Estimating daily minimum, maximum, and mean near surface air temperature using hybrid satellite models across Israel.

PubMed

Rosenfeld, Adar; Dorman, Michael; Schwartz, Joel; Novack, Victor; Just, Allan C; Kloog, Itai

2017-11-01

Meteorological stations measure air temperature (Ta) accurately with high temporal resolution, but usually suffer from limited spatial resolution due to their sparse distribution across rural, undeveloped or less populated areas. Remote sensing satellite-based measurements provide daily surface temperature (Ts) data in high spatial and temporal resolution and can improve the estimation of daily Ta. In this study we developed spatiotemporally resolved models which allow us to predict three daily parameters: Ta Max (day time), 24h mean, and Ta Min (night time) on a fine 1km grid across the state of Israel. We used and compared both the Aqua and Terra MODIS satellites. We used linear mixed effect models, IDW (inverse distance weighted) interpolations and thin plate splines (using a smooth nonparametric function of longitude and latitude) to first calibrate between Ts and Ta in those locations where we have available data for both and used that calibration to fill in neighboring cells without surface monitors or missing Ts. Out-of-sample ten-fold cross validation (CV) was used to quantify the accuracy of our predictions. Our model performance was excellent for both days with and without available Ts observations for both Aqua and Terra (CV Aqua R 2 results for min 0.966, mean 0.986, and max 0.967; CV Terra R 2 results for min 0.965, mean 0.987, and max 0.968). Our research shows that daily min, mean and max Ta can be reliably predicted using daily MODIS Ts data even across Israel, with high accuracy even for days without Ta or Ts data. These predictions can be used as three separate Ta exposures in epidemiology studies for better diurnal exposure assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

The collaborative historical African rainfall model: description and evaluation

USGS Publications Warehouse

Funk, Christopher C.; Michaelsen, Joel C.; Verdin, James P.; Artan, Guleid A.; Husak, Gregory; Senay, Gabriel B.; Gadain, Hussein; Magadazire, Tamuka

2003-01-01

In Africa the variability of rainfall in space and time is high, and the general availability of historical gauge data is low. This makes many food security and hydrologic preparedness activities difficult. In order to help overcome this limitation, we have created the Collaborative Historical African Rainfall Model (CHARM). CHARM combines three sources of information: climatologically aided interpolated (CAI) rainfall grids (monthly/0.5° ), National Centers for Environmental Prediction reanalysis precipitation fields (daily/1.875° ) and orographic enhancement estimates (daily/0.1° ). The first set of weights scales the daily reanalysis precipitation fields to match the gridded CAI monthly rainfall time series. This produces data with a daily/0.5° resolution. A diagnostic model of orographic precipitation, VDELB—based on the dot-product of the surface wind V and terrain gradient (DEL) and atmospheric buoyancy B—is then used to estimate the precipitation enhancement produced by complex terrain. Although the data are produced on 0.1° grids to facilitate integration with satellite-based rainfall estimates, the ‘true’ resolution of the data will be less than this value, and varies with station density, topography, and precipitation dynamics. The CHARM is best suited, therefore, to applications that integrate rainfall or rainfall-driven model results over large regions. The CHARM time series is compared with three independent datasets: dekadal satellite-based rainfall estimates across the continent, dekadal interpolated gauge data in Mali, and daily interpolated gauge data in western Kenya. These comparisons suggest reasonable accuracies (standard errors of about half a standard deviation) when data are aggregated to regional scales, even at daily time steps. Thus constrained, numerical weather prediction precipitation fields do a reasonable job of representing large-scale diurnal variations.

Fusing Cubesat and Landsat 8 data for near-daily mapping of leaf area index at 3 m resolution

NASA Astrophysics Data System (ADS)

McCabe, M.; Houborg, R.

2017-12-01

Constellations of small cubesats are emerging as a relatively inexpensive observational resource with the potential to overcome spatio-temporal constraints of traditional single-sensor satellite missions. With more than 130 compact 3U (i.e., 10 x 10 x 30 cm) cubesats currently in orbit, the company "Planet" has realized near-daily image capture in RGB and the near-infrared (NIR) at 3 m resolution for every location on the earth. However cross-sensor inconsistencies can be a limiting factor, which result from relatively low signal-to-noise ratios, varying overpass times, and sensor-specific spectral response functions. In addition, the sensor radiometric information content is more limited compared to conventional satellite systems such as Landsat. In this study, a synergistic machine-learning framework utilizing Planet, Landsat 8, and MODIS data is developed to produce Landsat 8 consistent LAI with a factor of 10 increase in spatial resolution and a daily observing potential, globally. The Cubist machine-learning technique is used to establish scene-specific links between scale-consistent cubesat RGB+NIR imagery and Landsat 8 LAI. The scheme implements a novel LAI target sampling technique for model training purposes, which accounts for changes in cover conditions over the cubesat and Landsat acquisition timespans. Results over an agricultural region in Saudi Arabia highlight the utility of the approach for detecting high frequency (i.e., near-daily) and fine-scale (i.e., 3 m) intra-field dynamics in LAI with demonstrated potential for timely identification of developing crop risks. The framework maximizes the utility of ultra-high resolution cubesat data for agricultural management and resource efficiency optimization at the precision scale.

Daily communication, conflict resolution, and marital quality in Chinese marriage: A three-wave, cross-lagged analysis.

PubMed

Li, Xiaomin; Cao, Hongjian; Zhou, Nan; Ju, Xiaoyan; Lan, Jing; Zhu, Qinyi; Fang, Xiaoyi

2018-05-17

Based on three annual waves of data obtained from 268 Chinese couples in the early years of marriage and using a three-wave, cross-lagged approach, the present study examined the associations among daily marital communication, marital conflict resolution, and marital quality. Results indicated unidirectional associations linking daily marital communication or marital conflict resolution to marital quality (instead of reciprocal associations); and when considered simultaneously in a single model, daily marital communication and marital conflict resolution explained variance in marital quality above and beyond each other. Furthermore, the authors also found a significant longitudinal, indirect association linking husbands' daily marital communication at Wave 1 to husbands' marital quality at Wave 3 via husbands' marital conflict resolution at Wave 2. Taken altogether, the current study adds to an emerging body of research aimed at clarifying: (a) the directionality of the associations between couple interactive processes and marital well-being; (b) the unique roles of daily marital communication and marital conflict resolution in predicting marital outcomes; and (c) how daily marital communication and marital conflict resolution may operate in conjunction with each other to shape the development of couple relationship well-being. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Assessment of spatiotemporal fusion algorithms for Planet and Worldview images

USDA-ARS?s Scientific Manuscript database

Although Worldview (WV) images (non-pansharpened) have 2-meter resolution, the re-visit times for the same areas may be 7 days or more. In contrast, Planet images using small satellites can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It will be ideal to f...

Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data

Treesearch

Qingyuan Zhang; Xiangming Xiao; Bobby Braswell; Ernst Linder; Scott Ollinger; Marie-Louise Smith; Julian P. Jenkins; Fred Baret; Andrew D. Richardson; Berrien III Moore; Rakesh Minocha

2006-01-01

In this paper, we present an improved procedure for collecting no or little atmosphere- and snow-contaminated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The resultant time series of daily MODIS data of a temperate deciduous broadleaf forest (the Bartlett Experimental Forest) in 2004 show strong seasonal dynamics of surface...

Computation Methods for NASA Data-streams for Agricultural Efficiency Applications

NASA Astrophysics Data System (ADS)

Shrestha, B.; O'Hara, C. G.; Mali, P.

2007-12-01

Temporal Map Algebra (TMA) is a novel technique for analyzing time-series of satellite imageries using simple algebraic operators that treats time-series imageries as a three-dimensional dataset, where two dimensions encode planimetric position on earth surface and the third dimension encodes time. Spatio-temporal analytical processing methods such as TMA that utilize moderate spatial resolution satellite imagery having high temporal resolution to create multi-temporal composites are data intensive as well as computationally intensive. TMA analysis for multi-temporal composites provides dramatically enhanced usefulness that will yield previously unavailable capabilities to user communities, if deployment is coupled with significant High Performance Computing (HPC) capabilities; and interfaces are designed to deliver the full potential for these new technological developments. In this research, cross-platform data fusion and adaptive filtering using TMA was employed to create highly useful daily datasets and cloud-free high-temporal resolution vegetation index (VI) composites with enhanced information content for vegetation and bio-productivity monitoring, surveillance, and modeling. Fusion of Normalized Difference Vegetation Index (NDVI) data created from Aqua and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) surface-reflectance data (MOD09) enables the creation of daily composites which are of immense value to a broad spectrum of global and national applications. Additionally these products are highly desired by many natural resources agencies like USDA/FAS/PECAD. Utilizing data streams collected by similar sensors on different platforms that transit the same areas at slightly different times of the day offers the opportunity to develop fused data products that have enhanced cloud-free and reduced noise characteristics. Establishing a Fusion Quality Confidence Code (FQCC) provides a metadata product that quantifies the method of fusion for a given pixel and enables a relative quality and confidence factor to be established for a given daily pixel value. When coupled with metadata that quantify the source sensor, day and time of acquisition, and the fusion method of each pixel to create the daily product; a wealth of information is available to assist in deriving new data and information products. These newly developed abilities to create highly useful daily data sets imply that temporal composites for a geographic area of interest may be created for user-defined temporal intervals that emphasize a user designated day of interest. At GeoResources Institute, Mississippi State University, solutions have been developed to create custom composites and cross-platform satellite data fusion using TMA which are useful for National Aeronautics and Space Administration (NASA) Rapid Prototyping Capability (RPC) and Integrated System Solutions (ISS) experiments for agricultural applications.

A generalized formulation for downscaling data based on Fourier Transform and inversion: Mathematical rationale and application to the Max-Planck-Institute aerosol climatology data

NASA Astrophysics Data System (ADS)

Zhang, Taiping; Stackhouse, Paul W.; Gupta, Shashi K.; Cox, Stephen J.; Mikovitz, J. Colleen

2017-02-01

Occasionally, a need arises to downscale a time series of data from a coarse temporal resolution to a finer one, a typical example being from monthly means to daily means. For this case, daily means derived as such are used as inputs of climatic or atmospheric models so that the model results may exhibit variance on the daily time scale and retain the monthly mean of the original data set without an abrupt change from the end of one month to the beginning of the next. Different methods have been developed which often need assumptions, free parameters and the solution of simultaneous equations. Here we derive a generalized formulation by means of Fourier transform and inversion so that it can be used to directly compute daily means from a series of an arbitrary number of monthly means. The formulation can be used to transform any coarse temporal resolution to a finer one. From the derived results, the original data can be recovered almost identically. As a real application, we use this method to derive the daily counterpart of the MAC-v1 aerosol climatology that provides monthly mean aerosol properties for 18 shortwave bands and 12 longwave bands for the years from 1860 to 2100. The derived daily means are to be used as inputs of the shortwave and longwave algorithms of the NASA GEWEX SRB project.

Modeling fire behavior on tropical islands with high-resolution weather data

Treesearch

John W. Benoit; Francis M. Fujioka; David R. Weise

2009-01-01

In this study, we consider fire behavior simulation in tropical island scenarios such as Hawaii and Puerto Rico. The development of a system to provide real-time fire behavior prediction in Hawaii is discussed. This involves obtaining fuels and topography information at a fine scale, as well as supplying daily high-resolution weather forecast data for the area of...

Evaluation and intercomparison of GPM-IMERG and TRMM 3B42 daily precipitation products over Greece

NASA Astrophysics Data System (ADS)

Kazamias, A. P.; Sapountzis, M.; Lagouvardos, K.

2017-09-01

Accurate precipitation data at high temporal and spatial resolutions are needed for numerous applications in hydrology, water resources management and flood risk management. Satellite-based precipitation estimations/products offer a potential alternative source of rainfall data for regions with sparse rain gauge network. The recently launched Global Precipitation Measurement (GPM) mission is the successor of Tropical Rainfall Measuring Mission (TRMM) providing global precipitation estimates at spatial resolution of 0.1 degree x 0.1 degree and half-hourly temporal resolution. This study aims at evaluating the accuracy of the Integrated Multi-satellite Retrievals for GPM (IMERG) near-real-time daily product (GPM-3IMERGDL) against rain gauge observations from a network of stations distributed across Greece for the year 2016. Moreover, the GPM-IMERG product is also compared with its predecessor, the Version-7 near-real-time (3B42RT) daily product of TRMM Multisatellite Precipitation Analysis (TMPA). Several statistical metrics are used to quantitatively evaluate the performance of the satellite-based precipitation estimates against rain gauge observations. In addition, categorical statistical indices are used to assess rain detection capabilities of the two satellite products. The GPM-IMERG daily product shows reasonable agreement (CC=0.60) against rain gauge observations, with the exception of coastal areas in which low correlations are achieved. The GPM-IMERG daily precipitation product tends to overestimate rainfall, especially in complex terrain areas with high annual precipitation. In particular, rainfall estimates in western Greece have a strong positive bias. On the other hand, the TRMM 3B42 product shows low correlation (CC=0.45) against rain gauge observations and slightly underestimates rainfall. This study is a first attempt to evaluate and compare the newly introduced GPM-IMERG and the TRMM 3B42 rainfall products at daily timescale over Greece.

The Role of Temporal Evolution in Modeling Atmospheric Emissions from Tropical Fires

NASA Technical Reports Server (NTRS)

Marlier, Miriam E.; Voulgarakis, Apostolos; Shindell, Drew T.; Faluvegi, Gregory S.; Henry, Candise L.; Randerson, James T.

2014-01-01

Fire emissions associated with tropical land use change and maintenance influence atmospheric composition, air quality, and climate. In this study, we explore the effects of representing fire emissions at daily versus monthly resolution in a global composition-climate model. We find that simulations of aerosols are impacted more by the temporal resolution of fire emissions than trace gases such as carbon monoxide or ozone. Daily-resolved datasets concentrate emissions from fire events over shorter time periods and allow them to more realistically interact with model meteorology, reducing how often emissions are concurrently released with precipitation events and in turn increasing peak aerosol concentrations. The magnitude of this effect varies across tropical ecosystem types, ranging from smaller changes in modeling the low intensity, frequent burning typical of savanna ecosystems to larger differences when modeling the short-term, intense fires that characterize deforestation events. The utility of modeling fire emissions at a daily resolution also depends on the application, such as modeling exceedances of particulate matter concentrations over air quality guidelines or simulating regional atmospheric heating patterns.

High-resolution spatial modeling of daily weather elements for a catchment in the Oregon Cascade Mountains, United States

Treesearch

Christopher Daly; Jonathan W. Smith; Joseph I. Smith; Robert B. McKane

2007-01-01

High-quality daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decisionmaking. This paper describes the development. application. and assessment of methods to construct daily high resolution (~50-m cell size) meteorological grids for the...

Influence of daily versus monthly fire emissions on atmospheric model applications in the tropics

NASA Astrophysics Data System (ADS)

Marlier, M. E.; Voulgarakis, A.; Faluvegi, G.; Shindell, D. T.; DeFries, R. S.

2012-12-01

Fires are widely used throughout the tropics to create and maintain areas for agriculture, but are also significant contributors to atmospheric trace gas and aerosol concentrations. However, the timing and magnitude of fire activity can vary strongly by year and ecosystem type. For example, frequent, low intensity fires dominate in African savannas whereas Southeast Asian peatland forests are susceptible to huge pulses of emissions during regional El Niño droughts. Despite the potential implications for modeling interactions with atmospheric chemistry and transport, fire emissions have commonly been input into global models at a monthly resolution. Recognizing the uncertainty that this can introduce, several datasets have parsed fire emissions to daily and sub-daily scales with satellite active fire detections. In this study, we explore differences between utilizing the monthly and daily Global Fire Emissions Database version 3 (GFED3) products as inputs into the NASA GISS-E2 composition climate model. We aim to understand how the choice of the temporal resolution of fire emissions affects uncertainty with respect to several common applications of global models: atmospheric chemistry, air quality, and climate. Focusing our analysis on tropical ozone, carbon monoxide, and aerosols, we compare modeled concentrations with available ground and satellite observations. We find that increasing the temporal frequency of fire emissions from monthly to daily can improve correlations with observations, predominately in areas or during seasons more heavily affected by fires. Differences between the two datasets are more evident with public health applications: daily resolution fire emissions increases the number of days exceeding World Health Organization air quality targets.

Calculating distributed glacier mass balance for the Swiss Alps from RCM output: Development and testing of downscaling and validation methods

NASA Astrophysics Data System (ADS)

Machguth, H.; Paul, F.; Kotlarski, S.; Hoelzle, M.

2009-04-01

Climate model output has been applied in several studies on glacier mass balance calculation. Hereby, computation of mass balance has mostly been performed at the native resolution of the climate model output or data from individual cells were selected and statistically downscaled. Little attention has been given to the issue of downscaling entire fields of climate model output to a resolution fine enough to compute glacier mass balance in rugged high-mountain terrain. In this study we explore the use of gridded output from a regional climate model (RCM) to drive a distributed mass balance model for the perimeter of the Swiss Alps and the time frame 1979-2003. Our focus lies on the development and testing of downscaling and validation methods. The mass balance model runs at daily steps and 100 m spatial resolution while the RCM REMO provides daily grids (approx. 18 km resolution) of dynamically downscaled re-analysis data. Interpolation techniques and sub-grid parametrizations are combined to bridge the gap in spatial resolution and to obtain daily input fields of air temperature, global radiation and precipitation. The meteorological input fields are compared to measurements at 14 high-elevation weather stations. Computed mass balances are compared to various sets of direct measurements, including stake readings and mass balances for entire glaciers. The validation procedure is performed separately for annual, winter and summer balances. Time series of mass balances for entire glaciers obtained from the model run agree well with observed time series. On the one hand, summer melt measured at stakes on several glaciers is well reproduced by the model, on the other hand, observed accumulation is either over- or underestimated. It is shown that these shifts are systematic and correlated to regional biases in the meteorological input fields. We conclude that the gap in spatial resolution is not a large drawback, while biases in RCM output are a major limitation to model performance. The development and testing of methods to reduce regionally variable biases in entire fields of RCM output should be a focus of pursuing studies.

SDCLIREF - A sub-daily gridded reference dataset

NASA Astrophysics Data System (ADS)

Wood, Raul R.; Willkofer, Florian; Schmid, Franz-Josef; Trentini, Fabian; Komischke, Holger; Ludwig, Ralf

2017-04-01

Climate change is expected to impact the intensity and frequency of hydrometeorological extreme events. In order to adequately capture and analyze extreme rainfall events, in particular when assessing flood and flash flood situations, data is required at high spatial and sub-daily resolution which is often not available in sufficient density and over extended time periods. The ClimEx project (Climate Change and Hydrological Extreme Events) addresses the alteration of hydrological extreme events under climate change conditions. In order to differentiate between a clear climate change signal and the limits of natural variability, unique Single-Model Regional Climate Model Ensembles (CRCM5 driven by CanESM2, RCP8.5) were created for a European and North-American domain, each comprising 50 members of 150 years (1951-2100). In combination with the CORDEX-Database, this newly created ClimEx-Ensemble is a one-of-a-kind model dataset to analyze changes of sub-daily extreme events. For the purpose of bias-correcting the regional climate model ensembles as well as for the baseline calibration and validation of hydrological catchment models, a new sub-daily (3h) high-resolution (500m) gridded reference dataset (SDCLIREF) was created for a domain covering the Upper Danube and Main watersheds ( 100.000km2). As the sub-daily observations lack a continuous time series for the reference period 1980-2010, the need for a suitable method to bridge the gap of the discontinuous time series arouse. The Method of Fragments (Sharma and Srikanthan (2006); Westra et al. (2012)) was applied to transform daily observations to sub-daily rainfall events to extend the time series and densify the station network. Prior to applying the Method of Fragments and creating the gridded dataset using rigorous interpolation routines, data collection of observations, operated by several institutions in three countries (Germany, Austria, Switzerland), and the subsequent quality control of the observations was carried out. Among others, the quality control checked for steps, extensive dry seasons, temporal consistency and maximum hourly values. The resulting SDCLIREF dataset provides a robust precipitation reference for hydrometeorological applications in unprecedented high spatio-temporal resolution. References: Sharma, A.; Srikanthan, S. (2006): Continuous Rainfall Simulation: A Nonparametric Alternative. In: 30th Hydrology and Water Resources Symposium 4-7 December 2006, Launceston, Tasmania. Westra, S.; Mehrotra, R.; Sharma, A.; Srikanthan, R. (2012): Continuous rainfall simulation. 1. A regionalized subdaily disaggregation approach. In: Water Resour. Res. 48 (1). DOI: 10.1029/2011WR010489.

Valomaciclovir versus valacyclovir for the treatment of acute herpes zoster in immunocompetent adults: a randomized, double-blind, active-controlled trial.

PubMed

Tyring, Stephen K; Plunkett, Stephanie; Scribner, Anita R; Broker, Robert E; Herrod, John N; Handke, Lane T; Wise, John M; Martin, Paul A

2012-08-01

Herpes zoster is a common infectious disease that can result in significant acute and chronic morbidity. The safety and efficacy of once-daily oral valomaciclovir (EPB-348) was evaluated for non-inferiority to 3-times daily valacyclovir, an approved therapy. In this study, 373 immunocompetent adults with onset of a herpes zoster rash within the preceding 72 hr were randomly assigned to receive one of four treatments for 7 days: (1) EPB-348 1,000 mg once-daily; (2) EPB-348 2,000 mg once-daily; (3) EPB-348 3,000 mg once-daily; or (4) valacyclovir 1,000 mg 3-times daily. A 20% margin was the reference for non-inferiority assessment. For the primary efficacy measure of time to complete crusting of the zoster rash by Day 28, non-inferiority criteria were met for once-daily EPB-348 2,000 mg and once-daily EPB-348 3,000 mg compared to 3-times daily valacyclovir. Additionally, EPB-348 3,000 mg significantly shortened the time to complete rash crusting by Day 28 compared to valacyclovir. For secondary efficacy measures, non-inferiority was achieved for the EPB-348 1,000 and 2,000 mg groups compared to the valacyclovir group for time to rash resolution by Day 28. No EPB-348 group was non-inferior to valacyclovir for time to cessation of new lesion formation or time to cessation of pain by Day 120, though no significant differences occurred between treatment groups. Nausea, headache, and vomiting were the most common adverse events. Based on these results, additional studies are warranted to define further EPB-348's potential as an effective and safe therapy for acute herpes zoster. Copyright © 2012 Wiley Periodicals, Inc.

Hydrological Applications of a High-Resolution Radar Precipitation Data Base for Sweden

NASA Astrophysics Data System (ADS)

Olsson, Jonas; Berg, Peter; Norin, Lars; Simonsson, Lennart

2017-04-01

There is an increasing need for high-resolution observations of precipitation on local, regional, national and even continental level. Urbanization and other environmental changes often make societies more vulnerable to intense short-duration rainfalls (cloudbursts) and their consequences in terms of e.g. flooding and landslides. Impact and forecasting models of these hazards put very high demands on the rainfall input in terms of both resolution and accuracy. Weather radar systems obviously have a great potential in this context, but also limitations with respect to e.g. conversion algorithms and various error sources that may have a significant impact on the subsequent hydrological modelling. In Sweden, the national weather radar network has been in operation for nearly three decades, but until recently the hydrological applications have been very limited. This is mainly because of difficulties in managing the different errors and biases in the radar precipitation product, which made it hard to demonstrate any distinct added value as compared with gauge-based precipitation products. In the last years, however, in light of distinct progress in developing error correction procedures, substantial efforts have been made to develop a national gauge-adjusted radar precipitation product - HIPRAD (High-Resolution Precipitation from Gauge-Adjusted Weather Radar). In HIPRAD, the original radar precipitation data are scaled to match the monthly accumulations in a national grid (termed PTHBV) created by optimal interpolation of corrected daily gauge observations, with the intention to attain both a high spatio-temporal resolution and accurate long-term accumulations. At present, HIPRAD covers the period 2000-present with resolutions 15 min and 2×2 km2. A key motivation behind the development of HIPRAD is the intention to increase the temporal resolution in the national flood forecasting system from 1 day to 1 hour. Whereas a daily time step is sufficient to describe the rainfall-runoff process in large, slow river basins, which traditionally has been the main focus in the national forecasting, an hourly time step (or preferably even shorter) is required to simulate the flow in fast-responding basins. At the daily scale, the PTHBV product is used for model initialization prior to the forecasts but with its daily resolution it is not applicable at the hourly scale. For this purpose, a real-time version of HIPRAD has been developed which is currently running operationally. HIPRAD is also being used for historical simulations with an hourly time step, which is important for e.g. water quality assessment. Finally, we will use HIPRAD to gain an improved knowledge of the short-duration precipitation climate in Sweden. Currently there are many open issues with respect to e.g. geographical differences, spatial correlations and areal extremes. Here we will show and discuss selected results from the ongoing development and validation of HIPRAD as well as its various applications for hydrological forecasting and risk assessment. Further, web resources containing radar-based observation and forecasting for hydrological applications will be demonstrated. Finally, some future research directions will be outlined. Fast responding hydrological catchments require fine spatial and temporal resolution of the precipitation input data to provide realistic results.

Impact of temporal upscaling and chemical transport model horizontal resolution on reducing ozone exposure misclassification

NASA Astrophysics Data System (ADS)

Xu, Yadong; Serre, Marc L.; Reyes, Jeanette M.; Vizuete, William

2017-10-01

We have developed a Bayesian Maximum Entropy (BME) framework that integrates observations from a surface monitoring network and predictions from a Chemical Transport Model (CTM) to create improved exposure estimates that can be resolved into any spatial and temporal resolution. The flexibility of the framework allows for input of data in any choice of time scales and CTM predictions of any spatial resolution with varying associated degrees of estimation error and cost in terms of implementation and computation. This study quantifies the impact on exposure estimation error due to these choices by first comparing estimations errors when BME relied on ozone concentration data either as an hourly average, the daily maximum 8-h average (DM8A), or the daily 24-h average (D24A). Our analysis found that the use of DM8A and D24A data, although less computationally intensive, reduced estimation error more when compared to the use of hourly data. This was primarily due to the poorer CTM model performance in the hourly average predicted ozone. Our second analysis compared spatial variability and estimation errors when BME relied on CTM predictions with a grid cell resolution of 12 × 12 km2 versus a coarser resolution of 36 × 36 km2. Our analysis found that integrating the finer grid resolution CTM predictions not only reduced estimation error, but also increased the spatial variability in daily ozone estimates by 5 times. This improvement was due to the improved spatial gradients and model performance found in the finer resolved CTM simulation. The integration of observational and model predictions that is permitted in a BME framework continues to be a powerful approach for improving exposure estimates of ambient air pollution. The results of this analysis demonstrate the importance of also understanding model performance variability and its implications on exposure error.

The effect of flow data resolution on sediment yield estimation and channel design

NASA Astrophysics Data System (ADS)

Rosburg, Tyler T.; Nelson, Peter A.; Sholtes, Joel S.; Bledsoe, Brian P.

2016-07-01

The decision to use either daily-averaged or sub-daily streamflow records has the potential to impact the calculation of sediment transport metrics and stream channel design. Using bedload and suspended load sediment transport measurements collected at 138 sites across the United States, we calculated the effective discharge, sediment yield, and half-load discharge using sediment rating curves over long time periods (median record length = 24 years) with both daily-averaged and sub-daily streamflow records. A comparison of sediment transport metrics calculated with both daily-average and sub-daily stream flow data at each site showed that daily-averaged flow data do not adequately represent the magnitude of high stream flows at hydrologically flashy sites. Daily-average stream flow data cause an underestimation of sediment transport and sediment yield (including the half-load discharge) at flashy sites. The degree of underestimation was correlated with the level of flashiness and the exponent of the sediment rating curve. No consistent relationship between the use of either daily-average or sub-daily streamflow data and the resultant effective discharge was found. When used in channel design, computed sediment transport metrics may have errors due to flow data resolution, which can propagate into design slope calculations which, if implemented, could lead to unwanted aggradation or degradation in the design channel. This analysis illustrates the importance of using sub-daily flow data in the calculation of sediment yield in urbanizing or otherwise flashy watersheds. Furthermore, this analysis provides practical charts for estimating and correcting these types of underestimation errors commonly incurred in sediment yield calculations.

The combined use of Green-Ampt model and Curve Number method as an empirical tool for loss estimation

NASA Astrophysics Data System (ADS)

Petroselli, A.; Grimaldi, S.; Romano, N.

2012-12-01

The Soil Conservation Service - Curve Number (SCS-CN) method is a popular rainfall-runoff model widely used to estimate losses and direct runoff from a given rainfall event, but its use is not appropriate at sub-daily time resolution. To overcome this drawback, a mixed procedure, referred to as CN4GA (Curve Number for Green-Ampt), was recently developed including the Green-Ampt (GA) infiltration model and aiming to distribute in time the information provided by the SCS-CN method. The main concept of the proposed mixed procedure is to use the initial abstraction and the total volume given by the SCS-CN to calibrate the Green-Ampt soil hydraulic conductivity parameter. The procedure is here applied on a real case study and a sensitivity analysis concerning the remaining parameters is presented; results show that CN4GA approach is an ideal candidate for the rainfall excess analysis at sub-daily time resolution, in particular for ungauged basin lacking of discharge observations.

