range of features of the Earth System (atmosphere, including chemistry; ocean; land surface; and discuss the outlook for data assimilation, including the novel application of data assimilation ideas to observational information obtained using Citizen Science. Ultimately, a strong motivation of data assimilation is the many benefits it provides to users. These include: providing the initial state for weather and air quality forecasts; providing analyses and reanalyses for studying the Earth System; evaluating observations, instruments and models; assessing the relative value of elements of the Global Observing System (GOS; and assessing the added value of future additions to the GOS.

  10. Measuring surface temperature of isolated neutron stars and related problems

    Science.gov (United States)

    Teter, Marcus Alton

    New and exciting results for measuring neutron star surface temperatures began with the successful launch of the Chandra X-ray observatory. Among these results are new detections of neutron star surface temperatures which have made it possible to seriously test neutron star thermal evolution theories. The important new temperature determination of the Vela pulsar (Pavlov, et al., 2001a) requires a non-standard cooling scenario to explain it. Apart from this result, we have measured PSR B1055-52's surface temperature in this thesis, determining that it can be explained by standard cooling with heating. Our spectral fit of the combined data from ROSAT and Chandra have shown that a three component model, two thermal blackbodies and an non-thermal power-law, is required to explain the data. Furthermore, our phase resolved spectroscopy has begun to shed light on the geometry of the hot spot on PSR B1055-52's surface as well as the structure of the magnetospheric radiation. Also, there is strong evidence for a thermal distribution over its surface. Most importantly, the fact that PSR B1055-52 does not have a hydrogen atmosphere has been firmly established. To reconcile these two key observations, on the Vela pulsar and PSR B1055-52, we tested neutron star cooling with neutrino processes including the Cooper pair neutrino emission process. Overall, it has been found that a phase change associated with pions being present in the cores of more massive neutron stars explains all current of the data. A transition from neutron matter to pion condensates in the central stellar core explains the difference between standard and non-standard cooling scenarios, because the superfluid suppression of pion cooling will reduce the emissivity of the pion direct URCA process substantially. A neutron star with a mass of [Special characters omitted.] with a medium stiffness equation of state and a T72 type neutron superfluid models the standard cooling case well. A neutron star of [Special

  11. Assimilation of Aura Ozone Data and Comparisons with In Situ Observations

    Science.gov (United States)

    Stajner, Ivanka; Wargan, Krzysztof; Pawson, Steven

    2008-01-01

    Ozone data from the Ozone Monitoring Instrument (OMI) and the Microwave Limb Sounder (MLS) onboard EOS Aura satellite were assimilated into the Goddard Earth Observing System Version 4 (GEOS-4) ozone assimilation system. Comparison of assimilated ozone with ozone sonde and MOZAIC data indicate an agreement within 10% in the lower stratosphere, where dynamical processes dominate. Assimilation of OMI and MLS data improves tropospheric column estimates in the Atlantic region, but leads to an overestimation in the tropical Pacific in comparison with SHADOZ sondes. Transport and data biases are considered in order to understand these discrepancies. Comparisons of assimilated tropospheric ozone columns with ozone sonde data reveal root-mean-square (RMS) differences of 2.9 to 7.2 DU, which are typically smaller than the model-sonde RMS differences. Four different definitions of the tropopause using temperature lapse rate, potential vorticity (PV) and isentropic surfaces or ozone isosurfaces are compared with respect to their global impact on the estimated tropospheric ozone column. The largest sensitivity in the tropospheric ozone column is found near the subtropical jet, where the ozone or PV determined tropopause typically lies below the lapse rate tropopause.

  12. Assimilation of Aura Ozone Data and Comparisons with In Situ Observations

    Science.gov (United States)

    Stajner, Ivanka; Wargan, Krzysztof; Pawson, Steven

    2008-01-01

    Ozone data from the Ozone Monitoring Instrument (OMI) and the Microwave Limb Sounder (MLS) onboard EOS Aura satellite were assimilated into the Goddard Earth Observing System Version 4 (GEOS-4) ozone assimilation system. Comparison of assimilated ozone with ozone sonde and MOZAIC data indicate an agreement within 10% in the lower stratosphere, where dynamical processes dominate. Assimilation of OMI and MLS data improves tropospheric column estimates in the Atlantic region, but leads to an overestimation in the tropical Pacific in comparison with SHADOZ sondes. Transport and data biases are considered in order to understand these discrepancies. Comparisons of assimilated tropospheric ozone columns with ozone sonde data reveal root-mean-square (RMS) differences of 2.9 to 7.2 DU, which are typically smaller than the model-sonde RMS differences. Four different definitions of the tropopause using temperature lapse rate, potential vorticity (PV) and isentropic surfaces or ozone isosurfaces are compared with respect to their global impact on the estimated tropospheric ozone column. The largest sensitivity in the tropospheric ozone column is found near the subtropical jet, where the ozone or PV determined tropopause typically lies below the lapse rate tropopause.

  13. Detecting climate rationality and homogeneities of sea surface temperature data in Longkou marine station using surface air temperature

    Science.gov (United States)

    Li, Yan; Li, Huan; Wang, Qingyuan; Wang, Guosong; Fan, Wenjing

    2017-08-01

    This study presents a systematic evaluation of the climate rationality and homogeneity of monthly sea surface temperature (SST) in Longkou marine station from 1960 to 2011. The reference series are developed using adjacent surface air temperature (SAT) on a monthly timescale. The results suggest SAT as a viable option for use in evaluating climate rationality and homogeneity in the SST data on the coastal China Seas. According to the large-scale atmospheric circulation patterns and SAT of the adjacent meteorological stations, we confirm that there is no climate shift in 1972/1973 and then the climate shift in 1972/1973 is corrected. Besides, the SST time series has serious problems of inhomogeneity. Three documented break points have been checked using penalized maximum T (PMT) test and metadata. The changes in observation instruments and observation system are the main causes of the break points. For the monthly SST time series, the negative adjustments may be greatly due to the SST decreasing after automation. It is found that the increasing trend of annual mean SST after adjustment is higher than before, about 0.24 °C/10 yr.

  14. An eddy resolving tidal-driven model of the South China Sea assimilating along-track SLA data using the EnOI

    Directory of Open Access Journals (Sweden)

    J. Xie

    2011-10-01

    Full Text Available The upper ocean circulation in the South China Sea (SCS is driven by the Asian monsoon, the Kuroshio intrusion through the Luzon Strait, strong tidal currents, and a complex topography. Here, we demonstrate the benefit of assimilating along-track altimeter data into a nested configuration of the HYbrid Coordinate Ocean Model that includes tides. Including tides in models is important because they interact with the main circulation. However, assimilation of altimetry data into a model including tides is challenging because tides and mesoscale features contribute to the elevation of ocean surface at different time scales and require different corrections. To address this issue, tides are filtered out of the model output and only the mesoscale variability is corrected with a computationally cheap data assimilation method: the Ensemble Optimal Interpolation (EnOI. This method uses a running selection of members to handle the seasonal variability and assimilates the track data asynchronously. The data assimilative system is tested for the period 1994–1995, during which time a large number of validation data are available. Data assimilation reduces the Root Mean Square Error of Sea Level Anomalies from 9.3 to 6.9 cm and improves the representation of the mesoscale features. With respect to the vertical temperature profiles, the data assimilation scheme reduces the errors quantitatively with an improvement at intermediate depth and deterioration at deeper depth. The comparison to surface drifters shows an improvement of surface current by approximately −9% in the Northern SCS and east of Vietnam. Results are improved compared to an assimilative system that does not include tides and a system that does not consider asynchronous assimilation.

  15. GHRSST Level 4 ODYSSEA Mediterranean Sea Regional Foundation Sea Surface Temperature Analysis (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at Ifremer/CERSAT...

  16. Comparison of MTI and Ground Truth Sea Surface Temperatures at Nauru

    Energy Technology Data Exchange (ETDEWEB)

    Kurzeja, R.

    2002-09-05

    This report evaluates MTI-derived surface water temperature near the tropical Pacific island of Nauru. The MTI sea-surface temperatures were determined by the Los Alamos National Laboratory based on the robust retrieval.

  17. GHRSST Level 4 GAMSSA Global Foundation Sea Surface Temperature Analysis (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the Australian Bureau...

  18. GHRSST Level 4 RAMSSA Australian Regional Foundation Sea Surface Temperature Analysis (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the Australian Bureau...

  19. GHRSST Level 4 EUR Mediterranean Sea Regional Foundation Sea Surface Temperature Analysis (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily by Ifremer/CERSAT (France) using optimal...

  20. GHRSST Level 4 ODYSSEA Global Foundation Sea Surface Temperature Analysis (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at Ifremer/CERSAT...

  1. GHRSST Level 4 ODYSSEA Eastern Central Pacific Regional Foundation Sea Surface Temperature Analysis (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at Ifremer/CERSAT...

  2. GHRSST Level 4 G1SST Global Foundation Sea Surface Temperature Analysis (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis by the JPL OurOcean...

  3. GHRSST Level 4 DMI_OI Global Foundation Sea Surface Temperature Analysis (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis by the Danish...

  4. GHRSST Level 4 OSTIA Global Foundation Sea Surface Temperature Analysis (GDS versions 1 and 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the UK Met Office...

  5. GHRSST Level 4 MW_OI Global Foundation Sea Surface Temperature analysis (GDS version 2)

    Data.gov (United States)

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

  6. GHRSST Level 4 MUR North America Regional Foundation Sea Surface Temperature Analysis (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced as a retrospective dataset at the JPL Physical...

  7. Assessment of surface temperatures of buffalo bulls (Bubalus bubalis) raised under tropical conditions using infrared thermography

    National Research Council Canada - National Science Library

    Barros, D.V; Silva, L.K.X; Kahwage, P.R; Lourenço Júnior, J.B; Sousa, J.S; Silva, A.G.M; Franco, I.M; Martorano, L.G; Garcia, A.R

    2016-01-01

    This paper aimed to evaluate the surface temperatures of buffalo bulls using infrared thermography, considering four distinct anatomical parts over time, and to correlate surface temperatures and thermal comfort indexes...

  8. GHRSST Level 4 OSPO Global Nighttime Foundation Sea Surface Temperature Analysis (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the Office of...

  9. GHRSST Level 4 OSPO Global Foundation Sea Surface Temperature Analysis (GDS version 2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the Office of...

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

    Data.gov (United States)

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

  11. GHRSST Level 4 K10_SST Global 1 meter Sea Surface Temperature Analysis (GDS version 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced daily on an operational basis at the Naval...

  12. Data Assimilation using Artificial Neural Networks for the global FSU atmospheric model

    Science.gov (United States)

    Cintra, Rosangela; Cocke, Steven; Campos Velho, Haroldo

    2015-04-01

    Data assimilation is the process by which measurements and model predictions are combined to obtain an accurate representation of the state of the modeled system. Uncertainty is the characteristic of the atmosphere, coupled with inevitable inadequacies in observations and computer models and increase errors in weather forecasts. Data assimilation is a technique to generate an initial condition to a weather or climate forecasts. This paper shows the results of a data assimilation technique using artificial neural networks (ANN) to obtain the initial condition to the atmospheric general circulation model (AGCM) for the Florida State University in USA. The Local Ensemble Transform Kalman filter (LETKF) is implemented with Florida State University Global Spectral Model (FSUGSM). The ANN data assimilation is made to emulate the initial condition from LETKF to run the FSUGSM. LETKF is a version of Kalman filter with Monte-Carlo ensembles of short-term forecasts to solve the data assimilation problem. The model FSUGSM is a multilevel (27 vertical levels) spectral primitive equation model with a vertical sigma coordinate. All variables are expanded horizontally in a truncated series of spherical harmonic functions (at resolution T63) and a transform technique is applied to calculate the physical processes in real space. The LETKF data assimilation experiments are based in synthetic observations data (surface pressure, absolute temperature, zonal component wind, meridional component wind and humidity). For the ANN data assimilation scheme, we use Multilayer Perceptron (MLP-DA) with supervised training algorithm where ANN receives input vectors with their corresponding response or target output from LETKF scheme. An automatic tool that finds the optimal representation to these ANNs configures the MLP-DA in this experiment. After the training process, the scheme MLP-DA is seen as a function of data assimilation where the inputs are observations and a short-range forecast to

  13. An Open and Transparent Databank of Global Land Surface Temperature

    Science.gov (United States)

    Rennie, J.; Thorne, P.; Lawrimore, J. H.; Gleason, B.; Menne, M. J.; Williams, C.

    2013-12-01

    The International Surface Temperature Initiative (ISTI) consists of an effort to create an end-to-end process for land surface air temperature analyses. The foundation of this process is the establishment of a global land surface databank. The databank builds upon the groundbreaking efforts of scientists who led efforts to construct global land surface datasets in the 1980's and 1990's. A primary aim of the databank is to improve aspects including data provenance, version control, temporal and spatial coverage, and improved methods for bringing dozens of source data together into an integrated dataset. The databank consists of multiple stages, with each successive stage providing a higher level of processing, quality and integration. Currently more than 50 sources of data have been added to the databank. An automated algorithm has been developed that merges these sources into one complete dataset by removing duplicate station records, identifying two or more station records that can be merged into a single record, and incorporating new and unique stations. The program runs iteratively through all the sources which are ordered based upon criteria established by the ISTI. The highest preferred source, known as the target, runs through all the candidate sources, calculating station comparisons that are acceptable for merging. The process is probabilistic in approach, and the final fate of a candidate station is based upon metadata matching and data equivalence criteria. If there is not enough information, the station is withheld for further investigation. The algorithm has been validated using a pseudo-source of stations with a known time of observation bias, and correct matches have been made nearly 95% of the time. The final product, endorsed and recommended by ISTI, contains over 30,000 stations, however slight changes in the algorithm can perturb results. Subjective decisions, such as the ordering of the sources, or changing metadata and data matching thresholds

  14. Estimation of Land Surface Temperature under Cloudy Skies Using Combined Diurnal Solar Radiation and Surface Temperature Evolution

    Directory of Open Access Journals (Sweden)

    Xiaoyu Zhang

    2015-01-01

    Full Text Available Land surface temperature (LST is a key parameter in the interaction of the land-atmosphere system. However, clouds affect the retrieval of LST data from thermal-infrared remote sensing data. Thus, it is important to determine a method for estimating LSTs at times when the sky is overcast. Based on a one-dimensional heat transfer equation and on the evolution of daily temperatures and net shortwave solar radiation (NSSR, a new method for estimating LSTs under cloudy skies (Tcloud from diurnal NSSR and surface temperatures is proposed. Validation is performed against in situ measurements that were obtained at the ChangWu ecosystem experimental station in China. The results show that the root-mean-square error (RMSE between the actual and estimated LSTs is as large as 1.23 K for cloudy data. A sensitivity analysis to the errors in the estimated LST under clear skies (Tclear and in the estimated NSSR reveals that the RMSE of the obtained Tcloud is less than 1.5 K after adding a 0.5 K bias to the actual Tclear and 10 percent NSSR errors to the actual NSSR. Tcloud is estimated by the proposed method using Tclear and NSSR products of MSG-SEVIRI for southern Europe. The results indicate that the new algorithm is practical for retrieving the LST under cloudy sky conditions, although some uncertainty exists. Notably, the approach can only be used during the daytime due to the assumption of the variation in LST caused by variations in insolation. Further, if there are less than six Tclear observations on any given day, the method cannot be used.