Prospective evaluation of a 5 × 4 Gy prescription for palliation of canine nasal tumors.

PubMed

Tan-Coleman, Birgitte; Lyons, Jarred; Lewis, Craig; Rosenberg, Mona; Ruiz, Azucena

2013-01-01

We evaluated the efficacy of palliative radiation therapy using 5 × 4 Gy given daily in 18 dogs with nasal tumors. Dogs with malignant nasal tumors were evaluated for response rate, response duration, and survival. Seventy-eight percent of the dogs achieved complete resolution of clinical signs, and 16.5% had partial resolution of their signs. Overall median response duration for all dogs was 178 days after one course of radiation therapy. Six dogs received a second course of therapy when their disease progressed using the same daily 5 × 4 Gy scheme, and all six responded for a median time of 129.5 days for an overall median survival time in these six dogs of 309 days. Based on these results, a radiation prescription of 5 × 4 Gy appears to be useful palliatively in dogs with a malignant nasal tumor. © 2012 Veterinary Radiology & Ultrasound.

Evaluation of MODIS-Derived Cloud Fraction Using Surface Observations at Low-, Mid- and High Latitude DOE ARM sites

NASA Astrophysics Data System (ADS)

Wang, Yang; Zhao, Chuanfeng

2016-04-01

Clouds play essential roles in the Earth's energy and water cycle, and Cloud Fraction (CF) is one of the most important cloud parameters. The CF from Moderate Resolution Imaging Spectroradiometer (MODIS) has been widely used, whereas the time representation of these instantaneous CF values is not clear. In this study, we evaluate MODIS-derived CF by using continuous, day-and-night radar/lidar CF from the Atmospheric Radiation Measurement (ARM) program Active Remote Sensing of CLouds (ARSCL) product and the total sky cover (TSC) day-time CF datasets. Inter-comparisons between MODIS and surface CFs for time period from 2000 to 2011 are performed for three climate regimes as represented by the ARM sites of Southern Great Plains (SGP), Manus, Papua New Guinea (PNG) and North Slope of Alaska (NSA). We first choose both the TSC and ARSCL CFs averaged over 1 hour around the two passing time of satellite, which are around 10:30 AM and 1:30 PM local time. Then two kind of analyses have been done. One is the spatial variation analysis and the other is temporal variation analysis. For the spatial variation analysis, we compare the 1-hour averaged cloud fractions from TSC and ARSCL around 10:30 AM and 1:30 PM with the instantaneous cloud fractions from MODIS but with different spatial resolution. By obtaining the RMS errors and ratio of average values of CFs for these inter-comparisons, the optimal CF-matching spatial resolutions for MODIS regarding to TSC and ARSCL are obtained which are both 30 km radius of circle. We also find that the optimal matching spatial resolution increases when the ground observation average time increases. For the temporal analysis, we first analyze the diurnal variation of the cloud fraction based on the surface CFs from TSC and ARSCL from which we can see the daily representation of cloud fraction observed at 10:30 AM and 1:30 PM. Then we make a statistical comparison of daily and monthly cloud fraction between using all time observation and using the 1-hour averaged observations at both 10:30 AM and 1:30 PM. Comparison results will be shown in our paper. It shows a high correlation coefficient of 0.95 (0.93) for observations from TSC (ARSCL). The ratios of daily (monthly) averaged cloud fraction between using all time and using the time satellite passes are 0.87(0.92) and 0.86(0.97) for TSC and ARSCL, respectively. This suggests that considerable errors could be introduced while using the cloud fraction at two fixed time points (10:30 AM and 1:30 PM) to represent the daily cloud fraction.

Models for estimating daily rainfall erosivity in China

NASA Astrophysics Data System (ADS)

Xie, Yun; Yin, Shui-qing; Liu, Bao-yuan; Nearing, Mark A.; Zhao, Ying

2016-04-01

The rainfall erosivity factor (R) represents the multiplication of rainfall energy and maximum 30 min intensity by event (EI30) and year. This rainfall erosivity index is widely used for empirical soil loss prediction. Its calculation, however, requires high temporal resolution rainfall data that are not readily available in many parts of the world. The purpose of this study was to parameterize models suitable for estimating erosivity from daily rainfall data, which are more widely available. One-minute resolution rainfall data recorded in sixteen stations over the eastern water erosion impacted regions of China were analyzed. The R-factor ranged from 781.9 to 8258.5 MJ mm ha-1 h-1 y-1. A total of 5942 erosive events from one-minute resolution rainfall data of ten stations were used to parameterize three models, and 4949 erosive events from the other six stations were used for validation. A threshold of daily rainfall between days classified as erosive and non-erosive was suggested to be 9.7 mm based on these data. Two of the models (I and II) used power law functions that required only daily rainfall totals. Model I used different model coefficients in the cool season (Oct.-Apr.) and warm season (May-Sept.), and Model II was fitted with a sinusoidal curve of seasonal variation. Both Model I and Model II estimated the erosivity index for average annual, yearly, and half-month temporal scales reasonably well, with the symmetric mean absolute percentage error MAPEsym ranging from 10.8% to 32.1%. Model II predicted slightly better than Model I. However, the prediction efficiency for the daily erosivity index was limited, with the symmetric mean absolute percentage error being 68.0% (Model I) and 65.7% (Model II) and Nash-Sutcliffe model efficiency being 0.55 (Model I) and 0.57 (Model II). Model III, which used the combination of daily rainfall amount and daily maximum 60-min rainfall, improved predictions significantly, and produced a Nash-Sutcliffe model efficiency for daily erosivity index prediction of 0.93. Thus daily rainfall data was generally sufficient for estimating annual average, yearly, and half-monthly time scales, while sub-daily data was needed when estimating daily erosivity values.

Extracting 5m Shorelines From Multi-Temporal Images

NASA Astrophysics Data System (ADS)

Kapadia, A.; Jordahl, K. A.; Kington, J. D., IV

2016-12-01

Planet operates the largest Earth observing constellation of satellites, collecting imagery at an unprecedented temporal resolution. While daily cadence is expected in early 2017, Planet has already imaged the majority of landmass several dozen times over the past year. The current dataset provides enough value to build and test algorithms to automatically extract information. Here we demonstrate the extraction of shorelines across California using image stacks. The method implemented uses as input an uncalibrated RGB data product and limited NIR combined with the National Land Cover Database 2011 (NLCD2011) and Shuttle Radar Topography Mission (SRTM) to extract shorelines at 5 meter resolution. In the near future these methods along with daily cadence of imagery will allow for temporal monitoring of shorelines on a global scale.

An automated tool for a daily harmful algal bloom monitoring using MODIS imagery downscaled to 250 meters spatial resolution

NASA Astrophysics Data System (ADS)

El Alem, A.

2016-12-01

Harmful algal bloom (HAB) causes negative impacts to other organisms by producing natural toxins, mechanical damage to other micro-organisms, or simply by degrading waters quality. Contaminated waters could expose several billions of population to serious intoxications problems. Traditionally, HAB monitoring is made with standard methods limited to a restricted network of sampling points. However, rapid evolution of HABs makes it difficult to monitor their variation in time and space, threating then public safety. Daily monitoring is then the best way to control and to mitigate their harmful effect upon population, particularly for sources feeding cities. Recently, an approach for estimating chlorophyll-a (Chl-a) concentration, as a proxy of HAB presence, in inland waters based MODIS imagery downscaled to 250 meters spatial resolution was developed. Statistical evaluation of the developed approach highlighted the accuracy of Chl-a estimate with a R2 = 0.98, a relative RMSE of 15%, a relative BIAS of -2%, and a relative NASH of 0.95. Temporal resolution of MODIS sensor allows then a daily monitoring of HAB spatial distribution for inland waters of more than 2.25 Km2 of surface. Groupe-Hemisphere, a company specialized in environmental and sustainable planning in Quebec, has shown a great interest to the developed approach. Given the complexity of the preprocessing (geometric and atmospheric corrections as well as downscaling spatial resolution) and processing (Chl-a estimate) of images, a standalone application under the MATLAB's GUI environment was developed. The application allows an automated process for all preprocessing and processing steps. Outputs produced by the application for end users, many of whom may be decision makers or policy makers in the public and private sectors, allows a near-real time monitoring of water quality for a more efficient management.

A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa

NASA Astrophysics Data System (ADS)

Maidment, Ross I.; Grimes, David; Black, Emily; Tarnavsky, Elena; Young, Matthew; Greatrex, Helen; Allan, Richard P.; Stein, Thorwald; Nkonde, Edson; Senkunda, Samuel; Alcántara, Edgar Misael Uribe

2017-05-01

Rainfall information is essential for many applications in developing countries, and yet, continually updated information at fine temporal and spatial scales is lacking. In Africa, rainfall monitoring is particularly important given the close relationship between climate and livelihoods. To address this information gap, this paper describes two versions (v2.0 and v3.0) of the TAMSAT daily rainfall dataset based on high-resolution thermal-infrared observations, available from 1983 to the present. The datasets are based on the disaggregation of 10-day (v2.0) and 5-day (v3.0) total TAMSAT rainfall estimates to a daily time-step using daily cold cloud duration. This approach provides temporally consistent historic and near-real time daily rainfall information for all of Africa. The estimates have been evaluated using ground-based observations from five countries with contrasting rainfall climates (Mozambique, Niger, Nigeria, Uganda, and Zambia) and compared to other satellite-based rainfall estimates. The results indicate that both versions of the TAMSAT daily estimates reliably detects rainy days, but have less skill in capturing rainfall amount—results that are comparable to the other datasets.

Resolution Enhancement of MODIS-derived Water Indices for Studying Persistent Flooding

NASA Astrophysics Data System (ADS)

Underwood, L. W.; Kalcic, M. T.; Fletcher, R. M.

2012-12-01

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Resolution Enhancement of MODIS-Derived Water Indices for Studying Persistent Flooding

NASA Technical Reports Server (NTRS)

Underwood, L. W.; Kalcic, Maria; Fletcher, Rose

2012-01-01

Monitoring coastal marshes for persistent flooding and salinity stress is a high priority issue in Louisiana. Remote sensing can identify environmental variables that can be indicators of marsh habitat conditions, and offer timely and relatively accurate information for aiding wetland vegetation management. Monitoring activity accuracy is often limited by mixed pixels which occur when areas represented by the pixel encompasses more than one cover type. Mixtures of marsh grasses and open water in 250m Moderate Resolution Imaging Spectroradiometer (MODIS) data can impede flood area estimation. Flood mapping of such mixtures requires finer spatial resolution data to better represent the cover type composition within 250m MODIS pixel. Fusion of MODIS and Landsat can improve both spectral and temporal resolution of time series products to resolve rapid changes from forcing mechanisms like hurricane winds and storm surge. For this study, using a method for estimating sub-pixel values from a MODIS time series of a Normalized Difference Water Index (NDWI), using temporal weighting, was implemented to map persistent flooding in Louisiana coastal marshes. Ordinarily NDWI computed from daily 250m MODIS pixels represents a mixture of fragmented marshes and water. Here, sub-pixel NDWI values were derived for MODIS data using Landsat 30-m data. Each MODIS pixel was disaggregated into a mixture of the eight cover types according to the classified image pixels falling inside the MODIS pixel. The Landsat pixel means for each cover type inside a MODIS pixel were computed for the Landsat data preceding the MODIS image in time and for the Landsat data succeeding the MODIS image. The Landsat data were then weighted exponentially according to closeness in date to the MODIS data. The reconstructed MODIS data were produced by summing the product of fractional cover type with estimated NDWI values within each cover type. A new daily time series was produced using both the reconstructed 250-m MODIS, with enhanced features, and the approximated daily 30-m high-resolution image based on Landsat data. The algorithm was developed and tested over the Calcasieu-Sabine Basin, which was heavily inundated by storm surge from Hurricane Ike to study the extent and duration of flooding following the storm. Time series for 2000-2009, covering flooding events by Hurricane Rita in 2005 and Hurricane Ike in 2008, were derived. High resolution images were formed for all days in 2008 between the first cloud free Landsat scene and the last cloud-free Landsat scene. To refine and validate flooding maps, each time series was compared to Louisiana Coastwide Reference Monitoring System (CRMS) station water levels adjusted to marsh to optimize thresholds for MODIS-derived time series of NDWI. Seasonal fluctuations were adjusted by subtracting ten year average NDWI for marshes, excluding the hurricane events. Results from different NDWI indices and a combination of indices were compared. Flooding persistence that was mapped with higher-resolution data showed some improvement over the original MODIS time series estimates. The advantage of this novel technique is that improved mapping of extent and duration of inundation can be provided.

Rainfall disaggregation for urban hydrology: Effects of spatial consistence

NASA Astrophysics Data System (ADS)

Müller, Hannes; Haberlandt, Uwe

2015-04-01

For urban hydrology rainfall time series with a high temporal resolution are crucial. Observed time series of this kind are very short in most cases, so they cannot be used. On the contrary, time series with lower temporal resolution (daily measurements) exist for much longer periods. The objective is to derive time series with a long duration and a high resolution by disaggregating time series of the non-recording stations with information of time series of the recording stations. The multiplicative random cascade model is a well-known disaggregation model for daily time series. For urban hydrology it is often assumed, that a day consists of only 1280 minutes in total as starting point for the disaggregation process. We introduce a new variant for the cascade model, which is functional without this assumption and also outperforms the existing approach regarding time series characteristics like wet and dry spell duration, average intensity, fraction of dry intervals and extreme value representation. However, in both approaches rainfall time series of different stations are disaggregated without consideration of surrounding stations. This yields in unrealistic spatial patterns of rainfall. We apply a simulated annealing algorithm that has been used successfully for hourly values before. Relative diurnal cycles of the disaggregated time series are resampled to reproduce the spatial dependence of rainfall. To describe spatial dependence we use bivariate characteristics like probability of occurrence, continuity ratio and coefficient of correlation. Investigation area is a sewage system in Northern Germany. We show that the algorithm has the capability to improve spatial dependence. The influence of the chosen disaggregation routine and the spatial dependence on overflow occurrences and volumes of the sewage system will be analyzed.

Merging daily sea surface temperature data from multiple satellites using a Bayesian maximum entropy method

NASA Astrophysics Data System (ADS)

Tang, Shaolei; Yang, Xiaofeng; Dong, Di; Li, Ziwei

2015-12-01

Sea surface temperature (SST) is an important variable for understanding interactions between the ocean and the atmosphere. SST fusion is crucial for acquiring SST products of high spatial resolution and coverage. This study introduces a Bayesian maximum entropy (BME) method for blending daily SSTs from multiple satellite sensors. A new spatiotemporal covariance model of an SST field is built to integrate not only single-day SSTs but also time-adjacent SSTs. In addition, AVHRR 30-year SST climatology data are introduced as soft data at the estimation points to improve the accuracy of blended results within the BME framework. The merged SSTs, with a spatial resolution of 4 km and a temporal resolution of 24 hours, are produced in the Western Pacific Ocean region to demonstrate and evaluate the proposed methodology. Comparisons with in situ drifting buoy observations show that the merged SSTs are accurate and the bias and root-mean-square errors for the comparison are 0.15°C and 0.72°C, respectively.

What is the effect of LiDAR-derived DEM resolution on large-scale watershed model results?

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

Ping Yang; Daniel B. Ames; Andre Fonseca

This paper examines the effect of raster cell size on hydrographic feature extraction and hydrological modeling using LiDAR derived DEMs. LiDAR datasets for three experimental watersheds were converted to DEMs at various cell sizes. Watershed boundaries and stream networks were delineated from each DEM and were compared to reference data. Hydrological simulations were conducted and the outputs were compared. Smaller cell size DEMs consistently resulted in less difference between DEM-delineated features and reference data. However, minor differences been found between streamflow simulations resulted for a lumped watershed model run at daily simulations aggregated at an annual average. These findings indicatemore » that while higher resolution DEM grids may result in more accurate representation of terrain characteristics, such variations do not necessarily improve watershed scale simulation modeling. Hence the additional expense of generating high resolution DEM's for the purpose of watershed modeling at daily or longer time steps may not be warranted.« less

Intraseasonal to interannual variability of Kelvin wave momentum fluxes as derived from high-resolution radiosonde data

DOE PAGES

Sjoberg, Jeremiah P.; Birner, Thomas; Johnson, Richard H.

2017-07-26

Observational estimates of Kelvin wave momentum fluxes in the tropical lower stratosphere remain challenging. Here we extend a method based on linear wave theory to estimate daily time series of these momentum fluxes from high-resolution radiosonde data. Daily time series are produced for sounding sites operated by the US Department of Energy (DOE) and from the recent Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign. Our momentum flux estimates are found to be robust to different data sources and processing and in quantitative agreement with estimates from prior studies. Testing the sensitivity to vertical resolution, our estimated momentum fluxes aremore » found to be most sensitive to vertical resolution greater than 1 km, largely due to overestimation of the vertical wavelength. Climatological analysis is performed over a selected 11-year span of data from DOE Atmospheric Radiation Measurement (ARM) radiosonde sites. Analyses of this 11-year span of data reveal the expected seasonal cycle of momentum flux maxima in boreal winter and minima in boreal summer, and variability associated with the quasi-biennial oscillation of maxima during easterly phase and minima during westerly phase. Comparison between periods with active convection that is either strongly or weakly associated with the Madden–Julian Oscillation (MJO) suggests that the MJO provides a nontrivial increase in the lowermost stratospheric momentum fluxes.« less

Enhancing the temporal resolution of satellite-based flood extent generation using crowdsourced data for disaster monitoring.

NASA Astrophysics Data System (ADS)

Panteras, G.; Cervone, G.

2016-12-01

Satellite-based disaster monitoring has been extensively and successfully used for numerous crisis response and impact delineation tasks until nowadays. Remote sensing satellite are routinely used data during disasters for damage assessment and to coordinate relief operations. Although there is a plethora of satellite sensors able to provide actionable data about an event, their temporal resolution is limited by the satellite revisit time and the presence of clouds. These limitations do not allow for an uninterrupted and timely sensitive monitoring, which is crucial during disasters and emergencies. This research presents an approach that leverages the increased temporal resolution of crowdsourced data to partially overcame the limitations of satellite data. The proposed approach focuses on the geostatistical analysis of Tweeter data to help delineate the flood extent on a daily basis. The crowdsourced data are used to augment satellite imagery from EO-1 ALI, Landsat 8, WorldView-2 and WorldView-3 by fusing them together to complement the satellite observations. The proposed methodology was applied to estimate the daily flood extents in Charleston, SC, caused by hurricane Joaquin on October 2015. The results of the proposed methodology indicate that the user-generated data can be utilized adequately to both bridge the temporal gaps in the satellite-based observations and also to increase the spatial resolution of the flood extents.

Glacier Melt Detection in Complex Terrain Using New AMSR-E Calibrated Enhanced Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record

NASA Astrophysics Data System (ADS)

Ramage, J. M.; Brodzik, M. J.; Hardman, M.

2016-12-01

Passive microwave (PM) 18 GHz and 36 GHz horizontally- and vertically-polarized brightness temperatures (Tb) channels from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) have been important sources of information about snow melt status in glacial environments, particularly at high latitudes. PM data are sensitive to the changes in near-surface liquid water that accompany melt onset, melt intensification, and refreezing. Overpasses are frequent enough that in most areas multiple (2-8) observations per day are possible, yielding the potential for determining the dynamic state of the snow pack during transition seasons. AMSR-E Tb data have been used effectively to determine melt onset and melt intensification using daily Tb and diurnal amplitude variation (DAV) thresholds. Due to mixed pixels in historically coarse spatial resolution Tb data, melt analysis has been impractical in ice-marginal zones where pixels may be only fractionally snow/ice covered, and in areas where the glacier is near large bodies of water: even small regions of open water in a pixel severely impact the microwave signal. We use the new enhanced-resolution Calibrated Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record product's twice daily obserations to test and update existing snow melt algorithms by determining appropriate melt thresholds for both Tb and DAV for the CETB 18 and 36 GHz channels. We use the enhanced resolution data to evaluate melt characteristics along glacier margins and melt transition zones during the melt seasons in locations spanning a wide range of melt scenarios, including the Patagonian Andes, the Alaskan Coast Range, and the Russian High Arctic icecaps. We quantify how improvement of spatial resolution from the original 12.5 - 25 km-scale pixels to the enhanced resolution of 3.125 - 6.25 km improves the ability to evaluate melt timing across boundaries and transition zones in diverse glacial environments.

Mapping Daily Evapotranspiration based on Spatiotemporal Fusion of ASTER and MODIS Images over Irrigated Agricultural Areas in the Heihe River Basin, Northwest China

NASA Astrophysics Data System (ADS)

Huang, C.; LI, Y.

2017-12-01

Continuous monitoring of daily evapotranspiration (ET) is crucial for allocating and managing water resources in irrigated agricultural areas in arid regions. In this study, continuous daily ET at a 90-m spatial resolution was estimated using the Surface Energy Balance System (SEBS) by fusing Moderate Resolution Imaging Spectroradiometer (MODIS) images with high temporal resolution and Advanced Space-borne Thermal Emission Reflectance Radiometer (ASTER) images with high spatial resolution. The spatiotemporal characteristics of these sensors were obtained using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The performance of this approach was validated over a heterogeneous oasis-desert region covered by cropland, residential, woodland, water, Gobi desert, sandy desert, desert steppe, and wetland areas using in situ observations from automatic meteorological systems (AMS) and eddy covariance (EC) systems in the middle reaches of the Heihe River Basin in Northwest China. The error introduced during the data fusion process based on STARFM is within an acceptable range for predicted LST at a 90-m spatial resolution. The surface energy fluxes estimated using SEBS based on predicted remotely sensed data that combined the spatiotemporal characteristics of MODIS and ASTER agree well with the surface energy fluxes observed using EC systems for all land cover types, especially for vegetated area with MAP values range from 9% to 15%, which are less than the uncertainty (18%) of the observed in this study area. Time series of daily ET modelled from SEBS were compared to that modelled from PT-JPL (one of Satellite-based Priestley-Taylor ET model) and observations from EC systems. SEBS performed generally better than PT-JPL for vegetated area, especially irrigated cropland with bias, RMSE, and MAP values of 0.29 mm/d, 0.75 mm/d, 13% at maize site, -0.33 mm/d, 0.81 mm/d, and 14% at vegetable sites.

Effects of Real-Time NASA Vegetation Data on Model Forecasts of Severe Weather

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Bell, Jordan R.; LaFontaine, Frank J.; Peters-Lidard, Christa D.

2012-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the other uses the daily SPoRT/MODIS GVFs. Finally, snapshots of the LIS land surface fields are used to initialize two different simulations of the NU-WRF, one running with climatology LIS and GVFs, and the other running with experimental LIS and NASA/SPoRT GVFs. In this paper/presentation, case study results will be highlighted in regions with significant differences in GVF between the NCEP climatology and SPoRT product during severe weather episodes.

A daily Azores-Iceland North Atlantic Oscillation index back to 1850.

PubMed

Cropper, Thomas; Hanna, Edward; Valente, Maria Antónia; Jónsson, Trausti

2015-07-01

We present the construction of a continuous, daily (09:00 UTC), station-based (Azores-Iceland) North Atlantic Oscillation (NAO) Index back to 1871 which is extended back to 1850 with additional daily mean data. The constructed index more than doubles the length of previously existing, widely available, daily NAO time series. The index is created using entirely observational sea-level pressure (SLP) data from Iceland and 73.5% of observational SLP data from the Azores - the remainder being filled in via reanalysis (Twentieth Century Reanalysis Project and European Mean Sea Level Pressure) SLP data. Icelandic data are taken from the Southwest Iceland pressure series. We construct and document a new Ponta Delgada SLP time series based on recently digitized and newly available data that extend back to 1872. The Ponta Delgada time series is created by splicing together several fractured records (from Ponta Delgada, Lajes, and Santa Maria) and filling in the major gaps (pre-1872, 1888-1905, and 1940-1941) and occasional days (145) with reanalysis data. Further homogeneity corrections are applied to the Azores record, and the daily (09:00 UTC) NAO index is then calculated. The resulting index, with its extended temporal length and daily resolution, is the first reconstruction of daily NAO back into the 19th Century and therefore is useful for researchers across multiple disciplines.

Fast 3D Surface Extraction 2 pages (including abstract)

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

Sewell, Christopher Meyer; Patchett, John M.; Ahrens, James P.

Ocean scientists searching for isosurfaces and/or thresholds of interest in high resolution 3D datasets required a tedious and time-consuming interactive exploration experience. PISTON research and development activities are enabling ocean scientists to rapidly and interactively explore isosurfaces and thresholds in their large data sets using a simple slider with real time calculation and visualization of these features. Ocean Scientists can now visualize more features in less time, helping them gain a better understanding of the high resolution data sets they work with on a daily basis. Isosurface timings (512{sup 3} grid): VTK 7.7 s, Parallel VTK (48-core) 1.3 s, PISTONmore » OpenMP (48-core) 0.2 s, PISTON CUDA (Quadro 6000) 0.1 s.« less

Parameterization of water vapor using high-resolution GPS data and empirical models

NASA Astrophysics Data System (ADS)

Ningombam, Shantikumar S.; Jade, Sridevi; Shrungeshwara, T. S.

2018-03-01

The present work evaluates eleven existing empirical models to estimate Precipitable Water Vapor (PWV) over a high-altitude (4500 m amsl), cold-desert environment. These models are tested extensively and used globally to estimate PWV for low altitude sites (below 1000 m amsl). The moist parameters used in the model are: water vapor scale height (Hc), dew point temperature (Td) and water vapor pressure (Es 0). These moist parameters are derived from surface air temperature and relative humidity measured at high temporal resolution from automated weather station. The performance of these models are examined statistically with observed high-resolution GPS (GPSPWV) data over the region (2005-2012). The correlation coefficient (R) between the observed GPSPWV and Model PWV is 0.98 at daily data and varies diurnally from 0.93 to 0.97. Parameterization of moisture parameters were studied in-depth (i.e., 2 h to monthly time scales) using GPSPWV , Td , and Es 0 . The slope of the linear relationships between GPSPWV and Td varies from 0.073°C-1 to 0.106°C-1 (R: 0.83 to 0.97) while GPSPWV and Es 0 varied from 1.688 to 2.209 (R: 0.95 to 0.99) at daily, monthly and diurnal time scales. In addition, the moist parameters for the cold desert, high-altitude environment are examined in-depth at various time scales during 2005-2012.

Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Salomonson, Vincent V.; Riggs, George A.; Klein, Andrew G.

2003-01-01

Snow and sea ice products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, flown on the Terra and Aqua satellites, are or will be available through the National Snow and Ice Data Center Distributed Active Archive Center (DAAC). The algorithms that produce the products are automated, thus providing a consistent global data set that is suitable for climate studies. The suite of MODIS snow products begins with a 500-m resolution, 2330-km swath snow-cover map that is then projected onto a sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to daily and 8-day composite climate-modeling grid (CMG) products at 0.05 resolution. A daily snow albedo product will be available in early 2003 as a beta test product. The sequence of sea ice products begins with a swath product at 1-km resolution that provides sea ice extent and ice-surface temperature (IST). The sea ice swath products are then mapped onto the Lambert azimuthal equal area or EASE-Grid projection to create a daily and 8-day composite sea ice tile product, also at 1 -km resolution. Climate-Modeling Grid (CMG) sea ice products in the EASE-Grid projection at 4-km resolution are planned for early 2003.

VizieR Online Data Catalog: The Fermi-GBM three-year X-ray burst catalog (Jenke+, 2016)

NASA Astrophysics Data System (ADS)

Jenke, P. A.; Linares, M.; Connaughton, V.; Beklen, E.; Camero-Arranz, A.; Finger, M. H.; Wilson-Hodge, C. A.

2018-03-01

Gamma-ray Burst Monitor (GBM) is an all-sky monitor whose primary objective is to extend the energy range over which gamma-ray bursts are observed in the Large Area Telescope on Fermi (Meegan et al. 2009ApJ...702..791M). GBM consists of 12 NaI detectors with a diameter of 12.7 cm and a thickness of 1.27 cm and two bismuth germanate (BGO) detectors with a diameter and thickness of 12.7 cm. GBM has three continuous data types: CTIME data with nominal 0.256 s time resolution and 8-channel spectral resolution used for event detection and localization, CSPEC data with nominal 4.096 s time resolution and 128-channel spectral resolution, which are used for spectral modeling, and CTTE (continuous-time tagged event) data with time stamps (2 μs precision) on individual events at full 128-channel spectral resolution, which were made available in 2012 November. The Fermi-GBM X-ray Burst Monitor relies on daily inspection of CTIME channel 1 (12-25 keV) data and began operations on 2010 March 12. (3 data files).

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

NASA Astrophysics Data System (ADS)

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; Kotamarthi, V. Rao

2017-12-01

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary conditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045-2054 and 2085-2094) are compared with a historical decade (1995-2004). Probability density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5-10 times per year in most CONUS and ≥95°F days will increase by 1-2 months by the end of the century.

A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa

PubMed Central

Maidment, Ross I.; Grimes, David; Black, Emily; Tarnavsky, Elena; Young, Matthew; Greatrex, Helen; Allan, Richard P.; Stein, Thorwald; Nkonde, Edson; Senkunda, Samuel; Alcántara, Edgar Misael Uribe

2017-01-01

Rainfall information is essential for many applications in developing countries, and yet, continually updated information at fine temporal and spatial scales is lacking. In Africa, rainfall monitoring is particularly important given the close relationship between climate and livelihoods. To address this information gap, this paper describes two versions (v2.0 and v3.0) of the TAMSAT daily rainfall dataset based on high-resolution thermal-infrared observations, available from 1983 to the present. The datasets are based on the disaggregation of 10-day (v2.0) and 5-day (v3.0) total TAMSAT rainfall estimates to a daily time-step using daily cold cloud duration. This approach provides temporally consistent historic and near-real time daily rainfall information for all of Africa. The estimates have been evaluated using ground-based observations from five countries with contrasting rainfall climates (Mozambique, Niger, Nigeria, Uganda, and Zambia) and compared to other satellite-based rainfall estimates. The results indicate that both versions of the TAMSAT daily estimates reliably detects rainy days, but have less skill in capturing rainfall amount—results that are comparable to the other datasets. PMID:28534868

Integrated satellite data fusion and mining for monitoring lake water quality status of the Albufera de Valencia in Spain.

PubMed

Doña, Carolina; Chang, Ni-Bin; Caselles, Vicente; Sánchez, Juan M; Camacho, Antonio; Delegido, Jesús; Vannah, Benjamin W

2015-03-15

Lake eutrophication is a critical issue in the interplay of water supply, environmental management, and ecosystem conservation. Integrated sensing, monitoring, and modeling for a holistic lake water quality assessment with respect to multiple constituents is in acute need. The aim of this paper is to develop an integrated algorithm for data fusion and mining of satellite remote sensing images to generate daily estimates of some water quality parameters of interest, such as chlorophyll a concentrations and water transparency, to be applied for the assessment of the hypertrophic Albufera de Valencia. The Albufera de Valencia is the largest freshwater lake in Spain, which can often present values of chlorophyll a concentration over 200 mg m(-3) and values of transparency (Secchi Disk, SD) as low as 20 cm. Remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat Thematic Mapper (TM) and Enhance Thematic Mapper (ETM+) images were fused to carry out an integrative near-real time water quality assessment on a daily basis. Landsat images are useful to study the spatial variability of the water quality parameters, due to its spatial resolution of 30 m, in comparison to the low spatial resolution (250/500 m) of MODIS. While Landsat offers a high spatial resolution, the low temporal resolution of 16 days is a significant drawback to achieve a near real-time monitoring system. This gap may be bridged by using MODIS images that have a high temporal resolution of 1 day, in spite of its low spatial resolution. Synthetic Landsat images were fused for dates with no Landsat overpass over the study area. Finally, with a suite of ground truth data, a few genetic programming (GP) models were derived to estimate the water quality using the fused surface reflectance data as inputs. The GP model for chlorophyll a estimation yielded a R(2) of 0.94, with a Root Mean Square Error (RMSE) = 8 mg m(-3), and the GP model for water transparency estimation using Secchi disk showed a R(2) of 0.89, with an RMSE = 4 cm. With this effort, the spatiotemporal variations of water transparency and chlorophyll a concentrations may be assessed simultaneously on a daily basis throughout the lake for environmental management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spatiotemporal Variability of Drought in Pakistan through High-Resolution Daily Gridded In-Situ Observations

NASA Astrophysics Data System (ADS)

Bashir, F.; Zeng, X.; Gupta, H. V.; Hazenberg, P.

2017-12-01

Drought as an extreme event may have far reaching socio-economic impacts on agriculture based economies like Pakistan. Effective assessment of drought requires high resolution spatiotemporally continuous hydrometeorological information. For this purpose, new in-situ daily observations based gridded analyses of precipitation, maximum, minimum and mean temperature and diurnal temperature range are developed, that covers whole Pakistan on 0.01º latitude-longitude for a 54-year period (1960-2013). The number of participating meteorological observatories used in these gridded analyses is 2 to 6 times greater than any other similar product available. This data set is used to identify extreme wet and dry periods and their spatial patterns across Pakistan using Palmer Drought Severity Index (PDSI) and Standardized Precipitation Index (SPI). Periodicity of extreme events is estimated at seasonal to decadal scales. Spatiotemporal signatures of drought incidence indicating its extent and longevity in different areas may help water resource managers and policy makers to mitigate the severity of the drought and its impact on food security through suitable adaptive techniques. Moreover, this high resolution gridded in-situ observations of precipitation and temperature is used to evaluate other coarser-resolution gridded products.

Comparison of Land Surface Phenology Detections from Geostationary (AHI) and Polar-orbiting (VIIRS) Sensors in Tropical Southeast Asia

NASA Astrophysics Data System (ADS)

Liu, L.; Zhang, X.

2017-12-01

Land surface phenology (LSP) is an important indicator of ecosystem response to global change and reflects the exchange of water, energy, and carbon between the land surface and the atmosphere. However, the extraction of LSP in tropical Southeast Asia is very challenging due to weak seasonal variation and frequent cloud commination during the vegetation growing season. The successful launch of Advanced Himawari Imager (AHI) onboard Himawari-8 geostationary satellite in October 2014 provides large opportunities to obtain cloud-free observations in daily time series data because it collects data every 10 minutes at a spatial resolution of 500m-2000 m. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard operational Suomi National Polar-orbiting Partnership (Suomi NPP) satellite provides global moderate-resolution (375-750 m) data once every day. To compare the capability of AHI and VIIRS observations to monitor LSP in frequently-cloud-covered tropical Southeast Asia, this research first extracted LSP metrics based on the time series of daily two-band enhanced vegetation index (EVI2) from AHI and VIIRS using a hybrid piecewise logistic model in 2015 and 2016. The daily AHI EVI2 was calculated from diurnal observations after EVI2 at every 10 minutes was angularly corrected using an empirical kernel-driven model to eliminate the effect caused by the varying sun-satellite geometry. Subsequently, we compared the phenological transition dates of greenup onset and dormancy onset retrieved from AHI and VIIRS data at both pixel level and country level. Finally, we assessed the influences of the quality of daily observation from AHI and VIIRS on the reconstruction of EVI2 time series and the retrievals of phenological dates.

From daily to sub-daily time steps - Creating a high temporal and spatial resolution climate reference data set for hydrological modeling and bias-correction of RCM data

NASA Astrophysics Data System (ADS)

Willkofer, Florian; Wood, Raul R.; Schmid, Josef; von Trentini, Fabian; Ludwig, Ralf

2016-04-01

The ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) focuses on the effects of climate change on hydro-meteorological extreme events and their implications for water management in Bavaria and Québec. It builds on the conjoint analysis of a large ensemble of the CRCM5, driven by 50 members of the CanESM2, and the latest information provided through the CORDEX-initiative, to better assess the influence of natural climate variability and climatic change on the dynamics of extreme events. A critical point in the entire project is the preparation of a meteorological reference dataset with the required temporal (1-6h) and spatial (500m) resolution to be able to better evaluate hydrological extreme events in mesoscale river basins. For Bavaria a first reference data set (daily, 1km) used for bias-correction of RCM data was created by combining raster based data (E-OBS [1], HYRAS [2], MARS [3]) and interpolated station data using the meteorological interpolation schemes of the hydrological model WaSiM [4]. Apart from the coarse temporal and spatial resolution, this mosaic of different data sources is considered rather inconsistent and hence, not applicable for modeling of hydrological extreme events. Thus, the objective is to create a dataset with hourly data of temperature, precipitation, radiation, relative humidity and wind speed, which is then used for bias-correction of the RCM data being used as driver for hydrological modeling in the river basins. Therefore, daily data is disaggregated to hourly time steps using the 'Method of fragments' approach [5], based on available training stations. The disaggregation chooses fragments of daily values from observed hourly datasets, based on similarities in magnitude and behavior of previous and subsequent events. The choice of a certain reference station (hourly data, provision of fragments) for disaggregating daily station data (application of fragments) is crucial and several methods will be tested to achieve a profound spatial interpolation. This entire methodology shall be applicable for existing or newly developed datasets. References [1] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres) (2008), 113, D20119, doi:10.1029/2008JD10201. [2] Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A. and A. Gratzki. A Central European precipitation climatology - Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS). Meteorologische Zeitschrift (2013), 22/3, p.238-256. [3] MARS-AGRI4CAST. AGRI4CAST Interpolated Meteorological Data. http://mars.jrc.ec.europa.eu/mars/ About-us/AGRI4CAST/Data-distribution/AGRI4CAST-Interpolated-Meteorological-Data. 2007, last accessed May 10th, 2013. [4] Schulla, J. Model Description WaSiM - Water balance Simulation Model. 2015, available at: http://wasim.ch/en/products/wasim_description.htm. [5] Sharma, A. and S. Srikanthan. Continuous Rainfall Simulation: A Nonparametric Alternative. 30th Hydrology and Water Resources Symposium, Launceston, Tasmania, 4-7 December, 2006.

Scale appropriate modelling to represent dominant pollution processes in agricultural catchments, to underpin management and policy decisions

NASA Astrophysics Data System (ADS)

Adams, Russell; Quinn, Paul

2014-05-01

We present the development of scale appropriate modelling techniques to represent dominant pollution processes in agricultural catchments to underpin catchment management and its implications on policy. A quasi-physically based, spatially lumped macro-model (CRAFT), has been developed to assess mitigation options for nitrogen and phosphorus. CRAFT has been developed to use daily time series data of rainfall, stream flow and nutrient concentration data, and can be applied to catchments varying in size from a few hectares to 100s of square kilometres. If stream flow routing is added to the model then potentially larger catchments and sub-daily time steps could be represented. There are two key issues addressed here. Firstly, the model can be used to assess the usefulness of monitoring data collected at a high temporal resolution at considerable expense compared to routine grab sampling. An earlier study in the Frome catchment in southern England collected sub-daily water quality data for more than 12 months at the catchment outlet, comprising: total oxidised nitrogen (TON); soluble reactive phosphorus (SRP) and total phosphorus (TP) concentrations. The three data sets have quite different temporal signals relating to flow pathways with different residence times and the importance of runoff events in generating acute pollution. The flexible model structure was therefore developed to include different sources of runoff including overland flow from impervious areas in the catchment, where pollution hotspots will be located (e.g. farmyards). The model has been used to assess the value of collecting high resolution monitoring data, in this case by resampling the Frome sub-daily data to a daily timestep, and comparing these model simulations against those calibrated using all the samples. The usefulness of the high resolution data can be assessed on whether a daily model would undepredict (for example) high nutrient concentrations that can be identified in the sub-daily monitoring data. Secondly, the study aims to investigate the mitigation measures that can be used to address the catchment scale sources of N and P, under EU or other governmental legislation designed to reduce their loads. In a complex catchment like the Frome, the mitigation measures are likely to target both point and non-point sources, particularly of SRP (e.g. wastewater treatment plant discharges and soluble fertilizer applications respectively). For a modelling tool to be useful to land holders and policy makers, it is imperative that these stakeholders can investigate different scenarios by easily manipulating the model input parameters, e.g. by reducing the diffuse sources of SRP and TON (by parameter adjustment), or modifying flow pathways through runoff attenuation (e.g. reducing runoff from farmyards), and the model structure reflects this functionality allowing it to be used as a runoff attenuation tool.

High resolution power spectra of daily Zurich sunspot numbers

NASA Technical Reports Server (NTRS)

Euler, H. C., Jr.

1973-01-01

High resolution power spectra of 77 years of Zurich daily sunspot numbers were computed using various lags and data point intervals. Major harmonic peaks of the approximately 124-month period showed up strongly as well as the 27-day solar rotational period.

Operational use of high-resolution sst in a coupled sea ice-ocean model

NASA Astrophysics Data System (ADS)

Albretsen, A.

2003-04-01

A high-latitude, near real time, sea surface temperature (SST) product with 10 km resolution is developed at the Norwegian Meteorological Institute (met.no) through the EUMETSAT project OSI-SAF (Ocean and Sea Ice Satellite Application Facility). The product covers the Atlantic Ocean from 50N to 90N and is produced twice daily. A digitized SST and sea ice map is produced manually once a week at the Ice Mapping Service at met.no using all available information from the previous week. This map is the basis for a daily SST analysis, in which the most recent OSI-SAF SST products are successively overlaid. The resulting SST analysis field is then used in a simple data assimilation scheme in a coupled ice-ocean model to perform daily 10 days forecasts of ocean and sea ice variables. Also, the associated OSI-SAF sea ice concentration product, built from different polar orbiting satellites, is assimilated into the sea ice model. Preliminary estimates of impact on forecast skill and error statistics will be presented.

The Daily Readiness Huddle: a process to rapidly identify issues and foster improvement through problem-solving accountability.

PubMed

Donnelly, Lane F; Cherian, Shirley S; Chua, Kimberly B; Thankachan, Sam; Millecker, Laura A; Koroll, Alex G; Bisset, George S

2017-01-01

Because of the increasing complexities of providing imaging for pediatric health care services, a more reliable process to manage the daily delivery of care is necessary. Objective We describe our Daily Readiness Huddle and the effects of the process on problem identification and improvement. Our Daily Readiness Huddle has four elements: metrics review, clinical volume review, daily readiness assessment, and problem accountability. It is attended by radiologists, directors, managers, front-line staff with concerns, representatives from support services (information technology [IT] and biomedical engineering [biomed]), and representatives who join the meeting in a virtual format from off-site locations. Data are visually displayed on erasable whiteboards. The daily readiness assessment uses queues to determine whether anyone has concerns or outlier data in regard to S-MESA (Safety, Methods, Equipment, Supplies or Associates). Through this assessment, problems are identified and categorized as quick hits (will be resolved in 24-48 h, not requiring project management) and complex issues. Complex issues are assigned an owner, quality coach and report-back date. Additionally, projects are defined as improvements that are often strategic, are anticipated to take more than 60 days, and do not necessarily arise out of identified issues during the Daily Readiness Huddle. We tracked and calculated the mean, median and range of days to resolution and completion for complex issues and for projects during the first full year of implementing this process. During the first 12 months, 91 complex issues were identified and resolved, 11 projects were in progress and 33 completed, with 23 other projects active or in planning. Time to resolution of complex issues (in days) was mean 37.5, median 34.0, and range 1-105. For projects, time to completion (in days) was mean 86.0, median 84.0, and range 5-280. The Daily Readiness Huddle process has given us a framework to rapidly identify issues, bring accountability to problem-solving, and foster improvement. It has also had a positive effect on team-building and coordination.

Integrated approach using multi-platform sensors for enhanced high-resolution daily ice cover product

NASA Astrophysics Data System (ADS)

Bonev, George; Gladkova, Irina; Grossberg, Michael; Romanov, Peter; Helfrich, Sean

2016-09-01

The ultimate objective of this work is to improve characterization of the ice cover distribution in the polar areas, to improve sea ice mapping and to develop a new automated real-time high spatial resolution multi-sensor ice extent and ice edge product for use in operational applications. Despite a large number of currently available automated satellite-based sea ice extent datasets, analysts at the National Ice Center tend to rely on original satellite imagery (provided by satellite optical, passive microwave and active microwave sensors) mainly because the automated products derived from satellite optical data have gaps in the area coverage due to clouds and darkness, passive microwave products have poor spatial resolution, automated ice identifications based on radar data are not quite reliable due to a considerable difficulty in discriminating between the ice cover and rough ice-free ocean surface due to winds. We have developed a multisensor algorithm that first extracts maximum information on the sea ice cover from imaging instruments VIIRS and MODIS, including regions covered by thin, semitransparent clouds, then supplements the output by the microwave measurements and finally aggregates the results into a cloud gap free daily product. This ability to identify ice cover underneath thin clouds, which is usually masked out by traditional cloud detection algorithms, allows for expansion of the effective coverage of the sea ice maps and thus more accurate and detailed delineation of the ice edge. We have also developed a web-based monitoring system that allows comparison of our daily ice extent product with the several other independent operational daily products.

Gridded precipitation fields at high temporal and spatial resolution for operational flood forecasting in the Rhine basin

NASA Astrophysics Data System (ADS)

van Osnabrugge, Bart; Weerts, Albrecht; Uijlenhoet, Remko

2017-04-01

Gridded areal precipitation, as one of the most important hydrometeorological input variables for initial state estimation in operational hydrological forecasting, is available in the form of raster data sets (e.g. HYRAS and EOBS) for the River Rhine basin. These datasets are compiled off-line on a daily time step using station data with the highest possible spatial density. However, such a product is not available operationally and at an hourly discretisation. Therefore, we constructed an hourly gridded precipitation dataset at 1.44 km2 resolution for the Rhine basin for the period from 1998 to present using a REGNIE-like interpolation procedure (Weerts et al., 2008) using a low and a high density rain gauge network. The datasets were validated against daily HYRAS (Rauthe, 2013) and EOBS (Haylock, 2008) data. The main goal of the operational procedure is to emulate the HYRAS dataset as good as possible, as the daily HYRAS dataset is used in the off-line calibration of the hydrological model. Our main findings are that even with low station density, the spatial patterns found in the HYRAS data set are well reproduced. With low station density (years 1999-2006) our dataset underestimates precipitation compared to HYRAS and EOBS, notably during the winter. However, interpolation based on the same set of stations overestimates precipitation compared to EOBS for the years 2006-2014. This discrepancy disappears when switching to the high station density. We also analyze the robustness of the hourly precipitation fields by comparing with stations not used during interpolation. Specific issues regarding the data when creating the gridded precipitation fields will be highlighted. Finally, the datasets are used to drive an hourly and daily gridded WFLOW_HBV model of the Rhine at the same spatial resolution. Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, doi:10.1029/2008JD10201 Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A., Gratzki, A. 2013: A Central European precipitation climatology - Part 1: Generation and validation of a high-resolution gridded daily data set (HYRAS). Meteorologische Zeitschrift, 22(3), 235 256 Weerts, A.H., D. Meißner, and S. Rademacher, 2008. Input data rainfall-runoff model operational system FEWS-NL & FEWS-DE. Technical report, Deltares.

Daily Management System of the Henry Ford Production System: QTIPS to Focus Continuous Improvements at the Level of the Work.

PubMed

Zarbo, Richard J; Varney, Ruan C; Copeland, Jacqueline R; D'Angelo, Rita; Sharma, Gaurav

2015-07-01

To support our Lean culture of continuous improvement, we implemented a daily management system designed so critical metrics of operational success were the focus of local teams to drive improvements. We innovated a standardized visual daily management board composed of metric categories of Quality, Time, Inventory, Productivity, and Safety (QTIPS); frequency trending; root cause analysis; corrective/preventive actions; and resulting process improvements. In 1 year (June 2013 to July 2014), eight laboratory sections at Henry Ford Hospital employed 64 unique daily metrics. Most assessed long-term (>6 months), monitored process stability, while short-term metrics (1-6 months) were retired after successful targeted problem resolution. Daily monitoring resulted in 42 process improvements. Daily management is the key business accountability subsystem that enabled our culture of continuous improvement to function more efficiently at the managerial level in a visible manner by reviewing and acting based on data and root cause analysis. Copyright© by the American Society for Clinical Pathology.

Effects of daily, high spatial resolution a priori profiles of satellite-derived NOx emissions

NASA Astrophysics Data System (ADS)

Laughner, J.; Zare, A.; Cohen, R. C.

2016-12-01

The current generation of space-borne NO2 column observations provides a powerful method of constraining NOx emissions due to the spatial resolution and global coverage afforded by the Ozone Monitoring Instrument (OMI). The greater resolution available in next generation instruments such as TROPOMI and the capabilities of geosynchronous platforms TEMPO, Sentinel-4, and GEMS will provide even greater capabilities in this regard, but we must apply lessons learned from the current generation of retrieval algorithms to make the best use of these instruments. Here, we focus on the effect of the resolution of the a priori NO2 profiles used in the retrieval algorithms. We show that for an OMI retrieval, using daily high-resolution a priori profiles results in changes in the retrieved VCDs up to 40% when compared to a retrieval using monthly average profiles at the same resolution. Further, comparing a retrieval with daily high spatial resolution a priori profiles to a more standard one, we show that emissions derived increase by 100% when using the optimized retrieval.

All the stereotypes confirmed: differences in how Australian boys and girls use their time.

PubMed

Ferrar, Katia E; Olds, Tim S; Walters, Julie L

2012-10-01

To influence adolescent health, a greater understanding of time use and covariates such as gender is required. To explore gender-specific time use patterns in Australian adolescents using high-resolution time use data. This study analyzed 24-hour recall time use data collected as part of the 2007 Australian National Children's Nutrition and Physical Activity Survey (n = 2,200). Univariate analyses to determine gender differences in time use were conducted. Boys spent more (p < .0001) time participating in screen-based (17.7 % vs. 14.2% daily time) and physical activities (10.7% vs. 9.2%). Girls spent more (p < .0001) time being social (4.7% vs. 3.4% daily time), studying (2.0% vs. 1.7%), and doing household chores (4.7% vs. 3.4%). There are gender-specific differences in time use behavior among Australian adolescents. The results reinforce existing time use gender-based stereotypes. Implications. The gender-specific time use behaviors offer intervention design possibilities.

Merging climate and multi-sensor time-series data in real-time drought monitoring across the U.S.A.

USGS Publications Warehouse

Brown, Jesslyn F.; Miura, T.; Wardlow, B.; Gu, Yingxin

2011-01-01

Droughts occur repeatedly in the United States resulting in billions of dollars of damage. Monitoring and reporting on drought conditions is a necessary function of government agencies at multiple levels. A team of Federal and university partners developed a drought decision- support tool with higher spatial resolution relative to traditional climate-based drought maps. The Vegetation Drought Response Index (VegDRI) indicates general canopy vegetation condition assimilation of climate, satellite, and biophysical data via geospatial modeling. In VegDRI, complementary drought-related data are merged to provide a comprehensive, detailed representation of drought stress on vegetation. Time-series data from daily polar-orbiting earth observing systems [Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS)] providing global measurements of land surface conditions are ingested into VegDRI. Inter-sensor compatibility is required to extend multi-sensor data records; thus, translations were developed using overlapping observations to create consistent, long-term data time series. 

Assessing the capability of different satellite observing configurations to resolve the distribution of methane emissions at kilometer scales

NASA Astrophysics Data System (ADS)

Turner, Alexander J.; Jacob, Daniel J.; Benmergui, Joshua; Brandman, Jeremy; White, Laurent; Randles, Cynthia A.

2018-06-01

Anthropogenic methane emissions originate from a large number of fine-scale and often transient point sources. Satellite observations of atmospheric methane columns are an attractive approach for monitoring these emissions but have limitations from instrument precision, pixel resolution, and measurement frequency. Dense observations will soon be available in both low-Earth and geostationary orbits, but the extent to which they can provide fine-scale information on methane sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) to assess the capabilities of different satellite observing system configurations. We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 × 1.3 km2 spatial resolution and hourly temporal resolution over a 290 × 235 km2 domain in the Barnett Shale, a major oil and gas field in Texas with a large number of point sources. We sub-sample these footprints to match the observing characteristics of the recently launched TROPOMI instrument (7 × 7 km2 pixels, 11 ppb precision, daily frequency), the planned GeoCARB instrument (2.7 × 3.0 km2 pixels, 4 ppb precision, nominal twice-daily frequency), and other proposed observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its eigenvalues. We find that a week of TROPOMI observations should provide information on temporally invariant emissions at ˜ 30 km spatial resolution. GeoCARB should provide information available on temporally invariant emissions ˜ 2-7 km spatial resolution depending on sampling frequency (hourly to daily). Improvements to the instrument precision yield greater increases in information content than improved sampling frequency. A precision better than 6 ppb is critical for GeoCARB to achieve fine resolution of emissions. Transient emissions would be missed with either TROPOMI or GeoCARB. An aspirational high-resolution geostationary instrument with 1.3 × 1.3 km2 pixel resolution, hourly return time, and 1 ppb precision would effectively constrain the temporally invariant emissions in the Barnett Shale at the kilometer scale and provide some information on hourly variability of sources.

HIGH-RESOLUTION SPATIAL MODELING OF DAILY WEATHER ELEMENTS FOR A CATCHMENT IN THE OREGON CASCADE MOUNTAINS, UNITED STATES

EPA Science Inventory

High-quality, daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decision making. This paper describes the development, application, and assessment of ...

MISR Level 2 TOA/Cloud Classifier parameters (MIL2TCCL_V2)

NASA Technical Reports Server (NTRS)

Diner, David J. (Principal Investigator)

The TOA/Cloud Classifiers contain the Angular Signature Cloud Mask (ASCM), a scene classifier calculated using support vector machine technology (SVM) both of which are on a 1.1 km grid, and cloud fractions at 17.6 km resolution that are available in different height bins (low, middle, high) and are also calculated on an angle-by-angle basis. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=17.6 km; Longitude_Resolution=17.6 km; Horizontal_Resolution_Range=10 km - < 50 km or approximately .09 degree - < .5 degree; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly, Daily - < Weekly].

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

M. P. Jensen; Toto, T.

Standard Atmospheric Radiation Measurement (ARM) Climate Research Facility sounding files provide atmospheric state data in one dimension of increasing time and height per sonde launch. Many applications require a quick estimate of the atmospheric state at higher time resolution. The INTERPOLATEDSONDE (i.e., Interpolated Sounding) Value-Added Product (VAP) transforms sounding data into continuous daily files on a fixed time-height grid, at 1-minute time resolution, on 332 levels, from the surface up to a limit of approximately 40 km. The grid extends that high so the full height of soundings can be captured; however, most soundings terminate at an altitude between 25more » and 30 km, above which no data is provided. Between soundings, the VAP linearly interpolates atmospheric state variables in time for each height level. In addition, INTERPOLATEDSONDE provides relative humidity scaled to microwave radiometer (MWR) observations.« less

Global-scale assessment and combination of SMAP with ASCAT (Active) and AMSR2 (Passive) soil moisture products

USDA-ARS?s Scientific Manuscript database

Global-scale surface soil moisture (SSM) products retrieved from active and passive microwave remote sensing provide an effective method for monitoring near-real-time SSM content with nearly daily temporal resolution. In the present study, we first inter-compared global-scale error patterns and comb...

Spatial-Temporal Dynamics of High-Resolution Animal Networks: What Can We Learn from Domestic Animals?

PubMed

Chen, Shi; Ilany, Amiyaal; White, Brad J; Sanderson, Michael W; Lanzas, Cristina

2015-01-01

Animal social network is the key to understand many ecological and epidemiological processes. We used real-time location system (RTLS) to accurately track cattle position, analyze their proximity networks, and tested the hypothesis of temporal stationarity and spatial homogeneity in these networks during different daily time periods and in different areas of the pen. The network structure was analyzed using global network characteristics (network density), subgroup clustering (modularity), triadic property (transitivity), and dyadic interactions (correlation coefficient from a quadratic assignment procedure) at hourly level. We demonstrated substantial spatial-temporal heterogeneity in these networks and potential link between indirect animal-environment contact and direct animal-animal contact. But such heterogeneity diminished if data were collected at lower spatial (aggregated at entire pen level) or temporal (aggregated at daily level) resolution. The network structure (described by the characteristics such as density, modularity, transitivity, etc.) also changed substantially at different time and locations. There were certain time (feeding) and location (hay) that the proximity network structures were more consistent based on the dyadic interaction analysis. These results reveal new insights for animal network structure and spatial-temporal dynamics, provide more accurate descriptions of animal social networks, and allow more accurate modeling of multiple (both direct and indirect) disease transmission pathways.

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

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

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary con- ditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045–2054 and 2085–2094) are compared with a historical decade (1995–2004). Probabilitymore » density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Finally, using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5–10 times per year in most CONUS and ≥ 95°F days will increase by 1–2 months by the end of the century.« less

High-Resolution Dynamical Downscaling Ensemble Projections of Future Extreme Temperature Distributions for the United States

DOE PAGES

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.; ...

2017-11-20

The aim of this study is to examine projections of extreme temperatures over the continental United States (CONUS) for the 21st century using an ensemble of high spatial resolution dynamically downscaled model simulations with different boundary conditions. The downscaling uses the Weather Research and Forecast model at a spatial resolution of 12 km along with outputs from three different Coupled Model Intercomparison Project Phase 5 global climate models that provide boundary con- ditions under two different future greenhouse gas (GHG) concentration trajectories. The results from two decadal-length time slices (2045–2054 and 2085–2094) are compared with a historical decade (1995–2004). Probabilitymore » density functions of daily maximum/minimum temperatures are analyzed over seven climatologically cohesive regions of the CONUS. The impacts of different boundary conditions as well as future GHG concentrations on extreme events such as heat waves and days with temperature higher than 95°F are also investigated. The results show that the intensity of extreme warm temperature in future summer is significantly increased, while the frequency of extreme cold temperature in future winter decreases. The distribution of summer daily maximum temperature experiences a significant warm-side shift and increased variability, while the distribution of winter daily minimum temperature is projected to have a less significant warm-side shift with decreased variability. Finally, using "business-as-usual" scenario, 5-day heat waves are projected to occur at least 5–10 times per year in most CONUS and ≥ 95°F days will increase by 1–2 months by the end of the century.« less

Toward daily monitoring of vegetation conditions at field scale through fusing data from multiple sensors

USDA-ARS?s Scientific Manuscript database

Vegetation monitoring requires remote sensing data at fine spatial and temporal resolution. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for crop and rangeland monitoring. The Landsat satellite s...