  15. Problems of variational assimilation of observational data for ocean general circulation models and methods for their solution

    Science.gov (United States)

    Agoshkov, V. I.; Ipatova, V. M.; Zalesnyi, V. B.; Parmuzin, E. I.; Shutyaev, V. P.

    2010-12-01

    Problems of the variational assimilation of satellite observational data on the temperature and level of the ocean surface, as well as data on the temperature and salinity of the ocean from the ARGO system of buoys, are formulated with the use of the global three-dimensional model of ocean thermodynamics developed at the Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS). Algorithms for numerical solutions of the problems are developed and substantiated, and data assimilation blocks are developed and incorporated into the global three-dimensional model. Numerical experiments are performed with the use of the Indian Ocean or the entire World Ocean as examples. These numerical experiments support the theoretical conclusions and demonstrate that the use of a model with an assimilation block of operational observational data is expedient.

  16. How essential are Argo observations to constrain a global ocean data assimilation system?

    Science.gov (United States)

    Turpin, V.; Remy, E.; Le Traon, P. Y.

    2016-02-01

    Observing system experiments (OSEs) are carried out over a 1-year period to quantify the impact of Argo observations on the Mercator Ocean 0.25° global ocean analysis and forecasting system. The reference simulation assimilates sea surface temperature (SST), SSALTO/DUACS (Segment Sol multi-missions dALTimetrie, d'orbitographie et de localisation précise/Data unification and Altimeter combination system) altimeter data and Argo and other in situ observations from the Coriolis data center. Two other simulations are carried out where all Argo and half of the Argo data are withheld. Assimilating Argo observations has a significant impact on analyzed and forecast temperature and salinity fields at different depths. Without Argo data assimilation, large errors occur in analyzed fields as estimated from the differences when compared with in situ observations. For example, in the 0-300 m layer RMS (root mean square) differences between analyzed fields and observations reach 0.25 psu and 1.25 °C in the western boundary currents and 0.1 psu and 0.75 °C in the open ocean. The impact of the Argo data in reducing observation-model forecast differences is also significant from the surface down to a depth of 2000 m. Differences between in situ observations and forecast fields are thus reduced by 20 % in the upper layers and by up to 40 % at a depth of 2000 m when Argo data are assimilated. At depth, the most impacted regions in the global ocean are the Mediterranean outflow, the Gulf Stream region and the Labrador Sea. A significant degradation can be observed when only half of the data are assimilated. Therefore, Argo observations matter to constrain the model solution, even for an eddy-permitting model configuration. The impact of the Argo floats' data assimilation on other model variables is briefly assessed: the improvement of the fit to Argo profiles do not lead globally to unphysical corrections on the sea surface temperature and sea surface height. The main conclusion

  17. Impacts of wind farms on surface air temperatures

    Science.gov (United States)

    Baidya Roy, Somnath; Traiteur, Justin J.

    2010-01-01

    Utility-scale large wind farms are rapidly growing in size and numbers all over the world. Data from a meteorological field campaign show that such wind farms can significantly affect near-surface air temperatures. These effects result from enhanced vertical mixing due to turbulence generated by wind turbine rotors. The impacts of wind farms on local weather can be minimized by changing rotor design or by siting wind farms in regions with high natural turbulence. Using a 25-y-long climate dataset, we identified such regions in the world. Many of these regions, such as the Midwest and Great Plains in the United States, are also rich in wind resources, making them ideal candidates for low-impact wind farms. PMID:20921371

  18. Change point detection of the Persian Gulf sea surface temperature

    Science.gov (United States)

    Shirvani, A.

    2017-01-01

    In this study, the Student's t parametric and Mann-Whitney nonparametric change point models (CPMs) were applied to detect change point in the annual Persian Gulf sea surface temperature anomalies (PGSSTA) time series for the period 1951-2013. The PGSSTA time series, which were serially correlated, were transformed to produce an uncorrelated pre-whitened time series. The pre-whitened PGSSTA time series were utilized as the input file of change point models. Both the applied parametric and nonparametric CPMs estimated the change point in the PGSSTA in 1992. The PGSSTA follow the normal distribution up to 1992 and thereafter, but with a different mean value after year 1992. The estimated slope of linear trend in PGSSTA time series for the period 1951-1992 was negative; however, that was positive after the detected change point. Unlike the PGSSTA, the applied CPMs suggested no change point in the Niño3.4SSTA time series.

  19. Investigation of Sea Surface Temperature (SST) anomalies over Cyprus area

    Science.gov (United States)

    Georgiou, Andreas; Akçit, Nuhcan

    2016-08-01

    The temperature of the sea surface has been identified as an important parameter of the natural environment, governing processes that occur in the upper ocean. This paper focuses on the analysis of the Sea Surface Temperature (SST) anomalies at the greater area of Cyprus. For that, SST data derived from MODerate-resolution Imaging Spectroradiometer (MODIS) instrument on board both Aqua and Terra sun synchronous satellites were used. A four year period was chosen as a first approach to address and describe this phenomenon. Geographical Information Systems (GIS) has been used as an integrated platform of analysis and presentation in addition of the support of MATLAB®. The methodology consists of five steps: (i) Collection of MODIS SST imagery, (ii) Development of the digital geo-database; (iii) Model and run the methodology in GIS as a script; (iv) Calculation of SST anomalies; and (v) Visualization of the results. The SST anomaly values have presented a symmetric distribution over the study area with an increase trend through the years of analysis. The calculated monthly and annual average SST anomalies (ASST) make more obvious this trend, with negative and positive SST changes to be distributed over the study area. In terms of seasons, the same increase trend presented during spring, summer, autumn and winter with 2013 to be the year with maximum ASST observed values. Innovative aspects comprise of straightforward integration and modeling of available tools, providing a versatile platform of analysis and semi-automation of the operation. In addition, the fine resolution maps that extracted from the analysis with a wide spatial coverage, allows the detail representation of SST and ASST respectively in the region.

  20. A study of the coupling relationship between concrete surface temperature and concrete surface emissivity in natural conditions.

    Science.gov (United States)

    Tang, Lin-Ling; Chen, Xiao-Ling; Wang, Jia-Ning; Zhao, Hong-Mei; Huang, Qi-Ting

    2014-07-01

    Land surface emissivity (LSE) has already been recognized as a crucial parameter for the determination of land surface temperature (LST). There is an ill-posed problem for the retrieval of LST and LSE. And laboratory-based emissivity is measured in natural constant conditions, which is limited in the application in thermal remote sensing. To solve the above problems, the coupling of LST and LSE is explored to eliminate temperature effects and improve the accuracy of LES. And then, the estimation accuracy of LST from passive remote sensing images will be improved. For different land surface materials, the coupling of land surface emissivity and land surface temperature is various. This paper focuses on studying concrete surface that is one of the typical man-made materials in urban. First the experiments of measuring concrete surface emissivity and concrete surface temperature in natural conditions are arranged reasonably and the suitable data are selected under ideal atmosphere conductions. Then to improve the determination accuracy of concrete surface emissivity, the algorithm worked on the computer of Fourier Transform Infrared Spectroradiometer (FTIR) has been improved by the most adapted temperature and emissivity separation algorithm. Finally the coupling of concrete surface temperature and concrete surface emissivity is analyzed and the coupling model of concrete surface temperature and concrete surface emissivity is established. The results show that there is a highest correlation coefficient between the second derivative of emissivity spectra and concrete surface temperature, and the correlation coefficient is -0.925 1. The best coupling model is the stepwise regression model, whose determination coefficient (R2) is 0.886. The determination coefficient (R2) is 0.905 and the root mean squares error (RMSE) is 0.292 1 in the validation of the model. The coupling model of concrete surface temperature and concrete surface emissivity under natural conditions

  1. An Ensemble Algorithm Based Component for Geomagnetic Data Assimilation

    Directory of Open Access Journals (Sweden)

    Zhibin Sun and Weijia Kuang

    2015-01-01

    Full Text Available Geomagnetic data assimilation is one of the most recent developments in geomagnetic studies. It combines geodynamo model outputs and surface geomagnetic observations to provide more accurate estimates of the core dynamic state and provide accurate geomagnetic secular variation forecasting. To facilitate geomagnetic data assimilation studies, we develop a stand-alone data assimilation component for the geomagnetic community. This component is used to calculate the forecast error covariance matrices and the gain matrix from a given geodynamo solution, which can then be used for sequential geomagnetic data assimilation. This component is very flexible and can be executed independently. It can also be easily integrated with arbitrary dynamo models.