Daily monitoring of vegetation conditions and evapotranspiration at field scale by fusing multi-satellite images

USDA-ARS?s Scientific Manuscript database

Vegetation monitoring requires frequent remote sensing observations. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for vegetation monitoring. The medium spatial resolution (10-100m) sensors are su...

Prototype Global Burnt Area Algorithm Using a Multi-sensor Approach

NASA Astrophysics Data System (ADS)

López Saldaña, G.; Pereira, J.; Aires, F.

2013-05-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05Deg spatial resolution and is available for the 1981-1999 time period. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has been on orbit in the Terra platform since late 1999 and in Aqua since mid 2002; surface reflectance products, MYD09CMG and MOD09CMG, are available at 0.05Deg spatial resolution. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR and the aforementioned MODIS products, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for years 1998 to 2002, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Realization of daily evapotranspiration in arid ecosystems based on remote sensing techniques

NASA Astrophysics Data System (ADS)

Elhag, Mohamed; Bahrawi, Jarbou A.

2017-03-01

Daily evapotranspiration is a major component of water resources management plans. In arid ecosystems, the quest for an efficient water budget is always hard to achieve due to insufficient irrigational water and high evapotranspiration rates. Therefore, monitoring of daily evapotranspiration is a key practice for sustainable water resources management, especially in arid environments. Remote sensing techniques offered a great help to estimate the daily evapotranspiration on a regional scale. Existing open-source algorithms proved to estimate daily evapotranspiration comprehensively in arid environments. The only deficiency of these algorithms is the course scale of the used remote sensing data. Consequently, the adequate downscaling algorithm is a compulsory step to rationalize an effective water resources management plan. Daily evapotranspiration was estimated fairly well using an Advance Along-Track Scanner Radiometer (AATSR) in conjunction with (MEdium Resolution Imaging Spectrometer) MERIS data acquired in July 2013 with 1 km spatial resolution and 3 days of temporal resolution under a surface energy balance system (SEBS) model. Results were validated against reference evapotranspiration ground truth values using standardized Penman-Monteith method with R2 of 0.879. The findings of the current research successfully monitor turbulent heat fluxes values estimated from AATSR and MERIS data with a temporal resolution of 3 days only in conjunction with reliable meteorological data. Research verdicts are necessary inputs for a well-informed decision-making processes regarding sustainable water resource management.

Pluviometric characterization of the Coca river basin by using a stochastic rainfall model

NASA Astrophysics Data System (ADS)

González-Zeas, Dunia; Chávez-Jiménez, Adriadna; Coello-Rubio, Xavier; Correa, Ángel; Martínez-Codina, Ángela

2014-05-01

An adequate design of the hydraulic infrastructures, as well as, the prediction and simulation of a river basin require historical records with a greater temporal and spatial resolution. However, the lack of an extensive network of precipitation data, the short time scale data and the incomplete information provided by the available rainfall stations limit the analysis and design of complex hydraulic engineering systems. As a consequence, it is necessary to develop new quantitative tools in order to face this obstacle imposed by ungauged or poorly gauged basins. In this context, the use of a spatial-temporal rainfall model allows to simulate the historical behavior of the precipitation and at the same time, to obtain long-term synthetic series that preserve the extremal behavior. This paper provides a characterization of the precipitation in the Coca river basin located in Ecuador by using RainSim V3, a robust and well tested stochastic rainfall model based on a spatial-temporal Neyman-Scott rectangular pulses process. A preliminary consistency analysis of the historical rainfall data available has been done in order to identify climatic regions with similar precipitation behavior patterns. Mean and maximum yearly and monthly fields of precipitation of high resolution spaced grids have been obtained through the use of interpolation techniques. According to the climatological similarity, long time series of daily temporal resolution of precipitation have been generated in order to evaluate the model skill in capturing the structure of daily observed precipitation. The results show a good performance of the model in reproducing very well the gross statistics, including the extreme values of rainfall at daily scale. The spatial pattern represented by the observed and simulated precipitation fields highlights the existence of two important regions characterized by different pluviometric comportment, with lower precipitation in the upper part of the basin and higher precipitation in the lower part of the basin.

Echinacea purpurea therapy for the treatment of the common cold: a randomized, double-blind, placebo-controlled clinical trial.

PubMed

Yale, Steven H; Liu, Kejian

2004-06-14

Echinacea purpurea stimulates the immune response and is promoted to reduce symptom severity and the duration of upper respiratory tract infections. We sought to determine the efficacy of a standardized preparation of E purpurea in reducing symptom severity and duration of the common cold. A randomized, double-blind, placebo-controlled design was used. Patients received either 100 mg of E purpurea (freeze-dried pressed juice from the aerial portion of the plant) or a lactose placebo 3 times daily until cold symptoms were relieved or until the end of 14 days, whichever came first. Symptoms (sneezing, nasal discharge, nasal congestion, headache, sore or scratchy throat, hoarseness, muscle aches, and cough) were scored subjectively by the patient and recorded daily in a diary. Kaplan-Meier curves were used to estimate the survival function of time to resolution in each group. The Wilcoxon rank sum test was used to compare time to resolution between the 2 groups. One hundred twenty-eight patients were enrolled within 24 hours of cold symptom onset. Group demographic distribution was comparable for sex, age, time from symptom onset to enrollment in the study, average number of colds per year, and smoking history. No statistically significant difference was observed between treatment groups for either total symptom scores (P range,.29-.90) or mean individual symptom scores (P range,.09-.93). The time to resolution of symptoms was not statistically different (P =.73). Some studies have concluded that Echinacea effectively reduces the symptoms and duration of the common cold. We were unable to replicate such findings. Further studies using different preparations and dosages of E purpurea are necessary to validate previous claims.

Using multi-satellite data fusion to estimate daily high spatial resolution evapotranspiration over a forested site in North Carolina

USDA-ARS?s Scientific Manuscript database

Atmosphere-Land Exchange Inverse model and associated disaggregation scheme (ALEXI/DisALEXI). Satellite-based ET retrievals from both the Moderate Resolution Imaging Spectoradiometer (MODIS; 1km, daily) and Landsat (30m, bi-weekly) are fused with The Spatial and Temporal Adaptive Reflective Fusion ...

Cost reduction from resolution/improvement of carcinoid syndrome symptoms following treatment with above-standard dose of octreotide LAR.

PubMed

Huynh, Lynn; Totev, Todor; Vekeman, Francis; Neary, Maureen P; Duh, Mei S; Benson, Al B

2017-09-01

To calculate the cost reduction associated with diarrhea/flushing symptom resolution/improvement following treatment with above-standard dose octreotide-LAR from the commercial payor's perspective. Diarrhea and flushing are two major carcinoid syndrome symptoms of neuroendocrine tumor (NET). Previously, a study of NET patients from three US tertiary oncology centers (NET 3-Center Study) demonstrated that dose escalation of octreotide LAR to above-standard dose resolved/improved diarrhea/flushing in 79% of the patients within 1 year. Time course of diarrhea/flushing symptom data were collected from the NET 3-Center Study. Daily healthcare costs were calculated from a commercial claims database analysis. For the patient cohort experiencing any diarrhea/flushing symptom resolution/improvement, their observation period was divided into days of symptom resolution/improvement or no improvement, which were then multiplied by the respective daily healthcare cost and summed over 1 year to yield the blended mean annual cost per patient. For patients who experienced no diarrhea/flushing symptom improvement, mean annual daily healthcare cost of diarrhea/flushing over a 1-year period was calculated. The economic model found that 108 NET patients who experienced diarrhea/flushing symptom resolution/improvement within 1 year had statistically significantly lower mean annual healthcare cost/patient than patients with no symptom improvement, by $14,766 (p = .03). For the sub-set of 85 patients experiencing resolution/improvement of diarrhea, their cost reduction was more pronounced, at $18,740 (p = .01), statistically significantly lower than those with no improvement; outpatient costs accounted for 56% of the cost reduction (p = .02); inpatient costs, emergency department costs, and pharmacy costs accounted for the remaining 44%. The economic model relied on two different sources of data, with some heterogeneity in the prior treatment and disease status of patients. Symptom resolution/improvement of diarrhea/flushing after treatment with an above-standard dose of octreotide-LAR in NET was associated with a statistically significant healthcare cost decrease compared to a scenario of no symptom improvement.

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Comiso, Josefino C.; DiGirolamo, Nikolo E.; Shuman, Christopher A.; Key, Jeffrey R.; Koenig, Lora S.

2012-01-01

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid. This record will be elevated in status to a CDR when at least nine more years of data become available either from MODIS Terra or Aqua, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Our ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the VIIRS era. Differences in the APP and MODIS cloud masks have so far precluded the current 1ST records from spanning both the APP and MODIS time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The complete MODIS 1ST daily and monthly data record is available online.

Recent variations in seasonality of temperature and precipitation in Canada, 1976-95

NASA Astrophysics Data System (ADS)

Whitfield, Paul H.; Bodtker, Karin; Cannon, Alex J.

2002-11-01

A previously reported analysis of rehabilitated monthly temperature and precipitation time series for several hundred stations across Canada showed generally spatially coherent patterns of variation between two decades (1976-85 and 1986-95). The present work expands that analysis to finer time scales and a greater number of stations. We demonstrate how the finer temporal resolution, at 5 day or 11 day intervals, increases the separation between clusters of recent variations in seasonal patterns of temperature and precipitation. We also expand the analysis by increasing the number of stations from only rehabilitated monthly data sets to rehabilitated daily sets, then to approximately 1500 daily observation stations. This increases the spatial density of data and allows a finer spatial resolution of patterns between the two decades. We also examine the success of clustering partial records, i.e. sites where the data record is incomplete. The intent of this study was to be consistent with previous work and explore how greater temporal and spatial detail in the climate data affects the resolution of patterns of recent climate variations. The variations we report for temperature and precipitation are taking place at different temporal and spatial scales. Further, the spatial patterns are much broader than local climate regions and ecozones, indicating that the differences observed may be the result of variations in atmospheric circulation.

Evaluating climate models: Should we use weather or climate observations?

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

Oglesby, Robert J; Erickson III, David J

2009-12-01

Calling the numerical models that we use for simulations of climate change 'climate models' is a bit of a misnomer. These 'general circulation models' (GCMs, AKA global climate models) and their cousins the 'regional climate models' (RCMs) are actually physically-based weather simulators. That is, these models simulate, either globally or locally, daily weather patterns in response to some change in forcing or boundary condition. These simulated weather patterns are then aggregated into climate statistics, very much as we aggregate observations into 'real climate statistics'. Traditionally, the output of GCMs has been evaluated using climate statistics, as opposed to their abilitymore » to simulate realistic daily weather observations. At the coarse global scale this may be a reasonable approach, however, as RCM's downscale to increasingly higher resolutions, the conjunction between weather and climate becomes more problematic. We present results from a series of present-day climate simulations using the WRF ARW for domains that cover North America, much of Latin America, and South Asia. The basic domains are at a 12 km resolution, but several inner domains at 4 km have also been simulated. These include regions of complex topography in Mexico, Colombia, Peru, and Sri Lanka, as well as a region of low topography and fairly homogeneous land surface type (the U.S. Great Plains). Model evaluations are performed using standard climate analyses (e.g., reanalyses; NCDC data) but also using time series of daily station observations. Preliminary results suggest little difference in the assessment of long-term mean quantities, but the variability on seasonal and interannual timescales is better described. Furthermore, the value-added by using daily weather observations as an evaluation tool increases with the model resolution.« less

Creating a seamless 1 km resolution daily land surface temperature dataset for urban and surrounding areas in the conterminous United States

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

Li, Xiaoma; Zhou, Yuyu; Asrar, Ghassem R.

High spatiotemporal land surface temperature (LST) datasets are increasingly needed in a variety of fields such as ecology, hydrology, meteorology, epidemiology, and energy systems. Moderate Resolution Imaging Spectroradiometer (MODIS) LST is one of such high spatiotemporal datasets that are widely used. But, it has large amount of missing values primarily because of clouds. Gapfilling the missing values is an important approach to create high spatiotemporal LST datasets. However current gapfilling methods have limitations in terms of accuracy and time required to assemble the data over large areas (e.g., national and continental levels). In this study, we developed a 3-step hybridmore » method by integrating a combination of daily merging, spatiotemporal gapfilling, and temporal interpolation methods, to create a high spatiotemporal LST dataset using the four daily LST observations from the two MODIS instruments on Terra and Aqua satellites. We applied this method in urban and surrounding areas for the conterminous U.S. in 2010. The evaluation of the gapfilled LST product indicates that its root mean squared error (RMSE) to be 3.3K for mid-daytime (1:30 pm) and 2.7K for mid-13 nighttime (1:30 am) observations. The method can be easily extended to other years and regions and is also applicable to other satellite products. This seamless daily (mid-daytime and mid-nighttime) LST product with 1 km spatial resolution is of great value for studying effects of urbanization (e.g., urban heat island) and the related impacts on people, ecosystems, energy systems and other infrastructure for cities.« less

Comparison of alternative spatial resolutions in the application of a spatially distributed biogeochemical model over complex terrain

USGS Publications Warehouse

Turner, D.P.; Dodson, R.; Marks, D.

1996-01-01

Spatially distributed biogeochemical models may be applied over grids at a range of spatial resolutions, however, evaluation of potential errors and loss of information at relatively coarse resolutions is rare. In this study, a georeferenced database at the 1-km spatial resolution was developed to initialize and drive a process-based model (Forest-BGC) of water and carbon balance over a gridded 54976 km2 area covering two river basins in mountainous western Oregon. Corresponding data sets were also prepared at 10-km and 50-km spatial resolutions using commonly employed aggregation schemes. Estimates were made at each grid cell for climate variables including daily solar radiation, air temperature, humidity, and precipitation. The topographic structure, water holding capacity, vegetation type and leaf area index were likewise estimated for initial conditions. The daily time series for the climatic drivers was developed from interpolations of meteorological station data for the water year 1990 (1 October 1989-30 September 1990). Model outputs at the 1-km resolution showed good agreement with observed patterns in runoff and productivity. The ranges for model inputs at the 10-km and 50-km resolutions tended to contract because of the smoothed topography. Estimates for mean evapotranspiration and runoff were relatively insensitive to changing the spatial resolution of the grid whereas estimates of mean annual net primary production varied by 11%. The designation of a vegetation type and leaf area at the 50-km resolution often subsumed significant heterogeneity in vegetation, and this factor accounted for much of the difference in the mean values for the carbon flux variables. Although area wide means for model outputs were generally similar across resolutions, difference maps often revealed large areas of disagreement. Relatively high spatial resolution analyses of biogeochemical cycling are desirable from several perspectives and may be particularly important in the study of the potential impacts of climate change.

Empirical downscaling of daily minimum air temperature at very fine resolutions in complex terrain

Treesearch

Zachary A. Holden; John T. Abatzoglou; Charles H. Luce; L. Scott Baggett

2011-01-01

Available air temperature models do not adequately account for the influence of terrain on nocturnal air temperatures. An empirical model for night time air temperatures was developed using a network of one hundred and forty inexpensive temperature sensors deployed across the Bitterroot National Forest, Montana. A principle component analysis (PCA) on minimum...

Assessment and Prediction of Natural Hazards from Satellite Imagery

PubMed Central

Gillespie, Thomas W.; Chu, Jasmine; Frankenberg, Elizabeth; Thomas, Duncan

2013-01-01

Since 2000, there have been a number of spaceborne satellites that have changed the way we assess and predict natural hazards. These satellites are able to quantify physical geographic phenomena associated with the movements of the earth’s surface (earthquakes, mass movements), water (floods, tsunamis, storms), and fire (wildfires). Most of these satellites contain active or passive sensors that can be utilized by the scientific community for the remote sensing of natural hazards over a number of spatial and temporal scales. The most useful satellite imagery for the assessment of earthquake damage comes from high-resolution (0.6 m to 1 m pixel size) passive sensors and moderate resolution active sensors that can quantify the vertical and horizontal movement of the earth’s surface. High-resolution passive sensors have been used to successfully assess flood damage while predictive maps of flood vulnerability areas are possible based on physical variables collected from passive and active sensors. Recent moderate resolution sensors are able to provide near real time data on fires and provide quantitative data used in fire behavior models. Limitations currently exist due to atmospheric interference, pixel resolution, and revisit times. However, a number of new microsatellites and constellations of satellites will be launched in the next five years that contain increased resolution (0.5 m to 1 m pixel resolution for active sensors) and revisit times (daily ≤ 2.5 m resolution images from passive sensors) that will significantly improve our ability to assess and predict natural hazards from space. PMID:25170186

Analysis of Correlation Tendency between Wind and Solar from Various Spatio-temporal Perspectives

NASA Astrophysics Data System (ADS)

Wang, X.; Weihua, X.; Mei, Y.

2017-12-01

Analysis of correlation between wind resources and solar resources could explore their complementary features, enhance the utilization efficiency of renewable energy and further alleviate the carbon emission issues caused by the fossil energy. In this paper, we discuss the correlation between wind and solar from various spatio-temporal perspectives (from east to west, in terms of plain, plateau, hill, and mountain, from hourly to daily, ten days and monthly) with observed data and modeled data from NOAA (National Oceanic and Atmospheric Administration) and NERL (National Renewable Energy Laboratory). With investigation of wind speed time series and solar radiation time series (period: 10 years, resolution: 1h) of 72 stations located in various landform and distributed dispersedly in USA, the results show that the correlation coefficient, Kendall's rank correlation coefficient, changes negative to positive value from east coast to west coast of USA, and this phenomena become more obvious when the time scale of resolution increases from daily to ten days and monthly. Furthermore, considering the differences of landforms which influence the local meteorology the Kendall coefficients of diverse topographies are compared and it is found that the coefficients descend from mountain to hill, plateau and plain. However, no such evident tendencies could be found in daily scale. According to this research, it is proposed that the complementary feature of wind resources and solar resources in the east or in the mountain area of USA is conspicuous. Subsequent study would try to further verify this analysis by investigating the operation status of wind power station and solar power station.

STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

NASA Astrophysics Data System (ADS)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present numerous application of the STAMMEX grids spanning from case studies of the major Central European floods to long-term changes in different precipitation statistics, including those accounting for the alternation of dry and wet periods and precipitation intensities associated with prolonged rainy episodes.

Estimating Daily Evapotranspiration Based on A Model of Evapotranspiration Fraction (EF) for Mixed Pixels

NASA Astrophysics Data System (ADS)

Xin, X.; Li, F.; Peng, Z.; Qinhuo, L.

2017-12-01

Land surface heterogeneities significantly affect the reliability and accuracy of remotely sensed evapotranspiration (ET), and it gets worse for lower resolution data. At the same time, temporal scale extrapolation of the instantaneous latent heat flux (LE) at satellite overpass time to daily ET are crucial for applications of such remote sensing product. The purpose of this paper is to propose a simple but efficient model for estimating daytime evapotranspiration considering heterogeneity of mixed pixels. In order to do so, an equation to calculate evapotranspiration fraction (EF) of mixed pixels was derived based on two key assumptions. Assumption 1: the available energy (AE) of each sub-pixel equals approximately to that of any other sub-pixels in the same mixed pixel within acceptable margin of bias, and as same as the AE of the mixed pixel. It's only for a simpification of the equation, and its uncertainties and resulted errors in estimated ET are very small. Assumption 2: EF of each sub-pixel equals to the EF of the nearest pure pixel(s) of same land cover type. This equation is supposed to be capable of correcting the spatial scale error of the mixed pixels EF and can be used to calculated daily ET with daily AE data.The model was applied to an artificial oasis in the midstream of Heihe River. HJ-1B satellite data were used to estimate the lumped fluxes at the scale of 300 m after resampling the 30-m resolution datasets to 300 m resolution, which was used to carry on the key step of the model. The results before and after correction were compare to each other and validated using site data of eddy-correlation systems. Results indicated that the new model is capable of improving accuracy of daily ET estimation relative to the lumped method. Validations at 12 sites of eddy-correlation systems for 9 days of HJ-1B overpass showed that the R² increased to 0.82 from 0.62; the RMSE decreased to 1.60 MJ/m² from 2.47MJ/m²; the MBE decreased from 1.92 MJ/m² to 1.18MJ/m², which is a quite significant enhancement.The model is easy to apply. And the moduler of inhomogeneous surfaces is independent and easy to be embedded in the traditional remote sensing algorithms of heat fluxes to get daily ET, which were mainly designed to calculate LE or ET under unsaturated conditions and did not consider heterogeneities of land surface.

Surface wave effect on the upper ocean in marine forecast

NASA Astrophysics Data System (ADS)

Wang, Guansuo; Qiao, Fangli; Xia, Changshui; Zhao, Chang

2015-04-01

An Operational Coupled Forecast System for the seas off China and adjacent (OCFS-C) is constructed based on the paralleled wave-circulation coupled model, which is tested with comprehensive experiments and operational since November 1st, 2007. The main feature of the system is that the wave-induced mixing is considered in circulation model. Daily analyses and three day forecasts of three-dimensional temperature, salinity, currents and wave height are produced. Coverage is global at 1/2 degreed resolution with nested models up to 1/24 degree resolution in China Sea. Daily remote sensing sea surface temperatures (SST) are taken to relax to an analytical product as hot restarting fields for OCFS-C by the Nudging techniques. Forecasting-data inter-comparisons are performed to measure the effectiveness of OCFS-C in predicting upper-ocean quantities including SST, mixed layer depth (MLD) and subsurface temperature. The variety of performance with lead time and real-time is discussed as well using the daily statistic results for SST between forecast and satellite data. Several buoy observations and many Argo profiles are used for this validation. Except the conventional statistical metrics, non-dimension skill scores (SS) is taken to estimate forecast skill. Model SST comparisons with more one year-long SST time series from 2 buoys given a large SS value (more than 0.90). And skill in predicting the seasonal variability of SST is confirmed. Model subsurface temperature comparisons with that from a lot of Argo profiles indicated that OCFS-C has low skill in predicting subsurface temperatures between 80m and 120m. Inter-comparisons of MLD reveal that MLD from model is shallower than that from Argo profiles by about 12m. QCFS-C is successful and steady in predicting MLD. The daily statistic results for SST between 1-d, 2-d and 3-d forecast and data is adopted to describe variability of Skill in predicting SST with lead time or real time. In a word QCFS-C shows reasonable accuracy over a series of studies designed to test ability to predict upper ocean conditions.

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

NASA Astrophysics Data System (ADS)

Martin, Gill M.; Klingaman, Nicholas P.; Moise, Aurel F.

2017-01-01

This study analyses tropical rainfall variability (on a range of temporal and spatial scales) in a set of parallel Met Office Unified Model (MetUM) simulations at a range of horizontal resolutions, which are compared with two satellite-derived rainfall datasets. We focus on the shorter scales, i.e. from the native grid and time step of the model through sub-daily to seasonal, since previous studies have paid relatively little attention to sub-daily rainfall variability and how this feeds through to longer scales. We find that the behaviour of the deep convection parametrization in this model on the native grid and time step is largely independent of the grid-box size and time step length over which it operates. There is also little difference in the rainfall variability on larger/longer spatial/temporal scales. Tropical convection in the model on the native grid/time step is spatially and temporally intermittent, producing very large rainfall amounts interspersed with grid boxes/time steps of little or no rain. In contrast, switching off the deep convection parametrization, albeit at an unrealistic resolution for resolving tropical convection, results in very persistent (for limited periods), but very sporadic, rainfall. In both cases, spatial and temporal averaging smoothes out this intermittency. On the ˜ 100 km scale, for oceanic regions, the spectra of 3-hourly and daily mean rainfall in the configurations with parametrized convection agree fairly well with those from satellite-derived rainfall estimates, while at ˜ 10-day timescales the averages are overestimated, indicating a lack of intra-seasonal variability. Over tropical land the results are more varied, but the model often underestimates the daily mean rainfall (partly as a result of a poor diurnal cycle) but still lacks variability on intra-seasonal timescales. Ultimately, such work will shed light on how uncertainties in modelling small-/short-scale processes relate to uncertainty in climate change projections of rainfall distribution and variability, with a view to reducing such uncertainty through improved modelling of small-/short-scale processes.

Metronidazole Vaginal Gel 1.3% in the Treatment of Bacterial Vaginosis: A Dose-Ranging Study

PubMed Central

Chavoustie, Steven E.; Jacobs, Mark; Reisman, Howard A.; Waldbaum, Arthur S.; Levy, Sharon F.; Hillier, Sharon L.; Nyirjesy, Paul

2015-01-01

Objective Metronidazole vaginal gel (MVG) 0.75% is a US Food and Drug Administration–approved, 5-day treatment for bacterial vaginosis (BV). This study tested the hypothesis that a shorter treatment course at a higher dose (MVG 1.3%) would yield similar efficacy to 5 days of MVG 0.75%. Materials and Methods This phase 2, multicenter, randomized, controlled, investigator-blinded, dose-ranging study enrolled women with a clinical diagnosis of BV. Patients were assigned to MVG 1.3% once daily for 1, 3, or 5 days or MVG 0.75% once daily for 5 days. The therapeutic cure rate, requiring clinical and bacteriological cure, at the end-of-study visit was determined for the per-protocol population. A Kaplan-Meier analysis was used to estimate median time-to-symptom resolution. Results In total, 255 women (mean age = 35 y) were enrolled. The per-protocol population included 189 patients. The therapeutic cure rate was higher in the 1-day (13/43, 30.2%), 3-day (12/48, 25.0%), and 5-day (16/49, 32.7%) MVG 1.3% groups versus the MVG 0.75% group (10/49, 20.4%). Median time-to-resolution of fishy odor was shorter in the 3 MVG 1.3% groups versus the MVG 0.75% group. The 5-day MVG 1.3% group had the lowest rate of symptom return. No clinically important differences were observed in adverse events across treatment groups; most events were mild or moderate in intensity and considered unrelated to treatment. Similar results were found in the modified intent-to-treat population. Conclusions Metronidazole vaginal gel 1.3% applied once daily for 1, 3, or 5 days showed similar efficacy, safety, and tolerability as MVG 0.75% once daily for 5 days. PMID:24983350

Metronidazole vaginal gel 1.3% in the treatment of bacterial vaginosis: a dose-ranging study.

PubMed

Chavoustie, Steven E; Jacobs, Mark; Reisman, Howard A; Waldbaum, Arthur S; Levy, Sharon F; Hillier, Sharon L; Nyirjesy, Paul

2015-04-01

Metronidazole vaginal gel (MVG) 0.75% is a US Food and Drug Administration-approved, 5-day treatment for bacterial vaginosis (BV). This study tested the hypothesis that a shorter treatment course at a higher dose (MVG 1.3%) would yield similar efficacy to 5 days of MVG 0.75%. This phase 2, multicenter, randomized, controlled, investigator-blinded, dose-ranging study enrolled women with a clinical diagnosis of BV. Patients were assigned to MVG 1.3% once daily for 1, 3, or 5 days or MVG 0.75% once daily for 5 days. The therapeutic cure rate, requiring clinical and bacteriological cure, at the end-of-study visit was determined for the per-protocol population. A Kaplan-Meier analysis was used to estimate median time-to-symptom resolution. In total, 255 women (mean age = 35 y) were enrolled. The per-protocol population included 189 patients. The therapeutic cure rate was higher in the 1-day (13/43, 30.2%), 3-day (12/48, 25.0%), and 5-day (16/49, 32.7%) MVG 1.3% groups versus the MVG 0.75% group (10/49, 20.4%). Median time-to-resolution of fishy odor was shorter in the 3 MVG 1.3% groups versus the MVG 0.75% group. The 5-day MVG 1.3% group had the lowest rate of symptom return. No clinically important differences were observed in adverse events across treatment groups; most events were mild or moderate in intensity and considered unrelated to treatment. Similar results were found in the modified intent-to-treat population. Metronidazole vaginal gel 1.3% applied once daily for 1, 3, or 5 days showed similar efficacy, safety, and tolerability as MVG 0.75% once daily for 5 days.

Study of atmospheric aerosols by IBA techniques: The LABEC experience

NASA Astrophysics Data System (ADS)

Lucarelli, F.; Calzolai, G.; Chiari, M.; Nava, S.; Carraresi, L.

2018-02-01

At the 3 MV Tandetron accelerator of the LABEC laboratory of INFN (Florence, Italy) an external beam facility is fully dedicated to PIXE-PIGE measurements of the elemental composition of atmospheric aerosols. All the elements with Z > 10 are simultaneously detected by PIXE typically in one minute. This setup allows us an easy automatic positioning, changing and scanning of samples collected by different kinds of devices: long series of daily PM (Particulate Matter) samples can be analysed in short times, as well as size-segregated and high time-resolution aerosol samples. Thanks to the capability of detecting all the crustal elements, PIXE-PIGE analyses are unrivalled in the study of mineral dust: consequently, they are very effective in the study of natural aerosols, like, for example, Saharan dust intrusions. Among the detectable elements there are also important markers of anthropogenic sources, which allow effective source apportionment studies in polluted urban environments using a multivariate method like Positive Matrix Factorization (PMF). Examples regarding recent monitoring campaigns, performed in urban and remote areas, both daily and with high time resolution (hourly samples), as well as with size selection, are presented. The importance of the combined use of the Particle Induced Gamma Ray emission technique (PIGE) and of other complementary (non-nuclear) techniques is highlighted.

Prototype global burnt area algorithm using the AVHRR-LTDR time series

NASA Astrophysics Data System (ADS)

López-Saldaña, Gerardo; Pereira, José Miguel; Aires, Filipe

2013-04-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05° spatial resolution and is available for the 1981-1999 time period. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR dataset, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for year 1998, which was selected because of a positive fire anomaly, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

SGP and TWP (Manus) Ice Cloud Vertical Velocities

DOE Data Explorer

Kalesse, Heike

2013-06-27

Daily netcdf-files of ice-cloud dynamics observed at the ARM sites at SGP (Jan1997-Dec2010) and Manus (Jul1999-Dec2010). The files include variables at different time resolution (10s, 20min, 1hr). Profiles of radar reflectivity factor (dbz), Doppler velocity (vel) as well as retrieved vertical air motion (V_air) and reflectivity-weighted particle terminal fall velocity (V_ter) are given at 10s, 20min and 1hr resolution. Retrieved V_air and V_ter follow radar notation, so positive values indicate downward motion. Lower level clouds are removed, however a multi-layer flag is included.

Examination of Daily Weather in the NCAR CCM

NASA Astrophysics Data System (ADS)

Cocke, S. D.

2006-05-01

The NCAR CCM is one of the most extensively studied climate models in the scientific community. However, most studies focus primarily on the long term mean behavior, typically monthly or longer time scales. In this study we examine the daily weather in the GCM by performing a series of daily or weekly 10 day forecasts for one year at moderate (T63) and high (T126) resolution. The model is initialized with operational "AVN" and ECMWF analyses, and model performance is compared to that of major operational centers, using conventional skill scores used by the major centers. Such a detailed look at the CCM at shorter time scales may lead to improvements in physical parameterizations, which may in turn lead to improved climate simulations. One finding from this study is that the CCM has a significant drying tendency in the lower troposphere compared to the operational analyses. Another is that the large scale predictability of the GCM is competitive with most of the operational models, particularly in the southern hemisphere.

Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Nebula Cloud Computing Environment

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Case, Jonathan L.; Venner, Jason; Moreno-Madrinan, Max. J.; Delgado, Francisco

2012-01-01

Over the past two years, scientists in the Earth Science Office at NASA fs Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real ]time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA fs Short ]term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface ] and satellite ]based observations.

Development of a High Resolution Weather Forecast Model for Mesoamerica Using the NASA Nebula Cloud Computing Environment

NASA Astrophysics Data System (ADS)

Molthan, A.; Case, J.; Venner, J.; Moreno-Madriñán, M. J.; Delgado, F.

2012-12-01

Over the past two years, scientists in the Earth Science Office at NASA's Marshall Space Flight Center (MSFC) have explored opportunities to apply cloud computing concepts to support near real-time weather forecast modeling via the Weather Research and Forecasting (WRF) model. Collaborators at NASA's Short-term Prediction Research and Transition (SPoRT) Center and the SERVIR project at Marshall Space Flight Center have established a framework that provides high resolution, daily weather forecasts over Mesoamerica through use of the NASA Nebula Cloud Computing Platform at Ames Research Center. Supported by experts at Ames, staff at SPoRT and SERVIR have established daily forecasts complete with web graphics and a user interface that allows SERVIR partners access to high resolution depictions of weather in the next 48 hours, useful for monitoring and mitigating meteorological hazards such as thunderstorms, heavy precipitation, and tropical weather that can lead to other disasters such as flooding and landslides. This presentation will describe the framework for establishing and providing WRF forecasts, example applications of output provided via the SERVIR web portal, and early results of forecast model verification against available surface- and satellite-based observations.

Continuity of MODIS and VIIRS Snow-Cover Maps during Snowmelt in the Catskill Mountains in New York

NASA Astrophysics Data System (ADS)

Hall, D. K.; Riggs, G. A., Jr.; Roman, M. O.; DiGirolamo, N. E.

2015-12-01

We investigate the local and regional differences and possible biases between the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible-Infrared Imager Radiometer Suite (VIIRS) snow-cover maps in the winter of 2012 during snowmelt conditions in the Catskill Mountains in New York using a time series of cloud-gap filled daily snow-cover maps. The MODIS Terra instrument has been providing daily global snow-cover maps since February 2000 (Riggs and Hall, 2015). Using the VIIRS instrument, launched in 2011, NASA snow products are being developed based on the heritage MODIS snow-mapping algorithms, and will soon be available to the science community. Continuity of the standard NASA MODIS and VIIRS snow-cover maps is essential to enable environmental-data records (EDR) to be developed for analysis of snow-cover trends using a consistent data record. For this work, we compare daily MODIS and VIIRS snow-cover maps of the Catskill Mountains from 29 February through 14 March 2012. The entire region was snow covered on 29 February and by 14 March the snow had melted; we therefore have a daily time series available to compare normalized difference snow index (NDSI), as an indicator of snow-cover fraction. The MODIS and VIIRS snow-cover maps have different spatial resolutions (500 m for MODIS and 375 m for VIIRS) and different nominal overpass times (10:30 AM for MODIS Terra and 2:30 PM for VIIRS) as well as different cloud masks. The results of this work will provide a quantitative assessment of the continuity of the snow-cover data records for use in development of an EDR of snow cover.http://modis-snow-ice.gsfc.nasa.gov/Riggs, G.A. and D.K. Hall, 2015: MODIS Snow Products User Guide to Collection 6, http://modis-snow-ice.gsfc.nasa.gov/?c=userguides

Internal Consistency of the NVAP Water Vapor Dataset

NASA Technical Reports Server (NTRS)

Suggs, Ronnie J.; Jedlovec, Gary J.; Arnold, James E. (Technical Monitor)

2001-01-01

The NVAP (NASA Water Vapor Project) dataset is a global dataset at 1 x 1 degree spatial resolution consisting of daily, pentad, and monthly atmospheric precipitable water (PW) products. The analysis blends measurements from the Television and Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS), the Special Sensor Microwave/Imager (SSM/I), and radiosonde observations into a daily collage of PW. The original dataset consisted of five years of data from 1988 to 1992. Recent updates have added three additional years (1993-1995) and incorporated procedural and algorithm changes from the original methodology. Since each of the PW sources (TOVS, SSM/I, and radiosonde) do not provide global coverage, each of these sources compliment one another by providing spatial coverage over regions and during times where the other is not available. For this type of spatial and temporal blending to be successful, each of the source components should have similar or compatible accuracies. If this is not the case, regional and time varying biases may be manifested in the NVAP dataset. This study examines the consistency of the NVAP source data by comparing daily collocated TOVS and SSM/I PW retrievals with collocated radiosonde PW observations. The daily PW intercomparisons are performed over the time period of the dataset and for various regions.

Performance Comparison of Big Data Analytics With NEXUS and Giovanni

NASA Astrophysics Data System (ADS)

Jacob, J. C.; Huang, T.; Lynnes, C.

2016-12-01

NEXUS is an emerging data-intensive analysis framework developed with a new approach for handling science data that enables large-scale data analysis. It is available through open source. We compare performance of NEXUS and Giovanni for 3 statistics algorithms applied to NASA datasets. Giovanni is a statistics web service at NASA Distributed Active Archive Centers (DAACs). NEXUS is a cloud-computing environment developed at JPL and built on Apache Solr, Cassandra, and Spark. We compute global time-averaged map, correlation map, and area-averaged time series. The first two algorithms average over time to produce a value for each pixel in a 2-D map. The third algorithm averages spatially to produce a single value for each time step. This talk is our report on benchmark comparison findings that indicate 15x speedup with NEXUS over Giovanni to compute area-averaged time series of daily precipitation rate for the Tropical Rainfall Measuring Mission (TRMM with 0.25 degree spatial resolution) for the Continental United States over 14 years (2000-2014) with 64-way parallelism and 545 tiles per granule. 16-way parallelism with 16 tiles per granule worked best with NEXUS for computing an 18-year (1998-2015) TRMM daily precipitation global time averaged map (2.5 times speedup) and 18-year global map of correlation between TRMM daily precipitation and TRMM real time daily precipitation (7x speedup). These and other benchmark results will be presented along with key lessons learned in applying the NEXUS tiling approach to big data analytics in the cloud.

Development of daily "swath" mascon solutions from GRACE

NASA Astrophysics Data System (ADS)

Save, Himanshu; Bettadpur, Srinivas

2016-04-01

The Gravity Recovery and Climate Experiment (GRACE) mission has provided invaluable and the only data of its kind over the past 14 years that measures the total water column in the Earth System. The GRACE project provides monthly average solutions and there are experimental quick-look solutions and regularized sliding window solutions available from Center for Space Research (CSR) that implement a sliding window approach and variable daily weights. The need for special handling of these solutions in data assimilation and the possibility of capturing the total water storage (TWS) signal at sub-monthly time scales motivated this study. This study discusses the progress of the development of true daily high resolution "swath" mascon total water storage estimate from GRACE using Tikhonov regularization. These solutions include the estimates of daily total water storage (TWS) for the mascon elements that were "observed" by the GRACE satellites on a given day. This paper discusses the computation techniques, signal, error and uncertainty characterization of these daily solutions. We discuss the comparisons with the official GRACE RL05 solutions and with CSR mascon solution to characterize the impact on science results especially at the sub-monthly time scales. The evaluation is done with emphasis on the temporal signal characteristics and validated against in-situ data set and multiple models.

Combined Use of Satellite Observations with Urban Surface Characteristics to Estimate PM Concentrations by Employing Mixed-Effects Models

NASA Astrophysics Data System (ADS)

Beloconi, Anton; Benas, Nikolaos; Chrysoulakis, Nektarios; Kamarianakis, Yiannis

2015-11-01

Linear mixed effects models were developed for the estimation of the average daily Particulate Matter (PM) concentration spatial distribution over the area of Greater London (UK). Both fine (PM2.5) and coarse (PM10) concentrations were predicted for the 2002- 2012 time period, based on satellite data. The latter included Aerosol Optical Thickness (AOT) at 3×3 km spatial resolution, as well as the Surface Relative Humidity, Surface Temperature and K-Index derived from MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. For a meaningful interpretation of the association among these variables, all data were homogenized with regard to spatial support and geographic projection, thus addressing the change of support problem and leading to a valid statistical inference. To this end, spatial (2D) and spatio- temporal (3D) kriging techniques were applied to in-situ particulate matter concentrations and the leave-one- station-out cross-validation was performed on a daily level to gauge the quality of the predictions. Satellite- derived covariates displayed clear seasonal patterns; in order to work with data which is stationary in mean, for each covariate, deviations from its estimated annual profiles were computed using nonlinear least squares and nonlinear absolute deviations. High-resolution land- cover and morphology static datasets were additionally incorporated in the analysis in order to catch the effects of nearby emission sources and sequestration sites. For pairwise comparisons of the particulate matter concentration means at distinct land-cover classes, the pairwise comparisons method for unequal sample sizes, known as Tukey's method, was performed. The use of satellite-derived products allowed better assessment of space-time interactions of PM, since these daily spatial measurements were able to capture differences in PM concentrations between grid cells, while the use of high- resolution land-cover and morphology static datasets allowed accounting for local industrial, domestic and traffic related air pollution. The developed methods are expected to fully exploit ESA's new Sentinel-3 observations to estimate spatial distributions of both PM10 and PM2.5 concentrations in arbitrary cities.

Agent-based Large-Scale Emergency Evacuation Using Real-Time Open Government Data

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

Lu, Wei; Liu, Cheng; Bhaduri, Budhendra L

The open government initiatives have provided tremendous data resources for the transportation system and emergency services in urban areas. This paper proposes a traffic simulation framework using high temporal resolution demographic data and real time open government data for evacuation planning and operation. A comparison study using real-world data in Seattle, Washington is conducted to evaluate the framework accuracy and evacuation efficiency. The successful simulations of selected area prove the concept to take advantage open government data, open source data, and high resolution demographic data in emergency management domain. There are two aspects of parameters considered in this study: usermore » equilibrium (UE) conditions of traffic assignment model (simple Non-UE vs. iterative UE) and data temporal resolution (Daytime vs. Nighttime). Evacuation arrival rate, average travel time, and computation time are adopted as Measure of Effectiveness (MOE) for evacuation performance analysis. The temporal resolution of demographic data has significant impacts on urban transportation dynamics during evacuation scenarios. Better evacuation performance estimation can be approached by integrating both Non-UE and UE scenarios. The new framework shows flexibility in implementing different evacuation strategies and accuracy in evacuation performance. The use of this framework can be explored to day-to-day traffic assignment to support daily traffic operations.« less

On-eye optical quality of daily disposable contact lenses for different wearing times.

PubMed

Montés-Micó, Robert; Belda-Salmerón, Lurdes; Ferrer-Blasco, Teresa; Albarrán-Diego, César; García-Lázaro, Santiago

2013-09-01

To quantify the optical quality of various daily disposable contact lenses in vivo and to ascertain its variation in terms of wearing time by means of objective non-invasive determination of wavefront patterns. The crx1 adaptive-optics system was used to measure the wavefront aberrations in 15 myopic eyes before and at 2-h intervals after contact lens fitting, over a 12-h wearing period. Seven types of contact lenses having different material, water content and lens design were evaluated in this study: Dailies Total1, Dailies AquaComfort Plus, Proclear 1 Day, 1-Day Acuvue TruEye, 1-Day Acuvue moist, SofLens daily disposable and Clariti 1-Day. The aberration data were analysed by fitting Zernike polynomials up to the 5th-order for 3 and 5-mm pupils. The optical quality under each condition and at each point in time was described by means of the Root-Mean-Square (RMS) value of wavefront aberration, Modulation Transfer Function (MTF), Point Spread Function and cut-off spatial frequency. A RMS increase was observed after contact lens fitting as well as over time, both for a 3-mm and a 5-mm pupil. Each type of lens induced a different amount of wavefront aberrations, which vary over time also in a different manner. Dailies Total1 showed the lowest RMS values both at baseline and at the end of the day. In addition, Dailies Total1 provided the best MTF out of all the contact lenses that were assessed. These observations were reflected in higher cut-off spatial frequencies and visual resolution both at baseline and after 12 h of wearing time. Aberrometry makes it possible to analyse accurately and in vivo the optical quality of contact lenses and to assess how lenses having different characteristics - such as material or water content - behave for different wearing times. These variations across contact lenses may result in differences in visual performance. © 2013 The Authors Ophthalmic & Physiological Optics © 2013 The College of Optometrists.

Trace element study in scallop shells by laser ablation ICP-MS: the example of Ba/Ca ratios

NASA Astrophysics Data System (ADS)

Lorrain, A.; Pécheyran, C.; Paulet, Y.-M.; Chauvaud, L.; Amouroux, D.; Krupp, E.; Donard, O.

2003-04-01

As scallop shells grow incrementally at a rate of one line per day, environmental changes could then be evidenced on a daily basis. As an example for trace element incorporation studies, barium is a geochemical tracer that can be directly related to oceanic primary productivity. Hence, monitoring Ba/Ca variations in a scallop shell should give information about phytoplanktonic events encountered day by day during its life. The very high spatial resolution (typically 40 - 200 µm) and the high elemental sensitivity required can only be achieved by the combination of laser ablation coupled to inductively coupled plasma mass spectrometry. This study demonstrates that Laser ablation coupled to ICP-MS determination is a relevant tool for high resolution distribution measurement of trace elements in calcite matrix. The ablation strategy related to single line rastering and calcium normalisation were found to be the best analytical conditions in terms of reproducibility and sensitivity. The knowledge of P. maximus growth rings periodicity (daily), combined with LA-ICP-MS micro analysis allows the acquisition of time dated profiles with high spatial and thus temporal resolution. This resolution makes P. maximus a potential tool for environmental reconstruction and especially for accurate calibration of proxies. However, the relations among Ba/Ca peaks and phytoplanktonic events differed according to the animals and some inter-annual discrepancies complexify the interpretation.

Systematic recover of long high-resolution rainfall time series recorded by pluviographs during the 20th century.

NASA Astrophysics Data System (ADS)

Delitala, Alessandro M. S.; Deidda, Roberto; Mascaro, Giuseppe; Piga, Enrico; Querzoli, Giorgio

2010-05-01

During most of the 20th century, precipitation has been continuously measured by means of the so-called "pluviographs", i.e. rain gauges including a mechanical apparatus for continuously recording the depth of water from precipitation on specific strip charts, usually on a weekly basis. The signal recorded on such strips was visually examined by trained personnel on a regular basis, in order to extract the daily precipitation totals and the maximum precipitation intensities over short periods (from a few minutes to hours). The rest of the high-resolution information contained in the signal was usually not extracted, except for specific cases. A systematic recovering of the entire information at high temporal resolution contained in these precipitation signals would provide a fundamental database to improve the characterization of historical rainfall climatology during the previous century. The Department of Land Engineering of the University of Cagliari has recently developed and tested an automatic software, based on image analysis techniques, which is able to acquire the scanned images of the pluviograph strip charts, to automatically digitise the signal and to produce a digital database of continuous precipitation records at the highest possible temporal resolution, i.e. 5 to 10 minutes. Along with that, a significant amount of daily precipitation totals from the late 19th and the 20th century, either elaborated from pluviograph strip charts or simply derived from bucket rain gauges, still exists in paper form, but it has never been digitalized. Within a project partly-funded by the Operational Programme of the European Union "Italia-Francia Marittimo", the Regional Environmental Protection Agency of Sardinia and the University of Cagliari will recover both the high-resolution rainfall signals and the older time series of daily totals recorded by a large number of pluviographs belonging to the historical monitoring networks of the island of Sardinia. Such data will then be used to construct the high-resolution climatology of precipitation over Sardinia, both assuming stationary climate and slowly varying climate. Specific attention will be devoted to a set of critical hydrological basins, often affected by intense precipitation and flash floods. All information will then be made available to researchers, regional officers, technicians (e.g. hydraulic engineers) and the greater public interested into such information. The present poster describes the general scope of the E.U. project and the specific activities in the field of climatology of Sardinia rainfall that will be conducted as well as the expected results. A section will be dedicated to show how the pluviograph strips are automatically digitized.

BIOMAP A Daily Time Step, Mechanistic Model for the Study of Ecosystem Dynamics

NASA Astrophysics Data System (ADS)

Wells, J. R.; Neilson, R. P.; Drapek, R. J.; Pitts, B. S.

2010-12-01

BIOMAP simulates competition between two Plant Functional Types (PFT) at any given point in the conterminous U.S. using a time series of daily temperature (mean, minimum, maximum), precipitation, humidity, light and nutrients, with PFT-specific rooting within a multi-layer soil. The model employs a 2-layer canopy biophysics, Farquhar photosynthesis, the Beer-Lambert Law for light attenuation and a mechanistic soil hydrology. In essence, BIOMAP is a re-built version of the biogeochemistry model, BIOME-BGC, into the form of the MAPSS biogeography model. Specific enhancements are: 1) the 2-layer canopy biophysics of Dolman (1993); 2) the unique MAPSS-based hydrology, which incorporates canopy evaporation, snow dynamics, infiltration and saturated and unsaturated percolation with ‘fast’ flow and base flow and a ‘tunable aquifer’ capacity, a metaphor of D’Arcy’s Law; and, 3) a unique MAPSS-based stomatal conductance algorithm, which simultaneously incorporates vapor pressure and soil water potential constraints, based on physiological information and many other improvements. Over small domains the PFTs can be parameterized as individual species to investigate fundamental vs. potential niche theory; while, at more coarse scales the PFTs can be rendered as more general functional groups. Since all of the model processes are intrinsically leaf to plot scale (physiology to PFT competition), it essentially has no ‘intrinsic’ scale and can be implemented on a grid of any size, taking on the characteristics defined by the homogeneous climate of each grid cell. Currently, the model is implemented on the VEMAP 1/2 degree, daily grid over the conterminous U.S. Although both the thermal and water-limited ecotones are dynamic, following climate variability, the PFT distributions remain fixed. Thus, the model is currently being fitted with a ‘reproduction niche’ to allow full dynamic operation as a Dynamic General Vegetation Model (DGVM). While global simulations of both climate and ecosystems must be done at coarse grid resolutions; smaller domains require higher resolution for the simulation of natural resource processes at the landscape scale and that of on-the-ground management practices. Via a combined multi-agency and private conservation effort we have implemented a Nested Scale Experiment (NeScE) that ranges from 1/2 degree resolution (global, ca. 50 km) to ca. 8km (North America) and 800 m (conterminous U.S.). Our first DGVM, MC1, has been implemented at all 3 scales. We are just beginning to implement BIOMAP into NeScE, with its unique features, and daily time step, as a counterpoint to MC1. We believe it will be more accurate at all resolutions providing better simulations of vegetation distribution, carbon balance, runoff, fire regimes and drought impacts.

Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.

2016-12-01

In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.

Variations in the Sea Ice Edge and the Marginal Ice Zone on Different Spatial Scales as Observed from Different Satellite Sensor

NASA Technical Reports Server (NTRS)

Markus, Thorsten; Henrichs, John

2006-01-01

The Marginal sea Ice Zone (MIZ) and the sea ice edge are the most dynamic areas of the sea ice cover. Knowledge of the sea ice edge location is vital for routing shipping in the polar regions. The ice edge is the location of recurrent plankton blooms, and is the habitat for a number of animals, including several which are under severe ecological threat. Polar lows are known to preferentially form along the sea ice edge because of induced atmospheric baroclinicity, and the ice edge is also the location of both vertical and horizontal ocean currents driven by thermal and salinity gradients. Finally, sea ice is both a driver and indicator of climate change and monitoring the position of the ice edge accurately over long time periods enables assessment of the impact of global and regional warming near the poles. Several sensors are currently in orbit that can monitor the sea ice edge. These sensors, though, have different spatial resolutions, different limitations, and different repeat frequencies. Satellite passive microwave sensors can monitor the ice edge on a daily or even twice-daily basis, albeit with low spatial resolution - 25 km for the Special Sensor Microwave Imager (SSM/I) or 12.5 km for the Advanced Microwave Scanning Radiometer (AMSR-E). Although special methods exist that allow the detection of the sea ice edge at a quarter of that nominal resolution (PSSM). Visible and infrared data from the Advanced Very High Resolution Radiometer (AVHRR) and from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide daily coverage at 1 km and 250 m, respectively, but the surface observations me limited to cloud-free periods. The Landsat 7 Enhanced Thematic Mapper (ETM+) has a resolution of 15 to 30 m but is limited to cloud-free periods as well, and does not provide daily coverage. Imagery from Synthetic Aperture Radar (SAR) instruments has resolutions of tens of meters to 100 m, and can be used to distinguish open water and sea ice on the basis of surface and volume scattering characteristics. The Canadian RADARSAT C-band SAR provides data that cover the Arctic Ocean and the MIZ every 3 days. A change-point detection approach was utilized to obtain an ice edge estimate from the RADARSAT data The Quickscat scatterometer provides ice edge information with a resolution of a few kilometers on a near-daily basis. During portions of March and April of 2003 a series of aircraft flights were conducted over the ice edge in the Bering Sea carrying the Polarimetric Scanning Radiometer (PSR), which provides spectral coverage identical with the AMSR-E instrument at a resolution of 500 meters. In this study we investigated these different data sets and analyzed differences in their definition of the sea ice edge and the marginal ice zone and how these differences as well as their individual limitations affect the monitoring of the ice edge dynamics. We also examined how the nature of the sea ice edge, including its location, compactness and shape, changes over the seasons. Our approach was based on calculation of distances between ice edges derived from the satellite and aircraft data sets listed above as well as spectral coherence methods and shape parameters such as tortuosity, curvature, and fractional dimension.

Global Precipitation at One-Degree Daily Resolution From Multi-Satellite Observations

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Morrissey, Mark M.; Curtis, Scott; Joyce, Robert; McGavock, Brad; Susskind, Joel

2000-01-01

The One-Degree Daily (1DD) technique is described for producing globally complete daily estimates of precipitation on a 1 deg x 1 deg lat/long grid from currently available observational data. Where possible (40 deg N-40 deg S), the Threshold-Matched Precipitation Index (TMPI) provides precipitation estimates in which the 3-hourly infrared brightness temperatures (IR T(sub b)) are thresholded and all "cold" pixels are given a single precipitation rate. This approach is an adaptation of the Geostationary Operational Environmental Satellite (GOES) Precipitation Index (GPI), but for the TMPI the IR Tb threshold and conditional rain rate are set locally by month from Special Sensor Microwave/Imager (SSM/I)-based precipitation frequency and the Global Precipitation Climatology Project (GPCP) satellite-gauge (SG) combined monthly precipitation estimate, respectively. At higher latitudes the 1DD features a rescaled daily Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) precipitation. The frequency of rain days in the TOVS is scaled down to match that in the TMPI at the data boundaries, and the resulting non-zero TOVS values are scaled locally to sum to the SG (which is a globally complete monthly product). The time series of the daily 1DD global images shows good continuity in time and across the data boundaries. Various examples are shown to illustrate uses. Validation for individual grid -box values shows a very high root-mean-square error but, it improves quickly when users perform time/space averaging according to their own requirements.

Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images

NASA Astrophysics Data System (ADS)

Hengl, Tomislav; Heuvelink, Gerard B. M.; Perčec Tadić, Melita; Pebesma, Edzer J.

2012-01-01

A computational framework to generate daily temperature maps using time-series of publicly available MODIS MOD11A2 product Land Surface Temperature (LST) images (1 km resolution; 8-day composites) is illustrated using temperature measurements from the national network of meteorological stations (159) in Croatia. The input data set contains 57,282 ground measurements of daily temperature for the year 2008. Temperature was modeled as a function of latitude, longitude, distance from the sea, elevation, time, insolation, and the MODIS LST images. The original rasters were first converted to principal components to reduce noise and filter missing pixels in the LST images. The residual were next analyzed for spatio-temporal auto-correlation; sum-metric separable variograms were fitted to account for zonal and geometric space-time anisotropy. The final predictions were generated for time-slices of a 3D space-time cube, constructed in the R environment for statistical computing. The results show that the space-time regression model can explain a significant part of the variation in station-data (84%). MODIS LST 8-day (cloud-free) images are unbiased estimator of the daily temperature, but with relatively low precision (±4.1°C); however their added value is that they systematically improve detection of local changes in land surface temperature due to local meteorological conditions and/or active heat sources (urban areas, land cover classes). The results of 10-fold cross-validation show that use of spatio-temporal regression-kriging and incorporation of time-series of remote sensing images leads to significantly more accurate maps of temperature than if plain spatial techniques were used. The average (global) accuracy of mapping temperature was ±2.4°C. The regression-kriging explained 91% of variability in daily temperatures, compared to 44% for ordinary kriging. Further software advancement—interactive space-time variogram exploration and automated retrieval, resampling and filtering of MODIS images—are anticipated.

The effect of horizontal resolution on simulation quality in the Community Atmospheric Model, CAM5.1

DOE PAGES

Wehner, Michael F.; Reed, Kevin A.; Li, Fuyu; ...

2014-10-13

We present an analysis of version 5.1 of the Community Atmospheric Model (CAM5.1) at a high horizontal resolution. Intercomparison of this global model at approximately 0.25°, 1°, and 2° is presented for extreme daily precipitation as well as for a suite of seasonal mean fields. In general, extreme precipitation amounts are larger in high resolution than in lower-resolution configurations. In many but not all locations and/or seasons, extreme daily precipitation rates in the high-resolution configuration are higher and more realistic. The high-resolution configuration produces tropical cyclones up to category 5 on the Saffir-Simpson scale and a comparison to observations revealsmore » both realistic and unrealistic model behavior. In the absence of extensive model tuning at high resolution, simulation of many of the mean fields analyzed in this study is degraded compared to the tuned lower-resolution public released version of the model.« less

Frequency of extreme daily temperatures (HadEX2) over Eurasia documented in a northern Red Sea coral oxygen isotope record during the last century

NASA Astrophysics Data System (ADS)

Ionita-Scholz, Monica; Felis, Thomas; Rimbu, Norel; Lohmann, Gerrit

2017-04-01

The potential of a bimonthly-resolved northern Red Sea coral δ18O record as an archive for the occurrence of extreme daily temperature phenomena over Eurasia during Northern Hemisphere winter is investigated for the 1901-1995 period using extreme indices provided by the HadEX2 dataset (e.g., frost days, ice days, cold nights and cold days). The coral δ18O record reflects a combined signal of temperature and salinity variations in the surface waters of the northern Red Sea, and has been previously shown to provide a proxy for atmospheric circulation changes over the Northern Hemisphere mid-latitudes at interannual to decadal time scales. Here we show, by applying composite analysis, that cooler/more arid (warmer/less arid) winter conditions in the northern Red Sea region, indicated by positive (negative) coral δ18O anomalies (January-February), are related to a strong (weak) Northern Hemisphere polar vortex and, as a consequence, to a decreased (increased) number of days characterized by very cold temperatures and frost over Scandinavia and Central Europe. This situation is associated with an increased (decreased) number of days characterized by very cold temperatures and frost over the Balkan region. The occurrence of these daily temperature extremes is modulated by the frequency of atmospheric blocking over the British Isles and Central Europe, and a shift in the direction of the North Atlantic storm tracks. Importantly, coral records provide a bimonthly to monthly resolution, compared to other high-resolution proxy records which have either an annual resolution (e.g., ice cores, varved sediments) or an annual resolution with a signal that is biased towards a specific season that in most cases is not winter (e.g., tree rings). We argue that bimonthly-resolved northern Red Sea coral δ18O records provide an archive of interannual to decadal variations in the occurrence of extreme daily temperature events over wintertime Eurasia prior to the start of instrumental observations.