  2. Ocular Surface Temperature in Age-Related Macular Degeneration

    Directory of Open Access Journals (Sweden)

    Andrea Sodi

    2014-01-01

    Full Text Available Background. The aim of this study is to investigate the ocular thermographic profiles in age-related macular degeneration (AMD eyes and age-matched controls to detect possible hemodynamic abnormalities, which could be involved in the pathogenesis of the disease. Methods. 32 eyes with early AMD, 37 eyes with atrophic AMD, 30 eyes affected by untreated neovascular AMD, and 43 eyes with fibrotic AMD were included. The control group consisted of 44 healthy eyes. Exclusion criteria were represented by any other ocular diseases other than AMD, tear film abnormalities, systemic cardiovascular abnormalities, diabetes mellitus, and a body temperature higher than 37.5°C. A total of 186 eyes without pupil dilation were investigated by infrared thermography (FLIR A320. The ocular surface temperature (OST of three ocular points was calculated by means of an image processing technique from the infrared images. Two-sample t-test and one-way analysis of variance (ANOVA test were used for statistical analyses. Results. ANOVA analyses showed no significant differences among AMD groups (P value >0.272. OST in AMD patients was significantly lower than in controls (P>0.05. Conclusions. Considering the possible relationship between ocular blood flow and OST, these findings might support the central role of ischemia in the pathogenesis of AMD.

  3. Collaborative Research: Atlantic Ocean Tropical/Subtropical Processes from Seasonal to Decadal Time Scales: Model/Data, Model/Model Comparison and Model/Data Synthesis Through Assimilation

    Science.gov (United States)

    Malannotte-Rizzoli, Paola

    2003-01-01

    The effort of this first year of research has been focused on the assimilation of TOPEX/Poseidon altimetric data into a primitive equation model of the Atlantic tropical/subtropical circulation. A reduced-rank, stationary Kalman filter has been constructed to assimilate the altimetric sea surface height anomaly (SHA) into the model. The goal is to assess how the inter-hemispheric transports between the Atlantic subtropics and tropics are affected by the assimilation and how the subsurface thermocline structure , and its variability ,is dynamically constrained by the SHA. The model is a reduced-gravity primitive equation GCM of the upper Atlantic Ocean between 30 S and 30 N. The assimilation scheme is an approximation to the extended Kalman filter in which the error covariances of the state estimates are calculated only in a reduced- dimension subspace. The subspace is defined by the leading empirical orthogonal functions calculated from an unconstrained model calculation. Both an identical twin experiment using simulated SHA observations and assimilation of the real TOPEX data were performed. Results from the twin experiments demonstrate the ability of the method to constrain the ocean circulation and the subsurface temperature structure. The impact on the subsurface temperature structure of TOPEX assimilation was assessed using data from expandable bathythermographs. This showed a substantial improvement in the estimated temperature variability only within 13 degrees in latitude around the equator. The impact of TOPEX SHA assimilation on zonally integrated meridional transport across different latitudes was also estimated. Again within 13 degrees from the equator both the mean amplitude and interannual variability of the surface and subsurface transports were significantly enhanced, while the transports were insensitive to the assimilation in the subtropics.

  4. Decadal modulation of global surface temperature by internal climate variability

    Science.gov (United States)

    Dai, Aiguo; Fyfe, John C.; Xie, Shang-Ping; Dai, Xingang

    2015-06-01

    Despite a steady increase in atmospheric greenhouse gases (GHGs), global-mean surface temperature (T) has shown no discernible warming since about 2000, in sharp contrast to model simulations, which on average project strong warming. The recent slowdown in observed surface warming has been attributed to decadal cooling in the tropical Pacific, intensifying trade winds, changes in El Niño activity, increasing volcanic activity and decreasing solar irradiance. Earlier periods of arrested warming have been observed but received much less attention than the recent period, and their causes are poorly understood. Here we analyse observed and model-simulated global T fields to quantify the contributions of internal climate variability (ICV) to decadal changes in global-mean T since 1920. We show that the Interdecadal Pacific Oscillation (IPO) has been associated with large T anomalies over both ocean and land. Combined with another leading mode of ICV, the IPO explains most of the difference between observed and model-simulated rates of decadal change in global-mean T since 1920, and particularly over the so-called `hiatus' period since about 2000. We conclude that ICV, mainly through the IPO, was largely responsible for the recent slowdown, as well as for earlier slowdowns and accelerations in global-mean T since 1920, with preferred spatial patterns different from those associated with GHG-induced warming or aerosol-induced cooling. Recent history suggests that the IPO could reverse course and lead to accelerated global warming in the coming decades.

  5. Air Temperature estimation from Land Surface temperature and solar Radiation parameters

    Science.gov (United States)

    Lazzarini, Michele; Eissa, Yehia; Marpu, Prashanth; Ghedira, Hosni

    2013-04-01

    Air Temperature (AirT) is a fundamental parameter in a wide range of applications such as climate change studies, weather forecast, energy balance modeling, efficiency of Photovoltaic (PV) solar cells, etc. Air temperature data are generally obtained through regular measurements from meteorological stations. The distribution of these stations is normally sparse, so the spatial pattern of this parameter cannot be accurately estimated by interpolation methods. This work investigated the relationship between Air Temperature measured at meteorological stations and spatially contiguous measurements derived from Remote Sensing techniques, such as Land Surface Temperature (LST) maps, emissivity maps and shortwave radiation maps with the aim of creating a continuous map of AirT. For LST and emissivity, MSG-SEVIRI LST product from Land Surface Analysis Satellite Applications Facility (LSA-SAF) has been used. For shortwave radiation maps, an Artificial Neural Networks ensemble model has been developed and previously tested to create continuous maps from Global Horizontal Irradiance (GHI) point measurements, utilizing six thermal channels of MSG-SEVIRI. The testing sites corresponded to three meteorological stations located in the United Arab Emirates (UAE), where in situ measurements of Air Temperature were available. From the starting parameters, energy fluxes and net radiation have been calculated, in order to have information on the incoming and outgoing long-wave radiation and the incoming short-wave radiation. The preliminary analysis (day and Night measurements, cloud free) showed a strong negative correlation (0.92) between Outgoing long-wave radiation - GHI and LST- AirT, with a RMSE of 1.84 K in the AirT estimation from the initial parameters. Regression coefficients have been determined and tested on all the ground stations. The analysis also demonstrated the predominant impact of the incoming short-wave radiation in the AirT hourly variation, while the incoming

  6. Seasonal variations of air-sea heat fluxes and sea surface temperature in the northwestern Pacific marginal seas

    Institute of Scientific and Technical Information of China (English)