Evaluation of sliding baseline methods for spatial estimation for cluster detection in the biosurveillance system

PubMed Central

Xing, Jian; Burkom, Howard; Moniz, Linda; Edgerton, James; Leuze, Michael; Tokars, Jerome

2009-01-01

Background The Centers for Disease Control and Prevention's (CDC's) BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of the daily disease monitoring task. Our study focused on finding useful anomalies at manageable alert rates according to available BioSense data history. Methods The study dataset included more than 3 years of daily counts of military outpatient clinic visits for respiratory and rash syndrome groupings. We applied four spatial estimation methods in implementations of space-time scan statistics cross-checked in Matlab and C. We compared the utility of these methods according to the resultant background cluster rate (a false alarm surrogate) and sensitivity to injected cluster signals. The comparison runs used a spatial resolution based on the facility zip code in the patient record and a finer resolution based on the residence zip code. Results Simple estimation methods that account for day-of-week (DOW) data patterns yielded a clear advantage both in background cluster rate and in signal sensitivity. A 28-day baseline gave the most robust results for this estimation; the preferred baseline is long enough to remove daily fluctuations but short enough to reflect recent disease trends and data representation. Background cluster rates were lower for the rash syndrome counts than for the respiratory counts, likely because of seasonality and the large scale of the respiratory counts. Conclusion The spatial estimation method should be chosen according to characteristics of the selected data streams. In this dataset with strong day-of-week effects, the overall best detection performance was achieved using subregion averages over a 28-day baseline stratified by weekday or weekend/holiday behavior. Changing the estimation method for particular scenarios involving different spatial resolution or other syndromes can yield further improvement. PMID:19615075

The ITSG-Grace2014 Gravity Field Model

NASA Astrophysics Data System (ADS)

Kvas, Andreas; Mayer-Gürr, Torsten; Zehenter, Norbert; Klinger, Beate

2015-04-01

The ITSG-Grace2014 GRACE-only gravity field model consists of a high resolution unconstrained static model (up to degree 200) with trend and annual signal, monthly unconstrained solutions with different spatial resolutions as well as daily snapshots derived by using a Kalman smoother. Apart from the estimated spherical harmonic coefficients, full variance-covariance matrices for the monthly solutions and the static gravity field component are provided. Compared to the previous release, multiple improvements in the processing chain are implemented: updated background models, better ionospheric modeling for GPS observations, an improved satellite attitude by combination of star camera and angular accelerations, estimation of K-band antenna center variations within the gravity field recovery process as well as error covariance function determination. Furthermore, daily gravity field variations have been modeled in the adjustment process to reduce errors caused by temporal leakage. This combined estimation of daily gravity variations field variations together with the static gravity field component represents a computational challenge due to the significantly increased parameter count. The modeling of daily variations up to a spherical harmonic degree of 40 for the whole GRACE observation period results in a system of linear equations with over 6 million unknown gravity field parameters. A least squares adjustment of this size is not solvable in a sensible time frame, therefore measures to reduce the problem size have to be taken. The ITSG-Grace2014 release is presented and selected parts of the processing chain and their effect on the estimated gravity field solutions are discussed.

An evaluation of terrain-based downscaling of fractional snow covered area data sets based on LiDAR-derived snow data and orthoimagery

NASA Astrophysics Data System (ADS)

Cristea, Nicoleta C.; Breckheimer, Ian; Raleigh, Mark S.; HilleRisLambers, Janneke; Lundquist, Jessica D.

2017-08-01

Reliable maps of snow-covered areas at scales of meters to tens of meters, with daily temporal resolution, are essential to understanding snow heterogeneity, melt runoff, energy exchange, and ecological processes. Here we develop a parsimonious downscaling routine that can be applied to fractional snow covered area (fSCA) products from satellite platforms such as the Moderate Resolution Imaging Spectroradiometer (MODIS) that provide daily ˜500 m data, to derive higher-resolution snow presence/absence grids. The method uses a composite index combining both the topographic position index (TPI) to represent accumulation effects and the diurnal anisotropic heat (DAH, sun exposure) index to represent ablation effects. The procedure is evaluated and calibrated using airborne-derived high-resolution data sets across the Tuolumne watershed, CA using 11 scenes in 2014 to downscale to 30 m resolution. The average matching F score was 0.83. We then tested our method's transferability in time and space by comparing against the Tuolumne watershed in water years 2013 and 2015, and over an entirely different site, Mt. Rainier, WA in 2009 and 2011, to assess applicability to other topographic and climatic conditions. For application to sites without validation data, we recommend equal weights for the TPI and DAH indices and close TPI neighborhoods (60 and 27 m for downscaling to 30 and 3 m, respectively), which worked well in both our study areas. The method is less effective in forested areas, which still requires site-specific treatment. We demonstrate that the procedure can even be applied to downscale to 3 m resolution, a very fine scale relevant to alpine ecohydrology research.

The impact of the resolution of meteorological datasets on catchment-scale drought studies

NASA Astrophysics Data System (ADS)

Hellwig, Jost; Stahl, Kerstin

2017-04-01

Gridded meteorological datasets provide the basis to study drought at a range of scales, including catchment scale drought studies in hydrology. They are readily available to study past weather conditions and often serve real time monitoring as well. As these datasets differ in spatial/temporal coverage and spatial/temporal resolution, for most studies there is a tradeoff between these features. Our investigation examines whether biases occur when studying drought on catchment scale with low resolution input data. For that, a comparison among the datasets HYRAS (covering Central Europe, 1x1 km grid, daily data, 1951 - 2005), E-OBS (Europe, 0.25° grid, daily data, 1950-2015) and GPCC (whole world, 0.5° grid, monthly data, 1901 - 2013) is carried out. Generally, biases in precipitation increase with decreasing resolution. Most important variations are found during summer. In low mountain range of Central Europe the datasets of sparse resolution (E-OBS, GPCC) overestimate dry days and underestimate total precipitation since they are not able to describe high spatial variability. However, relative measures like the correlation coefficient reveal good consistencies of dry and wet periods, both for absolute precipitation values and standardized indices like the Standardized Precipitation Index (SPI) or Standardized Precipitation Evaporation Index (SPEI). Particularly the most severe droughts derived from the different datasets match very well. These results indicate that absolute values of sparse resolution datasets applied to catchment scale might be critical to use for an assessment of the hydrological drought at catchment scale, whereas relative measures for determining periods of drought are more trustworthy. Therefore, studies on drought, that downscale meteorological data, should carefully consider their data needs and focus on relative measures for dry periods if sufficient for the task.

Validation of Satellite Snow Cover Maps in North America and Norway

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Solberg, Rune; Riggs, George A.

2002-01-01

Satellite-derived snow maps from NASA's Earth Observing System Moderate Resolution Imaging Spectroradiometer (MODIS) have been produced since February of 2000. The global maps are available daily at 500-m resolution, and at a climate-modeling grid (CMG) resolution of 1/20 deg (approximately 5.6 km). We compared the 8-day composite CMG MODIS-derived global maps from November 1,2001, through March 21,2002, and daily CMG maps from February 26 - March 5,2002, with National Oceanic and Atmospheric Administration (NOAA) Interactive Multisensor Snow and Ice Mapping System (IMS) 25-km resolution maps for North America. For the Norwegian study area, national snow maps, based on synoptic measurements as well as visual interpretation of AVHRR images, published by the Det Norske Meteorologiske Institutt (Norwegian Meteorological Institute) (MI) maps, as well as Landsat ETM+ images were compared with the MODIS maps. The MODIS-derived maps agreed over most areas with the IMS or MI maps, however, there are important areas of disagreement between the maps, especially when the 8-day composite maps were used. It is concluded that MODIS daily CMG maps should be studied for validation purposes rather than the 8-day composite maps, despite the limitations imposed by cloud obscuration when using the daily maps.

Towards High Spa-Temporal Resolution Estimates of Surface Radiative Fluxes from Geostationary Satellite Observations for the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Niu, X.; Yang, K.; Tang, W.; Qin, J.

2014-12-01

Surface Solar Radiation (SSR) plays an important role of the hydrological and land process modeling, which particularly contributes more than 90% to the total melt energy for the Tibetan Plateau (TP) ice melting. Neither surface measurement nor existing remote sensing products can meet that requirement in TP. The well-known satellite products (i.e. ISCCP-FD and GEWEX-SRB) are in relatively low spatial resolution (0.5º-2.5º) and temporal resolution (3-hourly, daily, or monthly). The objective of this study is to develop capabilities to improved estimates of SSR in TP based on geostationary satellite observations from the Multi-functional Transport Satellite (MTSAT) with high spatial (0.05º) and temporal (hourly) resolution. An existing physical model, the UMD-SRB (University of Maryland Surface Radiation Budget) which is the basis of the GEWEX-SRB model, is re-visited to improve SSR estimates in TP. The UMD-SRB algorithm transforms TOA radiances into broadband albedos in order to infer atmospheric transmissivity which finally determines the SSR. Specifically, main updates introduced in this study are: implementation at 0.05º spatial resolution at hourly intervals integrated to daily and monthly time scales; and improvement of surface albedo model by introducing the most recently developed Global Land Surface Broadband Albedo Product (GLASS) based on MODIS data. This updated inference scheme will be evaluated against ground observations from China Meteorological Administration (CMA) radiation stations and three TP radiation stations contributed from the Institute of Tibetan Plateau Research.

Burst Suppression on Processed Electroencephalography as a Predictor of Post-Coma Delirium in Mechanically Ventilated ICU Patients

PubMed Central

Andresen, Jennifer M.; Girard, Timothy D.; Pandharipande, Pratik P.; Davidson, Mario A.; Ely, E. Wesley; Watson, Paula L.

2015-01-01

Objectives Many patients, due to a combination of illness and sedatives, spend a considerable amount of time in a comatose state that can include time in burst suppression. We sought to determine if burst suppression measured by processed electroencephalography (pEEG) during coma in sedative-exposed patients is a predictor of post-coma delirium during critical illness. Design Observational convenience sample cohort Setting Medical and surgical ICUs in a tertiary care medical center Patients Cohort of 124 mechanically ventilated ICU patients Measurements and Main Results Depth of sedation was monitored twice daily using the Richmond Agitation-Sedation Scale and continuously monitored by pEEG. When non-comatose, patients were assessed for delirium twice daily using Confusion Assessment Method for the ICU (CAM-ICU). Multiple logistic regression and Cox proportional hazards regression were used to assess associations between time in burst suppression and both incidence and time to resolution of delirium, respectively, adjusting for time in deep sedation and a principal component score consisting of APACHE II score and cumulative doses of sedatives while comatose. Of the 124 patients enrolled and monitored, 55 patients either never had coma or never emerged from coma yielding 69 patients for whom we performed these analyses; 42 of these 69 (61%) had post-coma delirium. Most patients had burst-suppression during coma, though often short-lived [ median (intraquartile range) time in burst suppression, 6.4 (1-58) minutes]. After adjusting for covariates, even this short time in burst suppression independently predicted a higher incidence of post-coma delirium [odds ratio 4.16; 95% confidence interval (CI) 1.27-13.62; p=0.02] and a lower likelihood (delayed) resolution of delirium (hazard ratio 0.78; 95% CI 0.53-0.98; p=0.04). Conclusions Time in burst suppression during coma, as measured by processed EEG, was an independent predictor of incidence and time to resolution of post-coma/post-deep sedation delirium. These findings of this single center investigation support lighter sedation strategies. PMID:25072756

Precipitation extremes on multiple timescales - Bartlett-Lewis rectangular pulse model and intensity-duration-frequency curves

NASA Astrophysics Data System (ADS)

Ritschel, Christoph; Ulbrich, Uwe; Névir, Peter; Rust, Henning W.

2017-12-01

For several hydrological modelling tasks, precipitation time series with a high (i.e. sub-daily) resolution are indispensable. The data are, however, not always available, and thus model simulations are used to compensate. A canonical class of stochastic models for sub-daily precipitation are Poisson cluster processes, with the original Bartlett-Lewis (OBL) model as a prominent representative. The OBL model has been shown to well reproduce certain characteristics found in observations. Our focus is on intensity-duration-frequency (IDF) relationships, which are of particular interest in risk assessment. Based on a high-resolution precipitation time series (5 min) from Berlin-Dahlem, OBL model parameters are estimated and IDF curves are obtained on the one hand directly from the observations and on the other hand from OBL model simulations. Comparing the resulting IDF curves suggests that the OBL model is able to reproduce the main features of IDF statistics across several durations but cannot capture rare events (here an event with a return period larger than 1000 years on the hourly timescale). In this paper, IDF curves are estimated based on a parametric model for the duration dependence of the scale parameter in the generalized extreme value distribution; this allows us to obtain a consistent set of curves over all durations. We use the OBL model to investigate the validity of this approach based on simulated long time series.

A Gridded Daily Min/Max Temperature Dataset With 0.1° Resolution for the Yangtze River Valley and its Error Estimation

NASA Astrophysics Data System (ADS)

Xiong, Qiufen; Hu, Jianglin

2013-05-01

The minimum/maximum (Min/Max) temperature in the Yangtze River valley is decomposed into the climatic mean and anomaly component. A spatial interpolation is developed which combines the 3D thin-plate spline scheme for climatological mean and the 2D Barnes scheme for the anomaly component to create a daily Min/Max temperature dataset. The climatic mean field is obtained by the 3D thin-plate spline scheme because the relationship between the decreases in Min/Max temperature with elevation is robust and reliable on a long time-scale. The characteristics of the anomaly field tend to be related to elevation variation weakly, and the anomaly component is adequately analyzed by the 2D Barnes procedure, which is computationally efficient and readily tunable. With this hybridized interpolation method, a daily Min/Max temperature dataset that covers the domain from 99°E to 123°E and from 24°N to 36°N with 0.1° longitudinal and latitudinal resolution is obtained by utilizing daily Min/Max temperature data from three kinds of station observations, which are national reference climatological stations, the basic meteorological observing stations and the ordinary meteorological observing stations in 15 provinces and municipalities in the Yangtze River valley from 1971 to 2005. The error estimation of the gridded dataset is assessed by examining cross-validation statistics. The results show that the statistics of daily Min/Max temperature interpolation not only have high correlation coefficient (0.99) and interpolation efficiency (0.98), but also the mean bias error is 0.00 °C. For the maximum temperature, the root mean square error is 1.1 °C and the mean absolute error is 0.85 °C. For the minimum temperature, the root mean square error is 0.89 °C and the mean absolute error is 0.67 °C. Thus, the new dataset provides the distribution of Min/Max temperature over the Yangtze River valley with realistic, successive gridded data with 0.1° × 0.1° spatial resolution and daily temporal scale. The primary factors influencing the dataset precision are elevation and terrain complexity. In general, the gridded dataset has a relatively high precision in plains and flatlands and a relatively low precision in mountainous areas.

Glacial Boundary Features Delineated Using Enhanced-resolution Passive-microwave Data to Determine Melt Season Variation of the Vatnajokull Ice Cap, Iceland

NASA Astrophysics Data System (ADS)

Marzillier, D. M.; Ramage, J. M.

2017-12-01

Temperate glaciers such as those seen in Iceland experience high annual mass flux, thereby responding to small scale changes in Earth's climate. Decadal changes in the glacial margins of Iceland's ice caps are observable in the Landsat record, however twice daily AMSR-E Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) allow for observation on a daily temporal scale and a 3.125 km spatial scale, which can in turn be connected to patterns seen over longer periods of time. Passive microwave data allow for careful observation of melt onset and duration in Iceland's glacial regions by recording changes in emissivity of the ice surface, known as brightness temperature (TB), which is sensitive to fluctuations in the liquid water content of snow and ice seen during melting in glaciated regions. Enhanced resolution of this data set allows for a determination of a threshold that defines the melting season. The XPGR snowmelt algorithm originally presented by Abdalati and Steffen (1995) is used as a comparison with the diurnal amplitude variation (DAV) values on Iceland's Vatnajokull ice cap located at 64.4N, -16.8W. Ground-based air temperature data in this region, digital elevation models (DEMs), and river discharge dominated by glacial runoff are used to confirm the glacial response to changes in global climate. Results show that Iceland glaciers have a bimodal distribution of brightness temperature delineating when the snow/ice is melting and refreezing. Ground based temperatures have increased on a decadal trend. Clear glacial boundaries are visible on the passive microwave delineating strong features, and we are working to understand their variability and contribution to glacier evolution. The passive microwave data set allows connections to be made between observations seen on a daily scale and the long term glacier changes observed by the Landsat satellite record that integrates the overall glacier changes.

Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Skidmore, Andrew K.; Wang, Tiejun; Meroni, Michele; Ens, Bruno J.; Oosterbeek, Kees; O'Connor, Brian; Darvishzadeh, Roshanak; Heurich, Marco; Shepherd, Anita; Paganini, Marc

2017-07-01

Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250 m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30 m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5 m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLI data, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels due to cloud cover around phenological transition dates. The Proba-V and MODIS phenology retrievals scaled poorly relative to their high-resolution equivalents, indicating that medium-resolution phenology retrievals need to be interpreted with care, particularly in landscapes with fine-scale land cover variability.

The Climate Hazards group InfraRed Precipitation (CHIRP) with Stations (CHIRPS): Development and Validation

NASA Astrophysics Data System (ADS)

Peterson, P.; Funk, C. C.; Husak, G. J.; Pedreros, D. H.; Landsfeld, M.; Verdin, J. P.; Shukla, S.

2013-12-01

CHIRP and CHIRPS are new quasi-global precipitation products with daily to seasonal time scales, a 0.05° resolution, and a 1981 to near real-time period of record. Developed by the Climate Hazards Group at UCSB and scientists at the U.S. Geological Survey Earth Resources Observation and Science Center specifically for drought early warning and environmental monitoring, CHIRPS provides moderate latency precipitation estimates that place observed hydrologic extremes in their historic context. Three main types of information are used in the CHIRPS: (1) global 0.05° precipitation climatologies, (2) time-varying grids of satellite-based precipitation estimates, and (3) in situ precipitation observations. CHIRP: The global grids of long-term (1980-2009) average precipitation were estimated for each month based on station data, averaged satellite observations, and physiographic parameters. 1981-present time-varying grids of satellite precipitation were derived from spatially varying regression models based on pentadal cold cloud duration (CCD) values and TRMM V7 training data. The CCD time-series were derived from the CPC and NOAA B1 datasets. Pentadal CCD-percent anomaly values were multiplied by pentadal climatology fields to produce low bias pentadal precipitation estimates. CHIRPS: The CHG station blending procedure uses the satellite-observed spatial covariance structure to assign relative weights to neighboring stations and the CHIRP values. The CHIRPS blending procedure is based on the expected correlation between precipitation at a given target location and precipitation at the locations of the neighboring observation stations. These correlations are estimated using the CHIRP fields. The CHG has developed an extensive archive of in situ daily, pentadal and monthly precipitation totals. The CHG database has over half a billion daily rainfall observations since 1980 and another half billion before 1980. Most of these observations come from four sets of global climate observations: the monthly Global Historical Climate Network version 2 archive, the daily Global Historical Climate Network archive, the Global Summary of the Day dataset (GSOD), and the daily Global Telecommunication System (GTS) archive provided by NOAA's Climate Prediction Center (CPC). A screening procedure was developed to flag and remove potential false zeros from the daily data, since these potentially spurious data can artificially suppress rainfall totals. Validation: Our validation focused on precipitation products with global coverage, long periods of record and near real-time availability: CHIRP, CHIRPS, CPC-Unified, CFS Reanalysis and ECMWF datasets were compared to GPCC and high quality datasets from Uganda, Colombia and the Sahel. The CHIRP and CHIRPS are shown to have low systematic errors (bias) and low mean absolute errors. Analyses in Uganda, Colombia and the Sahel indicate that the ECMWF, CPC-Unified and CFS-Reanalysis have large inhomogeneities, making them unsuitable for drought monitoring. The CHIRPS performance appears quite similar to research quality products like the GPCC and GPCP, but with higher resolution and lower latency.

Expanding the Estimation of Surface PM2.5 from Aqua and Terra MODIS Aerosol Optical Depth in the EPA's AirNow Satellite Data Processor to Suomi NPP VIIRS

NASA Astrophysics Data System (ADS)

Szykman, J.; Kondragunta, S.; Zhang, H.; Dickerson, P.; van Donkelaar, A.; Martin, R. V.; Pasch, A. N.; White, J. E.; DeWinter, J. L.; Zahn, P. H.; Dye, T. S.; Haderman, M. D.

2012-12-01

The U.S. Environmental Protection Agency's (EPA) Air Quality Index (AQI) relies on hourly measurements of ground-based surface PM2.5 (particles smaller than 2.5 μm in median diameter) to develop daily AQI index maps. The EPA is improving the accuracy of AQI information and extending its coverage for reporting to the public by incorporating National Aeronautics and Space Administration (NASA) satellite-derived surface PM2.5 concentrations into daily AQI maps. The additional coverage will provide air quality information in regions without dense monitoring networks. The AirNow Satellite Data Processor (ASDP) uses daily PM2.5 estimates and uncertainties derived from average Aqua and Terra MODerate resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) in near real-time over the United States. The algorithm to derive surface PM2.5 from MODIS AOD relies on linear relationships between AOD and PM2.5 generated from multi-year GEOS-Chem model simulations (van Donkelaar et al., 2012). Parameters from the regression equation (slopes and intercepts) are saved in a lookup table (LUT) with 4 km spatial resolution for each day of a given year. To improve data accuracy and continuity, a filter is applied to remove MODIS AOD with low accuracy (e.g., over bright surfaces) and an inverse distance weighted average is applied to fill in gaps created by cloud coverage. Daily surface PM2.5 estimates and their uncertainties are generated at the National Oceanic and Atmospheric Administration (NOAA) using the van Donkelaar et al. algorithm and near real-time MODIS AOD products from Terra and Aqua and are provided to the EPA through its Infusing satellite Data into Environmental Applications (IDEA) website. The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on October 28, 2011, and similar to MODIS, provides AOD products for real-time applications. NOAA plans to explore the value of VIIRS AOD products to improve AQI. This presentation will focus on a description of ASDP, including an overview of the algorithm used to estimate surface PM2.5 using satellite data and examples of high resolution VIIRS AOD products and their value to the ASDP. Disclaimer: Although this work was reviewed by the U.S. Environmental Protection Agency and approved for publication, it may not necessarily reflect official Agency policy.

Global Monitoring of Air Pollution Using Spaceborne Sensors

NASA Technical Reports Server (NTRS)

Chu, D. A.; Kaufman, Y. J.; Tanre, D.; Remer, L. A.; Einaudi, Franco (Technical Monitor)

2000-01-01

The MODIS sensor onboard EOS-Terra satellite provides not only daily global coverage but also high spectral (36 channels from 0.41 to 14 microns wavelength) and spatial (250m, 500m and 1km) resolution measurements. A similar MODIS instrument will be also configured into EOS-Aqua satellite to be launched soon. Using the complementary EOS-Terra and EOS-Aqua sun-synchronous orbits (10:30 AM and 1:30 PM equator-crossing time respectively), it enables us also to study the diurnal changes of the Earth system. It is unprecedented for the derivation of aerosol properties with such high spatial resolution and daily global converge. Aerosol optical depth and other aerosol properties, e.g., Angstrom coefficient over land and particle size over ocean, are derived as standard products at a spatial resolution of 10 x 10 sq km. The high resolution results are found surprisingly useful in detecting aerosols in both urban and rural regions as a result of urban/industrial pollution and biomass burning. For long-lived aerosols, the ability to monitoring the evolution of these aerosol events could help us to establish an system of air quality especially for highly populated areas. Aerosol scenarios with city pollution and biomass burning will be presented. Also presented are the method used in the derivation of aerosol optical properties and preliminary results will be presented, and issue as well as obstacles in validating aerosol optical depth with AERONET ground-based observations.

Variations in atmospheric angular momentum and the length of day

NASA Technical Reports Server (NTRS)

Rosen, R. D.; Salstein, D. A.

1982-01-01

Six years of twice daily global analyses were used to create and study a lengthy time series of high temporal resolution angular momentum values. Changes in these atmospheric values were compared to independently determined charges in the rotation rate of the solid Earth. Finally, the atmospheric data was examined in more detail to determine the time and space scales on which variations in momentum occur within the atmosphere and which regions are contributing most to the changes found in the global integral. The data and techniques used to derive the time series of momentum values are described.

Hydrology of the Niger River from Nimbus HRIR

NASA Technical Reports Server (NTRS)

Macleod, N. H.

1972-01-01

The seasonal changes in aspect of the Niger River in the Republic of Mali, West Africa, as seen in daytime imagery obtained by the high-resolution infrared radiometer on Nimbus 3 are described. The identification of different plants by their reflectance is shown to provide an ecological map that changes with time. It is concluded that Nimbus imagery provides an integrated view of the entire watershed on a daily basis.

Phenological monitoring of Acadia National Park using Landsat, MODIS and VIIRS observations and fused data

NASA Astrophysics Data System (ADS)

Liu, Y.; McDonough MacKenzie, C.; Primack, R.; Zhang, X.; Schaaf, C.; Sun, Q.; Wang, Z.

2015-12-01

Monitoring phenology with remotely sensed data has become standard practice in large-plot agriculture but remains an area of research in complex terrain. Landsat data (30m) provides a more appropriate spatial resolution to describe such regions but may only capture a few cloud-free images over a growing period. Daily data from the MODerate resolution Imaging Spectroradiometer(MODIS) and Visible Infrared Imaging Radiometer Suite(VIIRS) offer better temporal acquisitions but at coarse spatial resolutions of 250m to 1km. Thus fused data sets are being employed to provide the temporal and spatial resolutions necessary to accurately monitor vegetation phenology. This study focused on Acadia National Park, Maine, attempts to compare green-up from remote sensing and ground observations over varying topography. Three north-south field transects were established in 2013 on parallel mountains. Along these transects, researchers record the leaf out and flowering phenology for thirty plant species biweekly. These in situ spring phenological observations are compared with the dates detected by Landsat 7, Landsat 8, MODIS, and VIIRS observations, both separately and as fused data, to explore the ability of remotely sensed data to capture the subtle variations due to elevation. Daily Nadir BRDF Adjusted Reflectances(NBAR) from MODIS and VIIRS are fused with Landsat imagery to simulate 30m daily data via the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model(ESTARFM) algorithm. Piecewise logistic functions are fit to the time series to establish spring leaf-out dates. Acadia National Park, a region frequently affected by coastal clouds, is a particularly useful study area as it falls in a Landsat overlap region and thus offers the possibility of acquiring as many as 4 Landsat observations in a 16 day period. With the recent launch of Sentinel 2A, the community will have routine access to such high spatial and temporal data for phenological monitoring.

Regional model simulations of New Zealand climate

NASA Astrophysics Data System (ADS)

Renwick, James A.; Katzfey, Jack J.; Nguyen, Kim C.; McGregor, John L.

1998-03-01

Simulation of New Zealand climate is examined through the use of a regional climate model nested within the output of the Commonwealth Scientific and Industrial Research Organisation nine-level general circulation model (GCM). R21 resolution GCM output is used to drive a regional model run at 125 km grid spacing over the Australasian region. The 125 km run is used in turn to drive a simulation at 50 km resolution over New Zealand. Simulations with a full seasonal cycle are performed for 10 model years. The focus is on the quality of the simulation of present-day climate, but results of a doubled-CO2 run are discussed briefly. Spatial patterns of mean simulated precipitation and surface temperatures improve markedly as horizontal resolution is increased, through the better resolution of the country's orography. However, increased horizontal resolution leads to a positive bias in precipitation. At 50 km resolution, simulated frequency distributions of daily maximum/minimum temperatures are statistically similar to those of observations at many stations, while frequency distributions of daily precipitation appear to be statistically different to those of observations at most stations. Modeled daily precipitation variability at 125 km resolution is considerably less than observed, but is comparable to, or exceeds, observed variability at 50 km resolution. The sensitivity of the simulated climate to changes in the specification of the land surface is discussed briefly. Spatial patterns of the frequency of extreme temperatures and precipitation are generally well modeled. Under a doubling of CO2, the frequency of precipitation extremes changes only slightly at most locations, while air frosts become virtually unknown except at high-elevation sites.

Spatial and temporal remote sensing data fusion for vegetation monitoring

USDA-ARS?s Scientific Manuscript database

The suite of available remote sensing instruments varies widely in terms of sensor characteristics, spatial resolution and acquisition frequency. For example, the Moderate-resolution Imaging Spectroradiometer (MODIS) provides daily global observations at 250m to 1km spatial resolution. While imagery...