    LIU Na; WU Dexing; LIN Xiaopei; MENG Qingjia

    2014-01-01

    Using a net surface heat flux (Qnet) product obtained from the objectively analyzed air-sea fluxes (OAFlux) project and the international satellite cloud climatology project (ISCCP), and temperature from the simple ocean data assimilation (SODA), the seasonal variations of the air-sea heat fluxes in the northwestern Pa-cific marginal seas (NPMS) and their roles in sea surface temperature (SST) seasonality are studied. The seasonal variations of Qnet, which is generally determined by the seasonal cycle of latent heat flux (LH), are in response to the advection-induced changes of SST over the Kuroshio and its extension. Two dynamic regimes are identified in the NPMS:one is the area along the Kuroshio and its extension, and the other is the area outside the Kuroshio. The oceanic thermal advection dominates the variations of SST and hence the sea-air humidity plays a primary role and explains the maximum heat losing along the Kuroshio. The heat transported by the Kuroshio leads to a longer period of heat losing over the Kuroshio and its Extension. Positive anomaly of heat content corresponds with the maximum heat loss along the Kuroshio. The oceanic advection controls the variations of heat content and hence the surface heat flux. This study will help us understand the mechanism controlling variations of the coupled ocean-atmosphere system in the NPMS. In the Kuroshio region, the ocean current controls the ocean temperature along the main stream of the Ku-roshio, and at the same time, forces the air-sea fluxes.

  7. Inter-annual variability of sea surface temperature, wind speed and sea surface height anomaly over the tropical Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

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

    have made an attempt to study the annual and inter-annual variability of certain prominent processes occurring over the tropical Indian Ocean. The monthly mean values of Wind Speed (FSU), Sea Surface Temperature (REYNOLDS) and Sea Surface Height Anomaly...

  8. Computer Modeling of Planetary Surface Temperatures in Introductory Astronomy Courses

    Science.gov (United States)

    Barker, Timothy; Goodman, J.

    2013-01-01

    Barker, T., and Goodman, J. C., Wheaton College, Norton, MA Computer modeling is an essential part of astronomical research, and so it is important that students be exposed to its powers and limitations in the first (and, perhaps, only) astronomy course they take in college. Building on the ideas of Walter Robinson (“Modeling Dynamic Systems,” Springer, 2002) we have found that STELLA software (ISEE Systems) allows introductory astronomy students to do sophisticated modeling by the end of two classes of instruction, with no previous experience in computer programming or calculus. STELLA’s graphical interface allows students to visualize systems in terms of “flows” in and out of “stocks,” avoiding the need to invoke differential equations. Linking flows and stocks allows feedback systems to be constructed. Students begin by building an easily understood system: a leaky bucket. This is a simple negative feedback system in which the volume in the bucket (a “stock”) depends on a fixed inflow rate and an outflow that increases in proportion to the volume in the bucket. Students explore how changing inflow rate and feedback parameters affect the steady-state volume and equilibration time of the system. This model is completed within a 50-minute class meeting. In the next class, students are given an analogous but more sophisticated problem: modeling a planetary surface temperature (“stock”) that depends on the “flow” of energy from the Sun, the planetary albedo, the outgoing flow of infrared radiation from the planet’s surface, and the infrared return from the atmosphere. Students then compare their STELLA model equilibrium temperatures to observed planetary temperatures, which agree with model ones for worlds without atmospheres, but give underestimates for planets with atmospheres, thus introducing students to the concept of greenhouse warming. We find that if we give the students part of this model at the start of a 50-minute class they are

  9. Augmenting an operational forecasting system for the North and Baltic Seas by in situ T and S data assimilation

    Science.gov (United States)

    Losa, Svetlana; Danilov, Sergey; Schröter, Jens; Nerger, Lars; Maßmann, Silvia; Janssen, Frank

    2014-05-01

    In order to improve the hydrography forecast of the North and Baltic Seas, the operational circulation model of the German Federal Maritime and Hydrographic Agency (BSH) has been augmented by a data assimilation (DA) system. The DA system has been developed based on the Singular Evolution Interpolated Kalman (SEIK) filter algorithm (Pham, 1998) coded within the Parallel Data Assimilation Framework (Nerger et al., 2004, Nerger and Hiller, 2012). Previously the only data assimilated were sea surface temperature (SST) measurements obtained with the Advanced Very High Resolution Radiometer (AVHRR) aboard NOAA's polar orbiting satellites. While the quality of the forecast has been significantly improved by assimilating the satellite data (Losa et al., 2012, Losa et al., 2014), assimilation of in situ observational temperature (T) and salinity (S) profiles has allowed for further improvement. Assimilating MARNET time series and CTD and Scanfish measurements, however, required a careful calibration of the DA system with respect to local analysis. The study addresses the problem of the local SEIK analysis accounting for the data within a certain radius. The localisation radius is considered spatially variable and dependent on the system local dynamics. As such, we define the radius of the data influence based on the energy ratio of the baroclinic and barotropic flows. D. T. Pham, J. Verron, L. Gourdeau, 1998. Singular evolutive Kalman filters for data assimilation in oceanography, C. R. Acad. Sci. Paris, Earth and Planetary Sciences, 326, 255-260. L. Nerger, W. Hiller, J. Schröter, 2004. PDAF - The Parallel Data Assimilation Framework: Experiences with Kalman Filtering, In: Zwieflhofer, W., Mozdzynski, G. (Eds.), Use of high performance computing in meteorology: proceedings of the Eleventh ECMWF Workshop on the Use of High Performance Computing in Meteorology. Singapore: World Scientific, Reading, UK, 63-83. L. Nerger, W. Hiller, 2012. Software for Ensemble-based Data

  10. NOAA Climate Data Record (CDR) of Sea Surface Temperature -WHOI, Version 1.0

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The NOAA Ocean Surface Bundle (OSB) Climate Data Record (CDR) consist of three parts: sea surface temperature, near-surface atmospheric properties, and heat fluxes....

  11. Surface temperature evolution and the location of maximum and average surface temperature of a lithium-ion pouch cell under variable load profiles

    DEFF Research Database (Denmark)

    Goutam, Shovon; Timmermans, Jean-Marc; Omar, Noshin;

    2014-01-01

    , manganese and cobalt (NMC) based and the anode is graphite based. In order to measure the surface temperature, thermal infrared (IR) camera and contact thermocouples were used. A fairly uniform temperature distribution was observed over the cell surface in case of continuous charge and discharge up to 100A...

  12. Using distributed temperature sensing to monitor field scale dynamics of ground surface temperature and related substrate heat flux

    NARCIS (Netherlands)

    Bense, V.F.; Read, T.; Verhoef, A.

    2016-01-01

    We present one of the first studies of the use of distributed temperature sensing (DTS) along fibre-optic cables to purposely monitor spatial and temporal variations in ground surface temperature (GST) and soil temperature, and provide an estimate of the heat flux at the base of the canopy layer

  13. The impact of built-up surfaces on land surface temperatures in Italian urban areas.

    Science.gov (United States)

    Morabito, Marco; Crisci, Alfonso; Messeri, Alessandro; Orlandini, Simone; Raschi, Antonio; Maracchi, Giampiero; Munafò, Michele

    2016-05-01

    Urban areas are characterized by the very high degree of soil sealing and continuous built-up areas: Italy is one of the European countries with the highest artificial land cover rate, which causes a substantial spatial variation in the land surface temperature (LST), modifying the urban microclimate and contributing to the urban heat island effect. Nevertheless, quantitative data regarding the contribution of different densities of built-up surfaces in determining urban spatial LST changes is currently lacking in Italy. This study, which aimed to provide clear and quantitative city-specific information on annual and seasonal spatial LST modifications resulting from increased urban built-up coverage, was conducted generally throughout the whole year, and specifically in two different periods (cool/cold and warm/hot periods). Four cities (Milan, Rome, Bologna and Florence) were included in the study. The LST layer and the built-up-surface indicator were obtained via use of MODIS remote sensing data products (1km) and a very high-resolution map (5m) of built-up surfaces recently developed by the Italian National Institute for Environmental Protection and Research. The relationships between the dependent (mean daily, daytime and nighttime LST values) and independent (built-up surfaces) variables were investigated through linear regression analyses, and comprehensive built-up-surface-related LST maps were also developed. Statistically significant linear relationships (pcities studied, with a higher impact during the warm/hot period than in the cool/cold ones. Daytime and nighttime LST slope patterns depend on the city size and relative urban morphology. If implemented in the existing city plan, the urban maps of built-up-surface-related LST developed in this study might be able to support more sustainable urban land management practices by identifying the critical areas (Hot-Spots) that would benefit most from mitigation actions by local authorities, land-use decision

  14. Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China

    Institute of Scientific and Technical Information of China (English)

    XIAO Rong-bo; OUYANG Zhi-yun; ZHENG Hua; LI Wei-feng; SCHIENKE Erich W; WANG Xiao-ke

    2007-01-01

    Land surface temperature (LST), which is heavily influenced by urban surface structures, is a significant parameter in urban environmental analysis. This study examined the effect impervious surfaces (IS) spatial patterns have on LST in Beijing, China. A classification and regression tree model (CART) was adopted to estimate IS as a continuous variable using Landsat images from two seasons combined with QuickBird. LST was retrieved from the Landsat Thematic Mapper (TM) image to examine the relationships between IS and LST. The results revealed that CART was capable of consistently predicting LST with acceptable accuracy (correlation coefficient of 0.94 and the average error of 8.59%). Spatial patterns of IS exhibited changing gradients across the various urban-rural transects, with LST values showing a concentric shape that increased as you moved from the outskirts towards the downtown areas.Transect analysis also indicated that the changes in both IS and LST patterns were similar at various resolution levels, which suggests a distinct linear relationship between them. Results of correlation analysis further showed that IS tended to be positively correlated with LST, and that the correlation coefficients increased from 0.807 to 0.925 with increases in IS pixel size. The findings identified in this study provide a theoretical basis for improving urban planning efforts to lessen urban temperatures and thus dampen urban heat island effects.

  15. The EUSTACE project: delivering global, daily information on surface air temperature

    Science.gov (United States)

    Rayner, Nick

    2017-04-01

    Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-June 2018, https://www.eustaceproject.eu) we are developing an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods. We will present recent progress along this road in the EUSTACE project: 1. providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; 2. identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; 3. estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; 4. using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

  16. The EUSTACE project: delivering global, daily information on surface air temperature

    Science.gov (United States)

    Morice, C. P.; Rayner, N. A.; Auchmann, R.; Bessembinder, J.; Bronnimann, S.; Brugnara, Y.; Conway, E. A.; Ghent, D.; Good, E.; Herring, K.; Kennedy, J.; Lindgren, F.; Madsen, K. S.; Merchant, C. J.; van der Schrier, G.; Stephens, A.; Tonboe, R. T.; Waterfall, A. M.; Mitchelson, J.; Woolway, I.

    2015-12-01

    Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. These relationships can be derived either empirically or with the help of a physical model.Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals would be used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods.We will present plans and progress along this road in the EUSTACE project (2015-June 2018), i.e.: • providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras.Information will also be given on how interested users can become

  17. Weighted ensemble transform Kalman filter for image assimilation

    Directory of Open Access Journals (Sweden)

    Sebastien Beyou

    2013-01-01

    Full Text Available This study proposes an extension of the Weighted Ensemble Kalman filter (WEnKF proposed by Papadakis et al. (2010 for the assimilation of image observations. The main focus of this study is on a novel formulation of the Weighted filter with the Ensemble Transform Kalman filter (WETKF, incorporating directly as a measurement model a non-linear image reconstruction criterion. This technique has been compared to the original WEnKF on numerical and real world data of 2-D turbulence observed through the transport of a passive scalar. In particular, it has been applied for the reconstruction of oceanic surface current vorticity fields from sea surface temperature (SST satellite data. This latter technique enables a consistent recovery along time of oceanic surface currents and vorticity maps in presence of large missing data areas and strong noise.

  18. Evaluating Data Assimilation Algorithms

    CERN Document Server

    Law, K J H

    2011-01-01

    Data assimilation refers to methodologies for the incorporation of noisy observations of a physical system into an underlying model in order to infer the properties of the state of the system (and/or parameters). The model itself is typically subject to uncertainties, in the input data and in the physical laws themselves. This leads naturally to a Bayesian formulation in which the posterior probability distribution of the system state, given the observations, plays a central conceptual role. The aim of this paper is to use this Bayesian posterior probability distribution as a gold standard against which to evaluate various commonly used data assimilation algorithms. A key aspect of geophysical data assimilation is the high dimensionality of the computational model. With this in mind, yet with the goal of allowing an explicit and accurate computation of the posterior distribution in order to facilitate our evaluation, we study the 2D Navier-Stokes equations in a periodic geometry. We compute the posterior prob...

  19. Long-term surface temperature modeling of Pluto

    Science.gov (United States)

    Earle, Alissa M.; Binzel, Richard P.; Young, Leslie A.; Stern, S. A.; Ennico, K.; Grundy, W.; Olkin, C. B.; Weaver, H. A.

    2017-05-01

    NASA's New Horizons' reconnaissance of the Pluto system has revealed at high resolution the striking albedo contrasts from polar to equatorial latitudes on Pluto, as well as the sharpness of boundaries for longitudinal variations. These contrasts suggest that Pluto must undergo dynamic evolution that drives the redistribution of volatiles. Using the New Horizons results as a template, we explore the surface temperature variations driven seasonally on Pluto considering multiple timescales. These timescales include the current orbit (248 years) as well as the timescales for obliquity precession (peak-to-peak amplitude of 23° over 3 million years) and regression of the orbital longitude of perihelion (3.7 million years). These orbital variations create epochs of ;Extreme Seasons; where one pole receives a short, relatively warm summer and long winter, while the other receives a much longer, but less intense summer and short winter. We use thermal modeling to build upon the long-term insolation history model described by Earle and Binzel (2015) and investigate how these seasons couple with Pluto's albedo contrasts to create temperature effects. From this study we find that a bright region at the equator, once established, can become a site for net deposition. We see the region informally known as Sputnik Planitia as an example of this, and find it will be able to perpetuate itself as an ;always available; cold trap, thus having the potential to survive on million year or substantially longer timescales. Meanwhile darker, low-albedo, regions near the equator will remain relative warm and generally not attract volatile deposition. We argue that the equatorial region is a ;preservation zone; for whatever albedo is seeded there. This offers insight as to why the equatorial band of Pluto displays the planet's greatest albedo contrasts.