Full-Coverage High-Resolution Daily PM(sub 2.5) Estimation using MAIAC AOD in the Yangtze River Delta of China

NASA Technical Reports Server (NTRS)

Xiao, Qingyang; Wang, Yujie; Chang, Howard H.; Meng, Xia; Geng, Guannan; Lyapustin, Alexei Ivanovich; Liu, Yang

2017-01-01

Satellite aerosol optical depth (AOD) has been used to assess population exposure to fine particulate matter (PM (sub 2.5)). The emerging high-resolution satellite aerosol product, Multi-Angle Implementation of Atmospheric Correction(MAIAC), provides a valuable opportunity to characterize local-scale PM(sub 2.5) at 1-km resolution. However, non-random missing AOD due to cloud snow cover or high surface reflectance makes this task challenging. Previous studies filled the data gap by spatially interpolating neighboring PM(sub 2.5) measurements or predictions. This strategy ignored the effect of cloud cover on aerosol loadings and has been shown to exhibit poor performance when monitoring stations are sparse or when there is seasonal large-scale missngness. Using the Yangtze River Delta of China as an example, we present a Multiple Imputation (MI) method that combines the MAIAC high-resolution satellite retrievals with chemical transport model (CTM) simulations to fill missing AOD. A two-stage statistical model driven by gap-filled AOD, meteorology and land use information was then fitted to estimate daily ground PM(sub 2.5) concentrations in 2013 and 2014 at 1 km resolution with complete coverage in space and time. The daily MI models have an average R(exp 2) of 0.77, with an inter-quartile range of 0.71 to 0.82 across days. The overall Ml model 10-fold cross-validation R(exp 2) (root mean square error) were 0.81 (25 gm(exp 3)) and 0.73 (18 gm(exp 3)) for year 2013 and 2014, respectively. Predictions with only observational AOD or only imputed AOD showed similar accuracy.Comparing with previous gap-filling methods, our MI method presented in this study performed bette rwith higher coverage, higher accuracy, and the ability to fill missing PM(sub 2.5) predictions without ground PM(sub 2.5) measurements. This method can provide reliable PM(sub 2.5)predictions with complete coverage that can reduce biasin exposure assessment in air pollution and health studies.

Refining surface net radiation estimates in arid and semi-arid climates of Iran

NASA Astrophysics Data System (ADS)

Golkar, Foroogh; Rossow, William B.; Sabziparvar, Ali Akbar

2018-06-01

Although the downwelling fluxes exhibit space-time scales of dependency on characteristic of atmospheric variations, especially clouds, the upward fluxes and, hence the net radiation, depends on the variation of surface properties, particularly surface skin temperature and albedo. Evapotranspiration at the land surface depends on the properties of that surface and is determined primarily by the net surface radiation, mostly absorbed solar radiation. Thus, relatively high spatial resolution net radiation data are needed for evapotranspiration studies. Moreover, in more arid environments, the diurnal variations of surface (air and skin) temperature can be large so relatively high (sub-daily) time resolution net radiation is also needed. There are a variety of radiation and surface property products available but they differ in accuracy, space-time resolution and information content. This situation motivated the current study to evaluate multiple sources of information to obtain the best net radiation estimate with the highest space-time resolution from ISCCP FD dataset. This study investigates the accuracy of the ISCCP FD and AIRS surface air and skin temperatures, as well as the ISCCP FD and MODIS surface albedos and aerosol optical depths as the leading source of uncertainty in ISCCP FD dataset. The surface air temperatures, 10-cm soil temperatures and surface solar insolation from a number of surface sites are used to judge the best combinations of data products, especially on clear days. The corresponding surface skin temperatures in ISCCP FD, although they are known to be biased somewhat high, disagreed more with AIRS measurements because of the mismatch of spatial resolutions. The effect of spatial resolution on the comparisons was confirmed using the even higher resolution MODIS surface skin temperature values. The agreement of ISCCP FD surface solar insolation with surface measurements is good (within 2.4-9.1%), but the use of MODIS aerosol optical depths as an alternative was checked and found to not improve the agreement. The MODIS surface albedos differed from the ISCCP FD values by no more than 0.02-0.07, but because these differences are mostly at longer wavelengths, they did not change the net solar radiation very much. Therefore to obtain the best estimate of surface net radiation with the best combination of spatial and temporal resolution, we developed a method to adjust the ISCCP FD surface longwave fluxes using the AIRS surface air and skin temperatures to obtain the higher spatial resolution of the latter (45 km), while retaining the 3-h time intervals of the former. Overall, the refinements reduced the ISCCP FD longwave flux magnitudes by about 25.5-42.1 W/m2 RMS (maximum difference -27.5 W/m2 for incoming longwave radiation and -59 W/m2 for outgoing longwave radiation) with the largest differences occurring at 9:00 and 12:00 UTC near local noon. Combining the ISCCP FD net shortwave radiation data and the AIRS-modified net longwave radiation data changed the total net radiation for summertime by 4.64 to 61.5 W/m2 and for wintertime by 1.06 to 41.88 W/m2 (about 11.1-39.2% of the daily mean).

A stochastical event-based continuous time step rainfall generator based on Poisson rectangular pulse and microcanonical random cascade models

NASA Astrophysics Data System (ADS)

Pohle, Ina; Niebisch, Michael; Zha, Tingting; Schümberg, Sabine; Müller, Hannes; Maurer, Thomas; Hinz, Christoph

2017-04-01

Rainfall variability within a storm is of major importance for fast hydrological processes, e.g. surface runoff, erosion and solute dissipation from surface soils. To investigate and simulate the impacts of within-storm variabilities on these processes, long time series of rainfall with high resolution are required. Yet, observed precipitation records of hourly or higher resolution are in most cases available only for a small number of stations and only for a few years. To obtain long time series of alternating rainfall events and interstorm periods while conserving the statistics of observed rainfall events, the Poisson model can be used. Multiplicative microcanonical random cascades have been widely applied to disaggregate rainfall time series from coarse to fine temporal resolution. We present a new coupling approach of the Poisson rectangular pulse model and the multiplicative microcanonical random cascade model that preserves the characteristics of rainfall events as well as inter-storm periods. In the first step, a Poisson rectangular pulse model is applied to generate discrete rainfall events (duration and mean intensity) and inter-storm periods (duration). The rainfall events are subsequently disaggregated to high-resolution time series (user-specified, e.g. 10 min resolution) by a multiplicative microcanonical random cascade model. One of the challenges of coupling these models is to parameterize the cascade model for the event durations generated by the Poisson model. In fact, the cascade model is best suited to downscale rainfall data with constant time step such as daily precipitation data. Without starting from a fixed time step duration (e.g. daily), the disaggregation of events requires some modifications of the multiplicative microcanonical random cascade model proposed by Olsson (1998): Firstly, the parameterization of the cascade model for events of different durations requires continuous functions for the probabilities of the multiplicative weights, which we implemented through sigmoid functions. Secondly, the branching of the first and last box is constrained to preserve the rainfall event durations generated by the Poisson rectangular pulse model. The event-based continuous time step rainfall generator has been developed and tested using 10 min and hourly rainfall data of four stations in North-Eastern Germany. The model performs well in comparison to observed rainfall in terms of event durations and mean event intensities as well as wet spell and dry spell durations. It is currently being tested using data from other stations across Germany and in different climate zones. Furthermore, the rainfall event generator is being applied in modelling approaches aimed at understanding the impact of rainfall variability on hydrological processes. Reference Olsson, J.: Evaluation of a scaling cascade model for temporal rainfall disaggregation, Hydrology and Earth System Sciences, 2, 19.30

A downscaled 1 km dataset of daily Greenland ice sheet surface mass balance components (1958-2014)

NASA Astrophysics Data System (ADS)

Noel, B.; Van De Berg, W. J.; Fettweis, X.; Machguth, H.; Howat, I. M.; van den Broeke, M. R.

2015-12-01

The current spatial resolution in regional climate models (RCMs), typically around 5 to 20 km, remains too coarse to accurately reproduce the spatial variability in surface mass balance (SMB) components over the narrow ablation zones, marginal outlet glaciers and neighbouring ice caps of the Greenland ice sheet (GrIS). In these topographically rough terrains, the SMB components are highly dependent on local variations in topography. However, the relatively low-resolution elevation and ice mask prescribed in RCMs contribute to significantly underestimate melt and runoff in these regions due to unresolved valley glaciers and fjords. Therefore, near-km resolution topography is essential to better capture SMB variability in these spatially restricted regions. We present a 1 km resolution dataset of daily GrIS SMB covering the period 1958-2014, which is statistically downscaled from data of the polar regional climate model RACMO2.3 at 11 km, using an elevation dependence. The dataset includes all individual SMB components projected on the elevation and ice mask from the GIMP DEM, down-sampled to 1 km. Daily runoff and sublimation are interpolated to the 1 km topography using a local regression to elevation valid for each day specifically; daily precipitation is bi-linearly downscaled without elevation corrections. The daily SMB dataset is then reconstructed by summing downscaled precipitation, sublimation and runoff. High-resolution elevation and ice mask allow for properly resolving the narrow ablation zones and valley glaciers at the GrIS margins, leading to significant increase in runoff estimate. In these regions, and especially over narrow glaciers tongues, the downscaled products improve on the original RACMO2.3 outputs by better representing local SMB patterns through a gradual ablation increase towards the GrIS margins. We discuss the impact of downscaling on the SMB components in a case study for a spatially restricted region, where large elevation discrepancies are observed between both resolutions. Owing to generally enhanced runoff in the GrIS ablation zone, the evaluation of daily downscaled SMB against ablation measurements, collected at in-situ measuring sites derived from a newly compiled ablation dataset, shows a better agreement with observations relative to native RACMO2.3 SMB at 11 km.

PREGRIDBAL 1.0: towards a high-resolution rainfall atlas for the Balearic Islands (1950-2009)

NASA Astrophysics Data System (ADS)

López Mayol, Toni; Homar, Víctor; Ramis, Climent; Guijarro, José Antonio

2017-07-01

This work presents a catalog of daily precipitation fields in the Balearic Islands created with data from AEMET (State Meteorological Agency) assistant observations, including records from 1912. The original digital daily data file has been interpolated onto a regular 100 m-resolution grid (namely PREGRIDBAL), defined with the aim of becoming a valid standard for future methodological improvements and catalog upgrades. Daily precipitation amounts on each grid point are calculated using an analysis method based on ordinary kriging, using the daily anomaly with respect to the annual mean for all available observations each day. Due to quality concerns, the time span for products derived from the catalog is limited to the 1950-2009 period, when the number of operating stations reached 200. Therefore, from the time series of daily maps, monthly-, annual-, quinquennial-, and decadal-accumulations are produced. Similarly, the catalog allowed for quantification of climate trends in rainfall amounts in the Balearic Islands, with the significant advantage of minimizing the biases originated from heterogeneities in the spatial distribution of stations across the archipelago. Results show a general decrease in precipitation during the 1950-2009 period. From 1950 to 1979, the average annual precipitation across the islands was 624.3 mm, while from 1980 to 2009 it diminished to 555.36 mm. Changes in precipitation patterns, which vary among the different areas, are also detected. The most significant reductions are found in the northern half of the archipelago and especially in Mallorca, where the Tramuntana mountain range stands out. All seasonal trends show a decrease, with values ranging between 1 and 3 mm decade-1, with the exception of autumn, which reaches a positive trend up to 7 mm decade-1. October shows the most dramatic decrease (-10. 34 mm decade-1) and, conversely, September and November show an increase in precipitation (3.28 and 1.82 mm decade-1, respectively) with a statistical significance above 85 % across almost the entire archipelago, and even exceeding 95 % in Eivissa and Formentera.

Daily tympanometry for high-resolution measurement of the time between onset of cold-like illness and middle ear effusion.

PubMed

Doyle, William J; Winther, Birgit; Alper, Cuneyt M

2008-06-01

Tympanometry is a simple method to assess middle ear pressure (MEP) and the presence of middle ear effusion (MEE), a marker of otitis media (OM). To determine whether daily parental tympanometry and illness sign recording in their children can be used to define the time between onsets of cold-like illness (CLI) and MEE at high resolution. Prospective, longitudinal, 7 month, daily follow-up on 169 children aged 1 through 8.6 years. Tympanograms and illness were recorded daily by a parent. Tympanograms were examined, rejected if artifactual, and MEP data were entered into a database, with "flat tympanograms" coded as -400 mm H2O = MEE. The incidence and burden of CLIs (>2 days) were calculated, and for each CLI, the presence/absence of concurrent MEE (>2 days) was determined. For each child, the average MEP for CLI and nonCLI days was calculated. Paired CLI and tympanometric results were aligned and the days between event onsets determined. Stepwise regression was used to assign risk predictors for the measured outcomes. A total of 566 CLIs were recorded, and the average CLI burden/child was 16%. Age was a significant predictor of CLI incidence/child, and age, history of colds, and daily environment were predictors of CLI-burden/child. Of the 433 evaluable CLI episodes, MEE was a complication in 37%, and MEE with a CLI was predicted by age, OM history, and environment. MEP was significantly more negative during CLI episodes, and the magnitude was predicted by age, race, and OM history. The average difference in MEE-CLI onsets was 1.2 +/- 4.0 days; approximately 32% of MEEs occurred prior to CLI onset and 17% on the same day as CLI onset. CLIs adversely affect the middle ear-ambient pressure balance and are frequently associated with MEE episodes. The distribution in onsets between those events suggests that chemoprophylaxis of a child with a newly identified CLI to prevent MEE would have a low expected efficiency.

The Hydrometeorological DREAM: A Daily REcharge Assessment Model, for the Israeli Western Mountain Aquifer

NASA Astrophysics Data System (ADS)

Sheffer, N. A.; Dafny, E.; Gvirtzman, H.; Frumkin, A.; Navon, S.; Morin, E.

2008-05-01

The western part of the Israeli Mountain Aquifer (WMA) supplies 360-400 MCM/y of fresh water to the Israeli water budget, which is approximately 20% of the total consumption. The annually recharge to the WMA is considered to be 25-35% of annual rainfall. The high variability in recharge to the WMA is due to spatial and temporal differences in the rain contributing to the aquifer. Different winters producing the same amount of rain may contribute differently to the aquifer due to the locations of the storms, intensity, duration, dry spells between successive rain events, etc. Moreover, besides the climatic-meteorological factors, the recharge is dependent also on geographical factors, such as lithology, pedology, land-use, slope gradient, slope direction etc. The need for a robust reliable Hydrometeorological Daily basis REcharge Assessment Model (Hydrometeorological DREAM) brought us to develop a model with a relatively high spatial and temporal resolution. The concept is based on a relatively simple water budget that states that rainfall over land is added to the soil, and removed later on by means of evapotranspiration, recharge and runoff. The method in use to date at the Hydrological Service for estimating recharge to the WMA is based on an annual regression curve that can be implemented only after the total annual rainfall is known. The DREAM is a near real time estimator of recharge to the WMA using daily rainfall and pan evaporation data. Comparison of the DREAM results with the annual regression curve show a high agreement on an annual basis. The improvements introduced by the DREAM are: 1) Near real time daily values of infiltration, as opposed to calculated annual values established after the rain season is over. 2) High spatial resolution. The DREAM produces daily recharge values in more than 3000 mesh points throughout the 2200 km2 of recharge area. By linking the DREAM output as input to a hydrogeological model (such as FEFLOW, MODFLOW etc.) a completion of the water cycle can by achieved.

Impact of MODIS High-Resolution Sea-Surface Temperatures on WRF Forecasts at NWS Miami, FL

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaCasse, Katherine M.; Dembek, Scott R.; Santos, Pablo; Lapenta, William M.

2007-01-01

Over the past few years,studies at the Short-term Prediction Research and Transition (SPoRT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) composite sea-surface temperature (SST) products in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. The recent paper by LaCasse et al. (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPoRT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The scientific hypothesis being tested is: More accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running the WRF system in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software; The EMS is a standalone modeling system capable of downloading the necessary daily datasets, and initializing, running and displaying WRF forecasts in the NWS Advanced Weather Interactive Processing System (AWIPS) with little intervention required by forecasters. Twenty-seven hour forecasts are run daily with start times of 0300,0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and the far western portions of the Bahamas, the Florida Keys, the Straights of Florida, and adjacent waters of the Gulf of Mexico and Atlantic Ocean. Each model run is initialized using the Local Analysis and Prediction System (LAPS) analyses available in AWIPS, invoking the diabatic. "hot-start" capability. In this WRF model "hot-start", the LAPS-analyzed cloud and precipitation features are converted into model microphysics fields with enhanced vertical velocity profiles, effectively reducing the model spin-up time required to predict precipitation systems. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at l/12 degree resolution (approx. 9 km); however, the RTG product does not exhibit fine-scale details consistent with its grid resolution. SPoRT is conducting parallel WRF EMS runs identical to the operational runs at NWS MIA in every respect except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water. The MODIS SST composites for initializing the SPoRT WRF runs are generated on a 2-km grid four times daily at 0400, 0700, 1600, and 1900 UTC, based on the times of the overhead passes of the Aqua and Terra satellites. The incorporation of the MODIS SST composites into the SPoRTWRF runs is staggered such that the 0400UTC composite initializes the 0900 UTC WRF, the 0700 UTC composite initializes the 1500 UTC WRF, the 1600 UTC composite initializes the 2100 UTC WRF, and the 1900 UTC composite initializes the 0300 UTC WRF. A comparison of the SPoRT and Miami forecasts is underway in 2007, and includes quantitative verification of near-surface temperature, dewpoint, and wind forecasts at surface observation locations. In addition, particular days of interest are being analyzed to determine the impact of the MODIS SST data on the development and evolution of predicted sea/land-breeze circulations, clouds, and precipitation. This paper will present verification results comparing the NWS MIA forecasts the SPoRT experimental WRF forecasts, and highlight any substantial differences noted in the predicted mesoscale phenomena.

Grid Data Management and Customer Demands at MeteoSwiss

NASA Astrophysics Data System (ADS)

Rigo, G.; Lukasczyk, Ch.

2010-09-01

Data grids constitute the required input form for a variety of applications. Therefore, customers increasingly expect climate services to not only provide measured data, but also grids of these with the required configurations on an operational basis. Currently, MeteoSwiss is establishing a production chain for delivering data grids by subscription directly from the data warehouse in order to meet the demand for precipitation data grids by governmental, business and science customers. The MeteoSwiss data warehouse runs on an Oracle database linked with an ArcGIS Standard edition geodatabase. The grids are produced by Unix-based software written in R called GRIDMCH which extracts the station data from the data warehouse and stores the files in the file system. By scripts, the netcdf-v4 files are imported via an FME interface into the database. Currently daily and monthly deliveries of daily precipitation grids are available from MeteoSwiss with a spatial resolution of 2.2km x 2.2km. These daily delivered grids are a preliminary based on 100 measuring sites whilst the grid of the monthly delivery of daily sums is calculated out of about 430 stations. Crucial for the absorption by the customers is the understanding of and the trust into the new grid product. Clearly stating needs which can be covered by grid products, the customers require a certain lead time to develop applications making use of the particular grid. Therefore, early contacts and a continuous attendance as well as flexibility in adjusting the production process to fulfill emerging customer needs are important during the introduction period. Gridding over complex terrain can lead to temporally elevated uncertainties in certain areas depending on the weather situation and coverage of measurements. Therefore, careful instructions on the quality and use and the possibility to communicate the uncertainties of gridded data proofed to be essential especially to the business and science customers who require near-real-time datasets to build up trust in the product in different applications. The implementation of a new method called RSOI for the daily production allowed to bring the daily precipitation field up to the expectations of customers. The main use of the grids were near-realtime and past event analysis in areas scarcely covered with stations, and inputs for forecast tools and models. Critical success factors of the product were speed of delivery and at the same time accuracy, temporal and spatial resolution, and configuration (coordinate system, projection). To date, grids of archived precipitation data since 1961 and daily/monthly precipitation gridsets with 4h-delivery lag of Switzerland or subareas are available.

Spatio-temporal precipitation climatology over complex terrain using a censored additive regression model.

PubMed

Stauffer, Reto; Mayr, Georg J; Messner, Jakob W; Umlauf, Nikolaus; Zeileis, Achim

2017-06-15

Flexible spatio-temporal models are widely used to create reliable and accurate estimates for precipitation climatologies. Most models are based on square root transformed monthly or annual means, where a normal distribution seems to be appropriate. This assumption becomes invalid on a daily time scale as the observations involve large fractions of zero observations and are limited to non-negative values. We develop a novel spatio-temporal model to estimate the full climatological distribution of precipitation on a daily time scale over complex terrain using a left-censored normal distribution. The results demonstrate that the new method is able to account for the non-normal distribution and the large fraction of zero observations. The new climatology provides the full climatological distribution on a very high spatial and temporal resolution, and is competitive with, or even outperforms existing methods, even for arbitrary locations.

Monitoring Disaster-Related Power Outages Using NASA Black Marble Nighttime Light Product

NASA Astrophysics Data System (ADS)

Wang, Z.; Román, M. O.; Sun, Q.; Molthan, A. L.; Schultz, L. A.; Kalb, V. L.

2018-04-01

Timely and accurate monitoring of disruptions to the electricity grid, including the magnitude, spatial extent, timing, and duration of net power losses, is needed to improve situational awareness of disaster response and long-term recovery efforts. Satellite-derived Nighttime Lights (NTL) provide an indication of human activity patterns and have been successfully used to monitor disaster-related power outages. The global 500 m spatial resolution National Aeronautics and Space Administration (NASA) Black Marble NTL daily standard product suite (VNP46) is generated from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the NASA/National Oceanic and Atmospheric Administration (NOAA) Suomi National Polar-orbiting Partnership (Suomi- NPP) satellite, which began operations on 19 January 2012. With its improvements in product accuracy (including critical atmospheric and BRDF correction routines), the VIIRS daily Black Mable product enables systematic monitoring of outage conditions across all stages of the disaster management cycle.

Trend analysis of regional heat wave warning using RegCM simulations

NASA Astrophysics Data System (ADS)

Pongracz, R.; Bartholy, J.; Bartha, E. B.; Torek, O.; Torma, Cs.

2010-09-01

Heat wave events are important temperature-related climatological extremes due to their impacts on human health. In the future, they are very likely to occur more frequently and more intensely not only in the Carpathian Basin, but in most regions of the world because of global warming. In order to develop adaptation and mitigation strategies on local scale, it is essential to analyze the projected changes related to heat waves. In Hungary, three categories of heat wave warning are applied. They are associated to the daily mean temperature values. (i) Warning category 1 is issued when the daily mean temperature is larger than 25 °C. (ii) Warning category 2 is issued when the daily mean temperature for at least 3 consecutive days is larger than 25 °C. (iii) Warning category 3 is issued when the daily mean temperature for at least 3 consecutive days is larger than 27 °C. In this poster, frequency of these conditions are analyzed using regional climate model experiments of model RegCM with 10-km horizontal resolution adapted at the Department of Meteorology, Eotvos Lorand University in the frame of the CECILIA EU-project. The model RegCM is a 3-dimensional, sigma-coordinate, primitive equation model, and it was originally developed by Giorgi et al. Currently, it is available from the ICTP (International Centre for Theoretical Physics). The initial and lateral boundary conditions of the fine-resolution experiments have been provided by the global climate model ECHAM for the A1B emission scenario for three different time slices (1961-1990, 2021-2050, and 2071-2100).

Daily monitoring of 30 m crop condition over complex agricultural landscapes

NASA Astrophysics Data System (ADS)

Sun, L.; Gao, F.; Xie, D.; Anderson, M. C.; Yang, Y.

2017-12-01

Crop progress provides information necessary for efficient irrigation, scheduling fertilization and harvesting operations at optimal times for achieving higher yields. In the United States, crop progress reports are released online weekly by US Department of Agriculture (USDA) - National Agricultural Statistics Service (NASS). However, the ground data collection is time consuming and subjective, and these reports are provided at either district (multiple counties) or state level. Remote sensing technologies have been widely used to map crop conditions, to extract crop phenology, and to predict crop yield. However, for current satellite-based sensors, it is difficult to acquire both high spatial resolution and frequent coverage. For example, Landsat satellites are capable to capture 30 m resolution images, while the long revisit cycles, cloud contamination further limited their use in detecting rapid surface changes. On the other hand, MODIS can provide daily observations, but with coarse spatial resolutions range from 250 to 1000 m. In recent years, multi-satellite data fusion technology such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) has been used to combine the spatial resolution of Landsat with the temporal frequency of MODIS. It has been found that this synthetic dataset could provide more valuable information compared to the images acquired from only one single sensor. However, accuracy of STARFM depends on heterogeneity of landscape and available clear image pairs of MODIS and Landsat. In this study, a new fusion method was developed using the crop vegetation index (VI) timeseries extracted from "pure" MODIS pixels and Landsat overpass images to generate daily 30 m VI for crops. The fusion accuracy was validated by comparing to the original Landsat images. Results show that the relative error in non-rapid growing period is around 3-5% and in rapid growing period is around 6-8% . The accuracy is much better than that of STARFM which is 4-9% in non-rapid growing period and 10-16% in rapid growing period based on 13 image pairs. The predicted VI from this approach looks consistent and smooth in the SLC-off gap stripes of Landsat 7 ETM+ image. The new fusion results will be used to map crop phenology and to predict crop yield at field scale in the complex agricultural landscapes.

A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

NASA Technical Reports Server (NTRS)

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-01-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter PM(sub 2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data.We developed and cross validated models to predict daily PM(sub 2.5) at a 1X 1 km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1 X 1 km grid predictions. We used mixed models regressing PM(sub 2.5) measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R(sup 2) = 0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R(sup 2) = 0.87, R(sup)2 = 0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data.

PubMed

Kloog, Itai; Chudnovsky, Alexandra A; Just, Allan C; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2014-10-01

The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM 2.5 ) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM 2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003-2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM 2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Our model performance was excellent (mean out-of-sample R 2 =0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R 2 =0.87, R 2 =0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region.

A New Hybrid Spatio-Temporal Model For Estimating Daily Multi-Year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data

PubMed Central

Kloog, Itai; Chudnovsky, Alexandra A.; Just, Allan C.; Nordio, Francesco; Koutrakis, Petros; Coull, Brent A.; Lyapustin, Alexei; Wang, Yujie; Schwartz, Joel

2017-01-01

Background The use of satellite-based aerosol optical depth (AOD) to estimate fine particulate matter (PM2.5) for epidemiology studies has increased substantially over the past few years. These recent studies often report moderate predictive power, which can generate downward bias in effect estimates. In addition, AOD measurements have only moderate spatial resolution, and have substantial missing data. Methods We make use of recent advances in MODIS satellite data processing algorithms (Multi-Angle Implementation of Atmospheric Correction (MAIAC), which allow us to use 1 km (versus currently available 10 km) resolution AOD data. We developed and cross validated models to predict daily PM2.5 at a 1×1km resolution across the northeastern USA (New England, New York and New Jersey) for the years 2003–2011, allowing us to better differentiate daily and long term exposure between urban, suburban, and rural areas. Additionally, we developed an approach that allows us to generate daily high-resolution 200 m localized predictions representing deviations from the area 1×1 km grid predictions. We used mixed models regressing PM2.5 measurements against day-specific random intercepts, and fixed and random AOD and temperature slopes. We then use generalized additive mixed models with spatial smoothing to generate grid cell predictions when AOD was missing. Finally, to get 200 m localized predictions, we regressed the residuals from the final model for each monitor against the local spatial and temporal variables at each monitoring site. Results Our model performance was excellent (mean out-of-sample R2=0.88). The spatial and temporal components of the out-of-sample results also presented very good fits to the withheld data (R2=0.87, R2=0.87). In addition, our results revealed very little bias in the predicted concentrations (Slope of predictions versus withheld observations = 0.99). Conclusion Our daily model results show high predictive accuracy at high spatial resolutions and will be useful in reconstructing exposure histories for epidemiological studies across this region. PMID:28966552

Monitoring interannual variation in global crop yield using long-term AVHRR and MODIS observations

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Zhang, Qingyuan

2016-04-01

Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data have been extensively applied for crop yield prediction because of their daily temporal resolution and a global coverage. This study investigated global crop yield using daily two band Enhanced Vegetation Index (EVI2) derived from AVHRR (1981-1999) and MODIS (2000-2013) observations at a spatial resolution of 0.05° (∼5 km). Specifically, EVI2 temporal trajectory of crop growth was simulated using a hybrid piecewise logistic model (HPLM) for individual pixels, which was used to detect crop phenological metrics. The derived crop phenology was then applied to calculate crop greenness defined as EVI2 amplitude and EVI2 integration during annual crop growing seasons, which was further aggregated for croplands in each country, respectively. The interannual variations in EVI2 amplitude and EVI2 integration were combined to correlate to the variation in cereal yield from 1982-2012 for individual countries using a stepwise regression model, respectively. The results show that the confidence level of the established regression models was higher than 90% (P value < 0.1) in most countries in the northern hemisphere although it was relatively poor in the southern hemisphere (mainly in Africa). The error in the yield predication was relatively smaller in America, Europe and East Asia than that in Africa. In the 10 countries with largest cereal production across the world, the prediction error was less than 9% during past three decades. This suggests that crop phenology-controlled greenness from coarse resolution satellite data has the capability of predicting national crop yield across the world, which could provide timely and reliable crop information for global agricultural trade and policymakers.

Evolution of Precipitation Extremes in Three Large Ensembles of Climate Simulations - Impact of Spatial and Temporal Resolutions

NASA Astrophysics Data System (ADS)

Martel, J. L.; Brissette, F.; Mailhot, A.; Wood, R. R.; Ludwig, R.; Frigon, A.; Leduc, M.; Turcotte, R.