  20. High-temperature vesuvianite: crystal chemistry and surface considerations

    Science.gov (United States)

    Elmi, Chiara; Brigatti, Maria Franca; Pasquali, Luca; Montecchi, Monica; Laurora, Angela; Malferrari, Daniele; Nannarone, Stefano

    2011-06-01

    A multi-methodical approach has been applied for characterizing the bulk and surface crystal chemical features of a high-temperature vesuvianite crystal from skarns of Mount Somma-Vesuvius Volcano (Naples, Italy). Vesuvianite belongs to the space group P4/ nnc with unit cell parameters a = 15.633(1) Å, c = 11.834(1) Å and chemical formula (Ca18.858 Na0.028 Ba0.004 K0.006 Sr0.005 □0.098)19.000 (Al8.813 Ti0.037 Mg2.954 Mn0.008 Fe{0.114/2+} Fe{1.375/3+} Cr0.008 B0.202)13.511 Si18.000(O0.261 F0.940 OH7.799)9.000. Structure refinement, which converges at R = 0.0328, demonstrates a strong positional disorder down the fourfold axes, indicating that the Y1 site is split into two positions (Y1A and Y1B) alternatively occupied. However, because of X4 proximity to Y1B and Y1A, X4 cannot be occupied if Y1B or Y1A are. Overall Y1 occupancy (Y1A + Y1B) reaches approximately 0.5, as common in vesuvianite and occupancy of Y1B site is extremely limited. Moreover, T1 position, limitedly occupied, accommodates the excess of cations generally related to Y position. A small quantity (0.202 apfu) of boron is sited at the T2 site that, like T1, is poorly occupied. The determination of the amount of each element on the (100) vesuvianite surface, obtained through X-ray photoelectron spectroscopy high-resolution spectra in the region of the Si2p, Al2p, Mg1s, and Ca2p core levels, evidences that a greater amount of aluminum and a smaller amount of calcium characterize the surface with respect to the bulk. Although both of these features require further investigation, we may consider the Al increase can be related to preferential orientation of Al-rich sites on the (100) plane. Furthermore, the surface structure of vesuvianite suggests that Al, Ca, and Mg cations maintain coordination features at the surface similar to the bulk. Silica, however, while presenting fourfold coordination, shows also a [1]-fold small coordinated component at binding energy 99.85 eV, due to broken Si-O bonds at

  1. Seasonal Spatial Patterns of Surface Water Temperature, Surface Heat Fluxes and Meteorological Forcing Over Lake Geneva

    Science.gov (United States)

    Irani Rahaghi, A.; Lemmin, U.; Bouffard, D.; Riffler, M.; Wunderle, S.; Barry, D. A.

    2015-12-01

    In many lakes, surface heat flux (SHF) is the most important component controlling the lake's energy content. Accurate methods for the determination of SHF are valuable for water management, and for use in hydrological and meteorological models. Large lakes, not surprisingly, are subject to spatially and temporally varying meteorological conditions, and hence SHF. Here, we report on an investigation for estimating the SHF of a large European lake, Lake Geneva. We evaluated several bulk formulas to estimate Lake Geneva's SHF based on different data sources. A total of 64 different surface heat flux models were realized using existing representations for different heat flux components. Data sources to run the models included meteorological data (from an operational numerical weather prediction model, COSMO-2) and lake surface water temperature (LSWT, from satellite imagery). Models were calibrated at two points in the lake for which regular depth profiles of temperature are available, and which enabled computation of the total heat content variation. The latter, computed for 03.2008-12.2012, was the metric used to rank the different models. The best calibrated model was then selected to calculate the spatial distribution of SHF. Analysis of the model results shows that evaporative and convective heat fluxes are the dominant terms controlling the spatial pattern of SHF. The former is significant in all seasons while the latter plays a role only in fall and winter. Meteorological observations illustrate that wind-sheltering, and to some extent relative humidity variability, are the main reasons for the observed large-scale spatial variability. In addition, both modeling and satellite observations indicate that, on average, the eastern part of the lake is warmer than the western part, with a greater temperature contrast in spring and summer than in fall and winter whereas the SHF spatial splitting is stronger in fall and winter. This is mainly due to negative heat flux

  2. Data assimilation for air quality models

    DEFF Research Database (Denmark)

    Silver, Jeremy David

    2014-01-01

    -dimensional optimal interpolation procedure (OI), an Ensemble Kalman Filter (EnKF), and a three-dimensional variational scheme (3D-var). The three assimilation procedures are described and tested. A multi-faceted approach is taken for the verification, using independent measurements from surface air-quality...

  3. The mechanism for the impact of sea surface temperature anomaly on the ridgeline surface of Western Pacific

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Based on the atmospheric circulation data provided by ECMWF and the sea surface temperature data by NOAA, we studied the mechanism for the impact of sea surface temperature anomaly on the ridgeline surface of western Pacific using an improved high truncated spectral model. Our results show that the wave-wave interaction and the wave-mean flow interactions are weaker in the inner dynamic process of atmospheric circulation, when atmospheric circulation is forced by the sea surface temperature of El Ni-o pattern. With the external thermal forcing changed from winter to summer pattern, the range of ridgeline surface of western Pacific moving northward is smaller, which causes the ridgeline surface of western Pacific on south of normal. On the contrary, the wave-wave interaction and the wave-mean flow interaction are stronger, when atmospheric circulation is forced by the sea surface temperature of La Ni-a pattern. With the external thermal forcing turning from winter to summer pattern, the ridgeline surface of western Pacific shifts northward about 19 latitude degrees, which conduces the ridgeline surface of western Pacific on north of normal. After moving to certain latitude, the ridgeline surface of western Pacific oscillates with the most obvious 30-60 d period and the 4°-7° amplitude. It is one of the important reasons for the interannual variation of ridgeline surface of Western Pacific that the at- mospheric inner dynamical process forced out by different sea surface temperature anomaly pattern is different.

  4. The impact of heterogeneous surface temperatures on the 2-m air temperature over the Arctic Ocean in spring

    Directory of Open Access Journals (Sweden)

    A. Tetzlaff

    2012-07-01

    Full Text Available The influence of spatial surface temperature changes over the Arctic Ocean on the 2-m air temperature variability is estimated using backward trajectories based on ERA-Interim and the JRA25 wind fields. They are initiated at Alert, Barrow and at the Tara drifting station. Three different methods are used. The first one compares mean ice surface temperatures along the trajectories to the observed 2-m air temperatures at the stations. The second one correlates the observed temperatures to air temperatures obtained using a simple Lagrangian box model which only includes the effect of sensible heat fluxes. For the third method, mean sensible heat fluxes from the model are correlated with the difference of the air temperatures at the model starting point and the observed temperatures at the stations. The calculations are based on MODIS ice surface temperatures and four different sets of ice concentration derived from SSM/I and AMSR-E data. Under nearly cloud free conditions, up to 90% of the 2-m air temperature variance can be explained for Alert, and 60% for Barrow using these methods. The differences are attributed to the different ice conditions, which are characterized by high ice concentration around Alert and lower ice concentration near Barrow. These results are robust for the different sets of reanalyses and ice concentration data. Near-surface winds of both reanalyses show a large inconsistency in the Central Arctic, which leads to a large difference in the correlations between modeled and observed 2-m air temperatures at Tara. Explained variances amount to 70% using JRA and only 45% using ERA. The results also suggest that near-surface temperatures at a given site are influenced by the variability of surface temperatures in a domain of about 150 to 350 km radius around the site.

  5. Screen-level non-GTS data assimilation in a limited-area mesoscale model

    Directory of Open Access Journals (Sweden)

    M. Milelli

    2010-06-01

    Full Text Available The forecast in areas of very complex topography, as for instance the Alpine region, is still a challenge even for the new generation of numerical weather prediction models which aim at reaching the km-scale. The problem is enhanced by a general lack of standard observations, which is even more evident over the southern side of the Alps. For this reason, it would be useful to increase the performance of the mathematical models by locally assimilating non-conventional data. Since in ARPA Piemonte there is the availability of a great number of non-GTS stations, it has been decided to assimilate the 2 m temperature, coming from this dataset, in the very-high resolution version of the COSMO model, which has a horizontal resolution of about 3 km, more similar to the average resolution of the thermometers. Four different weather situations have been considered, ranging from spring to winter, from cloudy to clear sky. The aim of the work is to investigate the effects of the assimilation of non-GTS data in order to create an operational very high-resolution analysis, but also to test the option of running in the future a very short-range forecast starting from these analyses (RUC or Rapid Update Cycle. The results, in terms of Root Mean Square Error, Mean Error and diurnal cycle of some surface variables such as 2 m temperature, 2 m relative humidity and 10 m wind intensity show a positive impact during the assimilation cycle which tends to dissipate a few hours after the end of it. Moreover, the 2 m temperature assimilation has a slightly positive or neutral impact on the vertical profiles of temperature, eventhough some calibration is needed for the precipitation field which is too much perturbed during the assimilation cycle, while it is unaffected in the forecast period. So the stability of the planetary boundary layer, on the one hand, has not been particularly improved by the new-data assimilation, but, on the other hand, it has not been destroyed

  6. Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

    Science.gov (United States)

    Al-Hamdan, M. Z.; Crosson, W. L.; Estes, M. G., Jr.; Estes, S. M.; Quattrochi, D. A.; Johnson, D.

    2013-12-01

    This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heat-related mortality data. The current HWWS do not take into account intra-urban spatial variations in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with land surface temperature (LST) estimates derived from thermal remote sensing data. In order to further improve the assessment of intra-urban variations in risk from extreme heat, we developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. We will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

  7. Spatial Statistical Estimation for Massive Sea Surface Temperature Data

    Science.gov (United States)

    Marchetti, Y.; Vazquez, J.; Nguyen, H.; Braverman, A. J.

    2015-12-01

    We combine several large remotely sensed sea surface temperature (SST) datasets to create a single high-resolution SST dataset that has no missing data and provides an uncertainty associated with each value. This high resolution dataset will optimize estimates of SST in critical parts of the world's oceans, such as coastal upwelling regions. We use Spatial Statistical Data Fusion (SSDF), a statistical methodology for predicting global spatial fields by exploiting spatial correlations in the data. The main advantages of SSDF over spatial smoothing methodologies include the provision of probabilistic uncertainties, the ability to incorporate multiple datasets with varying footprints, measurement errors and biases, and estimation at any desired resolution. In order to accommodate massive input and output datasets, we introduce two modifications of the existing SSDF algorithm. First, we compute statistical model parameters based on coarse resolution aggregated data. Second, we use an adaptive spatial grid that allows us to perform estimation in a specified region of interest, but incorporate spatial dependence between locations in that region and all locations globally. Finally, we demonstrate with a case study involving estimations on the full globe at coarse resolution grid (30 km) and a high resolution (1 km) inset for the Gulf Stream region.

  8. Quality control methods for KOOS operational sea surface temperature products

    Institute of Scientific and Technical Information of China (English)

    YANG Chansu; KIM Sunhwa

    2016-01-01

    Sea surface temperature SST obtained from the initial version of the Korea Operational Oceanographic System (KOOS) SST satellite have low accuracy during summer and daytime. This is attributed to the diurnal warming effect. Error estimation of SST data must be carried out to use the real-time forecasting numerical model of the KOOS. This study suggests two quality control methods for the KOOS SST system. To minimize the diurnal warming effect, SSTs of areas where wind speed is higher than 5 m/s were used. Depending on the wind threshold value, KOOS SST data for August 2014 were reduced by 0.15°C. Errors in SST data are considered to be a combination of random, sampling, and bias errors. To estimate bias error, the standard deviation of bias between KOOS SSTs and climatology SSTs were used. KOOS SST data yielded an analysis error standard deviation value similar to OSTIA and NOAA NCDC (OISST) data. The KOOS SST shows lower random and sampling errors with increasing number of observations using six satellite datasets. In further studies, the proposed quality control methods for the KOOS SST system will be applied through more long-term case studies and comparisons with other SST systems.

  9. Bias correction methods for decadal sea-surface temperature forecasts

    Directory of Open Access Journals (Sweden)

    Balachandrudu Narapusetty

    2014-04-01

    Full Text Available Two traditional bias correction techniques: (1 systematic mean correction (SMC and (2 systematic least-squares correction (SLC are extended and applied on sea-surface temperature (SST decadal forecasts in the North Pacific produced by Climate Forecast System version 2 (CFSv2 to reduce large systematic biases. The bias-corrected forecast anomalies exhibit reduced root-mean-square errors and also significantly improve the anomaly correlations with observations. The spatial pattern of the SST anomalies associated with the Pacific area average (PAA index (spatial average of SST anomalies over 20°–60°N and 120°E–100°W is improved after employing the bias correction methods, particularly SMC. Reliability diagrams show that the bias-corrected forecasts better reproduce the cold and warm events well beyond the 5-yr lead-times over the 10 forecasted years. The comparison between both correction methods indicates that: (1 prediction skill of SST anomalies associated with the PAA index is improved by SMC with respect to SLC and (2 SMC-derived forecasts have a slightly higher reliability than those corrected by SLC.

  10. Downscaling MODIS Land Surface Temperature for Urban Public Health Applications

    Science.gov (United States)

    Al-Hamdan, Mohammad; Crosson, William; Estes, Maurice, Jr.; Estes, Sue; Quattrochi, Dale; Johnson, Daniel

    2013-01-01

    This study is part of a project funded by the NASA Applied Sciences Public Health Program, which focuses on Earth science applications of remote sensing data for enhancing public health decision-making. Heat related death is currently the number one weather-related killer in the United States. Mortality from these events is expected to increase as a function of climate change. This activity sought to augment current Heat Watch/Warning Systems (HWWS) with NASA remotely sensed data, and models used in conjunction with socioeconomic and heatrelated mortality data. The current HWWS do not take into account intra-urban spatial variation in risk assessment. The purpose of this effort is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature (LST) derived from thermal remote sensing data. In order to further improve the consideration of intra-urban variations in risk from extreme heat, we also developed and evaluated a number of spatial statistical techniques for downscaling the 1-km daily MODerate-resolution Imaging Spectroradiometer (MODIS) LST data to 60 m using Landsat-derived LST data, which have finer spatial but coarser temporal resolution than MODIS. In this paper, we will present these techniques, which have been demonstrated and validated for Phoenix, AZ using data from the summers of 2000-2006.

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

    Science.gov (United States)

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

    2016-10-01

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

  12. Data assimilation with the Ensemble Kalman Filter in simple forced and coupled models of the equatorial Pacific Ocean

    Science.gov (United States)

    Leeuwenburgh, O.; Burgers, G.

    2003-04-01

    An ocean data assimilation and forecast system for the Equatorial Pacific is presented. The Ensemble Kalman Filter is used to combine several types of real data with a reduced-gravity shallow-water model containing a simplified SST equation. A preliminary version of this assimilation system has been found in the past to produce skillful forecasts of Nino 3 and Nino 4 SST anomalies when artifical data obtained from model runs are used. The small size and simplicity of the model now allows us to experiment with different types of real data, ensemble sizes, assimilation frequency, etc. Forecasts are made by coupling a statistical atmosphere to the ocean model. We make a comparison between assimilation of subsurface temperature information and sea surface temperature and height into a model forced by observed winds, and assimilation of both ocean data and observed winds into the coupled model. The influence of model error can be studied by introducing changes to the model parameterizations or by comparing the difference in skill between the real data case and a twin experiment setup. The results are compared with the historical record of SST anomalies and will serve as a benchmark for the implementation of the Ensemble Kalman Filter with more elaborate models.

  13. Molecular Dynamics of Carbon Nanotubes Deposited on a Silicon Surface via Collision: Temperature Dependence

    Energy Technology Data Exchange (ETDEWEB)

    Saha, Leton C.; Mian, Shabeer A.; Kim, Hyo Jeong; Saha, Joyanta K.; Matin,