2017-12-01

Recent studies indicate that the frequency and intensity of extreme precipitation will increase in future climate due to global warming. In this study, we compare annual maxima precipitation series from three large ensembles of climate simulations at various spatial and temporal resolutions. The first two are at the global scale: the Canadian Earth System Model (CanESM2) 50-member large ensemble (CanESM2-LE) at a 2.8° resolution and the Community Earth System Model (CESM1) 40-member large ensemble (CESM1-LE) at a 1° resolution. The third ensemble is at the regional scale over both Eastern North America and Europe: the Canadian Regional Climate Model (CRCM5) 50-member large ensemble (CRCM5-LE) at a 0.11° resolution, driven at its boundaries by the CanESM-LE. The CRCM5-LE is a new ensemble issued from the ClimEx project (http://www.climex-project.org), a Québec-Bavaria collaboration. Using these three large ensembles, change in extreme precipitations over the historical (1980-2010) and future (2070-2100) periods are investigated. This results in 1 500 (30 years x 50 members for CanESM2-LE and CRCM5-LE) and 1200 (30 years x 40 members for CESM1-LE) simulated years over both the historical and future periods. Using these large datasets, the empirical daily (and sub-daily for CRCM5-LE) extreme precipitation quantiles for large return periods ranging from 2 to 100 years are computed. Results indicate that daily extreme precipitations generally will increase over most land grid points of both domains according to the three large ensembles. Regarding the CRCM5-LE, the increase in sub-daily extreme precipitations will be even more important than the one observed for daily extreme precipitations. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety.

Systematic errors in the simulation of the Asian summer monsoon: the role of rainfall variability on a range of time and space scales

NASA Astrophysics Data System (ADS)

Martin, Gill; Levine, Richard; Klingaman, Nicholas; Bush, Stephanie; Turner, Andrew; Woolnough, Steven

2015-04-01

Despite considerable efforts worldwide to improve model simulations of the Asian summer monsoon, significant biases still remain in climatological seasonal mean rainfall distribution, timing of the onset, and northward and eastward extent of the monsoon domain (Sperber et al., 2013). Many modelling studies have shown sensitivity to convection and boundary layer parameterization, cloud microphysics and land surface properties, as well as model resolution. Here we examine the problems in representing short-timescale rainfall variability (related to convection parameterization), problems in representing synoptic-scale systems such as monsoon depressions (related to model resolution), and the relationship of each of these with longer-term systematic biases. Analysis of the spatial distribution of rainfall intensity on a range of timescales ranging from ~30 minutes to daily, in the MetUM and in observations (where available), highlights how rainfall biases in the South Asian monsoon region on different timescales in different regions can be achieved in models through a combination of the incorrect frequency and/or intensity of rainfall. Over the Indian land area, the typical dry bias is related to sub-daily rainfall events being too infrequent, despite being too intense when they occur. In contrast, the wet bias regions over the equatorial Indian Ocean are mainly related to too frequent occurrence of lower-than-observed 3-hourly rainfall accumulations which result in too frequent occurrence of higher-than-observed daily rainfall accumulations. This analysis sheds light on the model deficiencies behind the climatological seasonal mean rainfall biases that many models exhibit in this region. Changing physical parameterizations alters this behaviour, with associated adjustments in the climatological rainfall distribution, although the latter is not always improved (Bush et al., 2014). This suggests a more complex interaction between the diabatic heating and the large-scale circulation than is indicated by the intensity and frequency of rainfall alone. Monsoon depressions and low pressure systems are important contributors to monsoon rainfall over central and northern India, areas where MetUM climate simulations typically show deficient monsoon rainfall. Analysis of MetUM climate simulations at resolutions ranging from N96 (~135km) to N512 (~25km) suggests that at lower resolution the numbers and intensities of monsoon depressions and low pressure systems and their associated rainfall are very low compared with re-analyses/observations. We show that there are substantial increases with horizontal resolution, but resolution is not the only factor. Idealised simulations, either using nudged atmospheric winds or initialised coupled hindcasts, which improve (strengthen) the mean state monsoon and cyclonic circulation over the Indian peninsula, also result in a substantial increase in monsoon depressions and associated rainfall. This suggests that a more realistic representation of monsoon depressions is possible even at lower resolution if the larger-scale systematic error pattern in the monsoon is improved.

Assessment of Multiple Daily Precipitation Statistics in ERA-Interim Driven Med-CORDEX and EURO-CORDEX Experiments Against High Resolution Observations

NASA Astrophysics Data System (ADS)

Coppola, E.; Fantini, A.; Raffaele, F.; Torma, C. Z.; Bacer, S.; Giorgi, F.; Ahrens, B.; Dubois, C.; Sanchez, E.; Verdecchia, M.

2017-12-01

We assess the statistics of different daily precipitation indices in ensembles of Med-CORDEX and EUROCORDEX experiments at high resolution (grid spacing of ˜0.11° , or RCM11) and medium resolution (grid spacing of ˜0.44° , or RCM44) with regional climate models (RCMs) driven by the ERA-Interim reanalysis of observations for the period 1989-2008. The assessment is carried out by comparison with a set of high resolution observation datasets for 9 European subregions. The statistics analyzed include quantitative metrics for mean precipitation, daily precipitation Probability Density Functions (PDFs), daily precipitation intensity, frequency, 95th percentile and 95th percentile of dry spell length. We assess both an ensemble including all Med-CORDEX and EURO-CORDEX models and one including the Med-CORDEX models alone. For the All Models ensembles, the RCM11 one shows a remarkable performance in reproducing the spatial patterns and seasonal cycle of mean precipitation over all regions, with a consistent and marked improvement compared to the RCM44 ensemble and the ERA-Interim reanalysis. A good consistency with observations by the RCM11 ensemble (and a substantial improvement compared to RCM44 and ERA-Interim) is found also for the daily precipitation PDFs, mean intensity and, to a lesser extent, the 95th percentile. In fact, for some regions the RCM11 ensemble overestimates the occurrence of very high intensity events while for one region the models underestimate the occurrence of the largest extremes. The RCM11 ensemble still shows a general tendency to underestimate the dry day frequency and 95th percentile of dry spell length over wetter regions, with only a marginal improvement compared to the lower resolution models. This indicates that the problem of the excessive production of low precipitation events found in many climate models persists also at relatively high resolutions, at least in wet climate regimes. Concerning the Med-CORDEX model ensembles we find that their performance is of similar quality as that of the all-models over the Mediterranean regions analyzed. Finally, we stress the need of consistent and quality checked fine scale observation datasets for the assessment of RCMs run at increasingly high horizontal resolutions.

Climate Forcing Datasets for Agricultural Modeling: Merged Products for Gap-Filling and Historical Climate Series Estimation

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Goldberg, Richard; Chryssanthacopoulos, James

2014-01-01

The AgMERRA and AgCFSR climate forcing datasets provide daily, high-resolution, continuous, meteorological series over the 1980-2010 period designed for applications examining the agricultural impacts of climate variability and climate change. These datasets combine daily resolution data from retrospective analyses (the Modern-Era Retrospective Analysis for Research and Applications, MERRA, and the Climate Forecast System Reanalysis, CFSR) with in situ and remotely-sensed observational datasets for temperature, precipitation, and solar radiation, leading to substantial reductions in bias in comparison to a network of 2324 agricultural-region stations from the Hadley Integrated Surface Dataset (HadISD). Results compare favorably against the original reanalyses as well as the leading climate forcing datasets (Princeton, WFD, WFD-EI, and GRASP), and AgMERRA distinguishes itself with substantially improved representation of daily precipitation distributions and extreme events owing to its use of the MERRA-Land dataset. These datasets also peg relative humidity to the maximum temperature time of day, allowing for more accurate representation of the diurnal cycle of near-surface moisture in agricultural models. AgMERRA and AgCFSR enable a number of ongoing investigations in the Agricultural Model Intercomparison and Improvement Project (AgMIP) and related research networks, and may be used to fill gaps in historical observations as well as a basis for the generation of future climate scenarios.

Generation and Evaluation of a Global Land Surface Phenology Product from Suomi-NPP VIIRS Observations

NASA Astrophysics Data System (ADS)

Zhang, X.; Liu, L.; Yan, D.; Moon, M.; Liu, Y.; Henebry, G. M.; Friedl, M. A.; Schaaf, C.

2017-12-01

Land surface phenology (LSP) datasets have been produced from a variety of coarse spatial resolution satellite observations at both regional and global scales and spanning different time periods since 1982. However, the LSP product generated from NASA's MODerate Resolution Imaging Spectroradiometer (MODIS) data at a spatial resolution of 500m, which is termed Land Cover Dynamics (MCD12Q2), is the only global product operationally produced and freely accessible at annual time steps from 2001. Because MODIS instrument is aging and will be replaced by the Visible Infrared Imaging Radiometer Suite (VIIRS), this research focuses on the generation and evaluation of a global LSP product from Suomi-NPP VIIRS time series observations that provide continuity with the MCD12Q2 product. Specifically, we generate 500m VIIRS global LSP data using daily VIIRS Nadir BRDF (bidirectional reflectance distribution function)-Adjusted reflectances (NBAR) in combination with land surface temperature, snow cover, and land cover type as inputs. The product provides twelve phenological metrics (seven phenological dates and five phenological greenness magnitudes), along with six quality metrics characterizing the confidence and quality associated with phenology retrievals at each pixel. In this paper, we describe the input data and algorithms used to produce this new product, and investigate the impact of VIIRS data time series quality on phenology detections across various climate regimes and ecosystems. As part of our analysis, the VIIRS LSP is evaluated using PhenoCam imagery in North America and Asia, and using higher spatial resolution satellite observations from Landsat 8 over an agricultural area in the central USA. We also explore the impact of high frequency cloud cover on the VIIRS LSP product by comparing with phenology detected from the Advanced Himawari Imager (AHI) onboard Himawari-8. AHI is a new geostationary sensor that observes land surface every 10 minutes, which increases the ability to capture cloud-free observations relative to data collected from polar-orbiting satellites such as Suomi-NPP, thereby improving the quality of daily time series data in regions with heavy cloud cover. Finally, the VIIRS LSP is compared with MCD12Q2 data to investigate the continuity of long-term global LSP data records.

Assessment of Spatiotemporal Fusion Algorithms for Planet and Worldview Images

PubMed Central

Zhu, Xiaolin; Gao, Feng; Chou, Bryan; Li, Jiang; Shen, Yuzhong; Koperski, Krzysztof; Marchisio, Giovanni

2018-01-01

Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images. PMID:29614745

Assessment of Spatiotemporal Fusion Algorithms for Planet and Worldview Images.

PubMed

Kwan, Chiman; Zhu, Xiaolin; Gao, Feng; Chou, Bryan; Perez, Daniel; Li, Jiang; Shen, Yuzhong; Koperski, Krzysztof; Marchisio, Giovanni

2018-03-31

Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images.

Bud break responds more strongly to daytime than night-time temperature under asymmetric experimental warming.

PubMed

Rossi, Sergio; Isabel, Nathalie

2017-01-01

Global warming is diurnally asymmetric, leading to a less cold, rather than warmer, climate. We investigated the effects of asymmetric experimental warming on plant phenology by testing the hypothesis that daytime warming is more effective in advancing bud break than night-time warming. Bud break was monitored daily in Picea mariana seedlings belonging to 20 provenances from Eastern Canada and subjected to daytime and night-time warming in growth chambers at temperatures varying between 8 and 16 °C. The higher advancements of bud break and shorter times required to complete the phenological phases occurred with daytime warming. Seedlings responded to night-time warming, but still with less advancement of bud break than under daytime warming. No advancement was observed when night-time warming was associated with a daytime cooling. The effect of the treatments was uniform across provenances. Our observations realized under controlled conditions allowed to experimentally demonstrate that bud break can advance under night-time warming, but to a lesser extent than under daytime warming. Prediction models using daily timescales could neglect the diverging influence of asymmetric warming and should be recalibrated for higher temporal resolutions. © 2016 John Wiley & Sons Ltd.

Expansion of the On-line Archive "Statistically Downscaled WCRP CMIP3 Climate Projections"

NASA Astrophysics Data System (ADS)

Brekke, L. D.; Pruitt, T.; Maurer, E. P.; Das, T.; Duffy, P.; White, K.

2009-12-01

Presentation highlights status and plans for a public-access archive of downscaled CMIP3 climate projections. Incorporating climate projection information into long-term evaluations of water and energy resources requires analysts to have access to projections at "basin-relevant" resolution. Such projections would ideally be bias-corrected to account for climate model tendencies to systematically simulate historical conditions different than observed. In 2007, the U.S. Bureau of Reclamation, Santa Clara University and Lawrence Livermore National Laboratory (LLNL) collaborated to develop an archive of 112 bias-corrected and spatially disaggregated (BCSD) CMIP3 temperature and precipitation projections. These projections were generated using 16 CMIP3 models to simulate three emissions pathways (A2, A1b, and B1) from one or more initializations (runs). Projections are specified on a monthly time step from 1950-2099 and at 0.125 degree spatial resolution within the North American Land Data Assimilation System domain (i.e. contiguous U.S., southern Canada and northern Mexico). Archive data are freely accessible at LLNL Green Data Oasis (url). Since being launched, the archive has served over 3500 data requests by nearly 500 users in support of a range of planning, research and educational activities. Archive developers continue to look for ways to improve the archive and respond to user needs. One request has been to serve the intermediate datasets generated during the BCSD procedure, helping users to interpret the relative influences of the bias-correction and spatial disaggregation on the transformed CMIP3 output. This request has been addressed with intermediate datasets now posted at the archive web-site. Another request relates closely to studying hydrologic and ecological impacts under climate change, where users are asking for projected diurnal temperature information (e.g., projected daily minimum and maximum temperature) and daily time step resolution. In response, archive developers are adding content in 2010, teaming with Scripps Institution of Oceanography (through their NOAA-RISA California-Nevada Applications Program and the California Climate Change Center) to apply a new daily downscaling technique to a sub-ensemble of the archive’s CMIP3 projections. The new technique, Bias-Corrected Constructed Analogs, combines the BC part of BCSD with a recently developed technique that preserves the daily sequencing structure of CMIP3 projections (Constructed Analogs, or CA). Such data will more easily serve hydrologic and ecological impacts assessments, and offer an opportunity to evaluate projection uncertainty associated with downscaling technique. Looking ahead to the arrival CMIP5 projections, archive collaborators have plans apply both BCSD and BCCA over the contiguous U.S. consistent with CMIP3 applications above, and also apply BCSD globally at a 0.5 degree spatial resolution. The latter effort involves collaboration with U.S. Army Corps of Engineers (USACE) and Climate Central.

Ten years of OMI observations: scientific highlights and impacts on the new generation of UV/VIS satellite instrumentation

NASA Astrophysics Data System (ADS)

Levelt, Pieternel; Veefkind, Pepijn; Bhartia, Pawan; Joiner, Joanna; Tamminen, Johanna; OMI Science Team

2014-05-01

On July 15, 2004 Ozone Monitoring Instrument (OMI) was successfully launched from the Vandenberg military air force basis in California, USA, on NASA's EOS-Aura spacecraft. OMI is the first of a new generation of UV/VIS nadir solar backscatter imaging spectrometers, which provides nearly global coverage in one day with an unprecedented spatial resolution of 13 x 24 km2. OMI measures solar irradiance and Earth radiances in the wavelength range of 270 to 500 nm with a spectral resolution of about 0.5 nm. OMI is designed and built by the Netherlands and Finland and is also a third party mission of ESA. The major step that was made in the OMI instrument compared to its predecessors is the use of 2-dimensional detector arrays (CCDs) in a highly innovative small optical design. These innovations enable the combination of a high spatial resolution and a good spectral resolution with daily global coverage. OMI measures a range of trace gases (O3, NO2, SO2, HCHO, BrO, OClO, H2O), clouds and aerosols. Albeit OMI is already 5 years over its design lifetime, the instrument is still fully operational. The successor of OMI is TROPOMI (TROPOspheric Monitoring Instrument) on the Copernicus Sentinel-5 precursor mission, planned for launch in 2015. OMI's unique capabilities rely in measuring tropospheric trace gases with a small footprint and daily global coverage. The unprecedented spatial resolution of the instrument revealed for the first time tropospheric pollution maps on a daily basis with urban scale resolution leading to improved air quality forecasts. The OMI measurements also improve our understanding of air quality and the interaction between air quality and climate change by combining measurements of air pollutants and aerosols. In recent years the data are also used for obtaining high-resolution global emission maps using inverse modelling or related techniques, challenging the bottom-up inventories based emission maps. In addition to scientific research, OMI also contributes to several operational services, including volcanic plume warning systems for aviation, UV forecasts and the air quality forecasts. In this invited talk an overview will be given of unique findings and new scientific results based on OMI data over the last 10 years and which unique OMI instrument features are recurring in the new generation of UV/VIS satellite instrumentation in Europe, USA and Asia.

A fast and reliable method for daily quality assurance in spot scanning proton therapy with a compact and inexpensive phantom.

PubMed

Bizzocchi, Nicola; Fracchiolla, Francesco; Schwarz, Marco; Algranati, Carlo

2017-01-01

In a radiotherapy center, daily quality assurance (QA) measurements are performed to ensure that the equipment can be safely used for patient treatment on that day. In a pencil beam scanning (PBS) proton therapy center, spot positioning, spot size, range, and dose output are usually verified every day before treatments. We designed, built, and tested a new, reliable, sensitive, and inexpensive phantom, coupled with an array of ionization chambers, for daily QA that reduces the execution times while preserving the reliability of the test. The phantom is provided with 2 pairs of wedges to sample the Bragg peak at different depths to have a transposition on the transverse plane of the depth dose. Three "boxes" are used to check spot positioning and delivered dose. The box thickness helps spread the single spot and to fit a Gaussian profile on a low resolution detector. We tested whether our new QA solution could detect errors larger than our action levels: 1 mm in spot positioning, 2 mm in range, and 10% in spot size. Execution time was also investigated. Our method is able to correctly detect 98% of spots that are actually in tolerance for spot positioning and 99% of spots out of 1 mm tolerance. All range variations greater than the threshold (2 mm) were correctly detected. The analysis performed over 1 month showed a very good repeatability of spot characteristics. The time taken to perform the daily quality assurance is 20 minutes, a half of the execution time of the former multidevice procedure. This "in-house build" phantom substitutes 2 very expensive detectors (a multilayer ionization chamber [MLIC] and a strip chamber, reducing by 5 times the cost of the equipment. We designed, built, and validated a phantom that allows for accurate, sensitive, fast, and inexpensive daily QA procedures in proton therapy with PBS. Copyright © 2017 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Tidewater dynamics at Store Glacier, West Greenland from daily repeat UAV surveys

NASA Astrophysics Data System (ADS)

Ryan, Jonathan; Hubbard, Alun; Toberg, Nick; Box, Jason; Todd, Joe; Christoffersen, Poul; Neal, Snooke

2017-04-01

A significant component of the Greenland ice sheet's mass wasteage to sea level rise is attributed to the acceleration and dynamic thinning at its tidewater margins. To improve understanding of the rapid mass loss processes occurring at large tidewater glaciers, we conducted a suite of daily repeat aerial surveys across the terminus of Store Glacier, a large outlet draining the western Greenland Ice Sheet, from May to July 2014 (https://www.youtube.com/watch?v=-y8kauAVAfE). The unmanned aerial vehicles (UAVs) were equipped with digital cameras, which, in combination with onboard GPS, enabled production of high spatial resolution orthophotos and digital elevation models (DEMs) using standard structure-from-motion techniques. These data provide insight into the short-term dynamics of Store Glacier surrounding the break-up of the sea-ice mélange that occurred between 4 and 7 June. Feature tracking of the orthophotos reveals that mean speed of the terminus is 16 - 18 m per day, which was independently verified against a high temporal resolution time-series derived from an expendable/telemetric GPS deployed at the terminus. Differencing the surface area of successive orthophotos enable quantification of daily calving rates, which significantly increase just after melange break-up. Likewise, by differencing bulk freeboard volume of icebergs through time we could also constrain the magnitude and variation of submarine melt. We calculate a mean submarine melt rate of 0.18 m per day throughout the spring period with relatively little supraglacial runoff and no active meltwater plumes to stimulate fjord circulation and upwelling of deeper, warmer water masses. Finally, we relate calving rates to the zonation and depth of water-filled crevasses, which were prominent across parts of the terminus from June onwards.

MODIS Snow-Cover Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vinvent V.; DiGirolamo, Nicolo; Bayr, Klaus J.; Houser, Paul (Technical Monitor)

2001-01-01

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. These products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to the currently available operation products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set is generated for long-term climates studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the product. The snow product suite starts with a 500-m resolution swath snow-cover map which is gridded to the Integerized Sinusoidal Grid to produce daily and eight-day composite tile products. The sequence then proceeds to a climate-modeling grid product at 5-km spatial resolution, with both daily and eight-day composite products. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented. Near-term enhancements include daily snow albedo and fractional snow cover.

Role of resolution in regional climate change projections over China

NASA Astrophysics Data System (ADS)

Shi, Ying; Wang, Guiling; Gao, Xuejie

2017-11-01

This paper investigates the sensitivity of projected future climate changes over China to the horizontal resolution of a regional climate model RegCM4.4 (RegCM), using RCP8.5 as an example. Model validation shows that RegCM performs better in reproducing the spatial distribution and magnitude of present-day temperature, precipitation and climate extremes than the driving global climate model HadGEM2-ES (HadGEM, at 1.875° × 1.25° degree resolution), but little difference is found between the simulations at 50 and 25 km resolutions. Comparison with observational data at different resolutions confirmed the added value of the RCM and finer model resolutions in better capturing the probability distribution of precipitation. However, HadGEM and RegCM at both resolutions project a similar pattern of significant future warming during both winter and summer, and a similar pattern of winter precipitation changes including dominant increase in most areas of northern China and little change or decrease in the southern part. Projected precipitation changes in summer diverge among the three models, especially over eastern China, with a general increase in HadGEM, little change in RegCM at 50 km, and a mix of increase and decrease in RegCM at 25 km resolution. Changes of temperature-related extremes (annual total number of daily maximum temperature > 25 °C, the maximum value of daily maximum temperature, the minimum value of daily minimum temperature in the three simulations especially in the two RegCM simulations are very similar to each other; so are the precipitation-related extremes (maximum consecutive dry days, maximum consecutive 5-day precipitation and extremely wet days' total amount). Overall, results from this study indicate a very low sensitivity of projected changes in this region to model resolution. While fine resolution is critical for capturing the spatial variability of the control climate, it may not be as important for capturing the climate response to homogeneous forcing (in this case greenhouse gas concentration changes).

Fundamental statistical relationships between monthly and daily meteorological variables: Temporal downscaling of weather based on a global observational dataset

NASA Astrophysics Data System (ADS)

Sommer, Philipp; Kaplan, Jed

2016-04-01

Accurate modelling of large-scale vegetation dynamics, hydrology, and other environmental processes requires meteorological forcing on daily timescales. While meteorological data with high temporal resolution is becoming increasingly available, simulations for the future or distant past are limited by lack of data and poor performance of climate models, e.g., in simulating daily precipitation. To overcome these limitations, we may temporally downscale monthly summary data to a daily time step using a weather generator. Parameterization of such statistical models has traditionally been based on a limited number of observations. Recent developments in the archiving, distribution, and analysis of "big data" datasets provide new opportunities for the parameterization of a temporal downscaling model that is applicable over a wide range of climates. Here we parameterize a WGEN-type weather generator using more than 50 million individual daily meteorological observations, from over 10'000 stations covering all continents, based on the Global Historical Climatology Network (GHCN) and Synoptic Cloud Reports (EECRA) databases. Using the resulting "universal" parameterization and driven by monthly summaries, we downscale mean temperature (minimum and maximum), cloud cover, and total precipitation, to daily estimates. We apply a hybrid gamma-generalized Pareto distribution to calculate daily precipitation amounts, which overcomes much of the inability of earlier weather generators to simulate high amounts of daily precipitation. Our globally parameterized weather generator has numerous applications, including vegetation and crop modelling for paleoenvironmental studies.

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

Wang, Jiali; Swati, F. N. U.; Stein, Michael L.

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, andmore » time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.« less

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_TRMM-PFM-VIRS_Beta4)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

A Prototype MODI- SSM/I Snow Mapping Algorithm

NASA Technical Reports Server (NTRS)

Tait, Andrew B.; Barton, Jonathan S.; Hall, Dorothy K.

1999-01-01

Data in the wavelength range 0.545 - 1.652 microns from the Moderate Resolution Imaging Spectroradiometer (MODIS), to be launched aboard the Earth Observing System (EOS) Terra in the fall of 1999, will be used to map daily global snow cover at 500m resolution. However, during darkness, or when the satellite's view of the surface is obscured by cloud, snow cover cannot be mapped using MODIS data. We show that during these conditions, it is possible to supplement the MODIS product by mapping the snow cover using passive microwave data from the Special Sensor Microwave Imager (SSM/I), albeit with much poorer resolution. For a 7-day time period in March 1999, a prototype MODIS snow-cover product was compared with a prototype MODIS-SSM/I product for the same area in the mid-western United States. The combined MODIS-SSM/I product mapped 9% more snow cover than the MODIS-only product.

Treatment of Refractory Filamentary Keratitis With Autologous Serum Tears.

PubMed

Read, Sarah P; Rodriguez, Marianeli; Dubovy, Sander; Karp, Carol L; Galor, Anat

2017-09-01

To report a case of filamentary keratitis (FK) successfully treated with autologous serum tears and to review the pathogenesis and management of FK. Case report including high-resolution anterior segment optical coherence tomography and filament histopathology. A 61-year-old Hispanic man presented with pain and photophobia of the right eye. He was found to have a corneal epithelial defect and a small peripheral infiltrate 4 months after Laser Assisted in situ Keratomileusis. After resolution of the epithelial defect, he developed FK. Over a 4-month period, conservative management with aggressive lubrication, lid hygiene, topical corticosteroids, topical cyclosporine, bandage contact lenses, and oral doxycycline failed to resolve the corneal filaments. Notably, treatment with 20% autologous serum tears, four times daily, led to a sustained resolution of the FK within 1 week. This case demonstrates the complexity of FK management and introduces autologous serum tears as a viable management option when conservative approaches to this condition fail.

High Resolution Doppler Imager FY 2001,2002,2003 Operations and Algorithm Maintenance

NASA Technical Reports Server (NTRS)

Skinner, Wilbert

2004-01-01

During the performance period of this grant HRDI (High Resolution Doppler Imager) operations remained nominal. The instrument has suffered no loss of scientific capability and operates whenever sufficient power is available. Generally, there are approximately 5-7 days per month when the power level is too low to permit observations. The daily latitude coverage for HRDI measurements in the mesosphere, lower thermosphere (MLT) region are shown.It shows that during the time of this grant, HRDI operations collected data at a rate comparable to that achieved during the UARS (Upper Atmosphere Research Satellite) prime mission (1991 -1995). Data collection emphasized MLT wind to support the validation efforts of the TIDI instrument on TIMED, therefore fulfilling one of the primary objectives of this phase of the UARS mission. Skinner et al., (2003) present a summary of the instrument performance during this period.

Temporal resolution requirements of satellite constellations for 30 m global burned area mapping

NASA Astrophysics Data System (ADS)

Melchiorre, A.; Boschetti, L.

2017-12-01

Global burned area maps have been generated systematically with daily, coarse resolution satellite data (Giglio et al. 2013). The production of moderate resolution (10 - 30 m) global burned area products would meet the needs of several user communities: improved carbon emission estimations due to heterogeneous landscapes and for local scale air quality and fire management applications (Mouillot et al. 2014; van der Werf et al. 2010). While the increased spatial resolution reduces the influence of mixed burnt/unburnt pixels and it would increase the spectral separation of burned areas, moderate resolution satellites have reduced temporal resolution (10 - 16 days). Fire causes a land-cover change spectrally visible for a period ranging from a few weeks in savannas to over a year in forested ecosystems (Roy et al. 2010); because clouds, smoke, and other optically thick aerosols limit the number of available observations (Roy et al. 2008; Smith and Wooster 2005), burned areas might disappear before they are observed by moderate resolution sensors. Data fusion from a constellation of different sensors has been proposed to overcome these limits (Boschetti et al. 2015; Roy 2015). In this study, we estimated the probability of moderate resolution satellites and virtual constellations (including Landsat-8/9, Sentinel-2A/B) to provide sufficient observations for burned area mapping globally, and by ecosystem. First, we estimated the duration of the persistence of the signal associated with burned areas by combining the MODIS Global Burned Area and the Nadir BRDF-Adjusted Reflectance Product by characterizing the post-fire trends in reflectance to determine the length of the period in which the burn class is spectrally distinct from the unburned and, therefore, detectable. The MODIS-Terra daily cloud data were then used to estimate the probability of cloud cover. The cloud probability was used at each location to estimate the minimum revisit time needed to obtain at least one cloud-free observation within the duration of the persistence of burned areas. As complementary results, the expected omission error due to insufficient observations was estimated for each of the satellite combination considered making use of the calendar and geometry of acquisition for each of the sensor included in the virtual constellation.

Impact of Lake Okeechobee Sea Surface Temperatures on Numerical Predictions of Summertime Convective Systems over South Florida

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Splitt, Michael E.; Fuell, Kevin K.; Santos, Pablo; Lazarus, Steven M.; Jedlovec, Gary J.

2009-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center, the Florida Institute of Technology, and the NOAA/NWS Weather Forecast Office at Miami, FL (MFL) are collaborating on a project to investigate the impact of using high-resolution, 2-km Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composites within the Weather Research and Forecasting (WRF) prediction system. The NWS MFL is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run daily initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution. The project objective is to determine whether more accurate specification of the lower-boundary forcing over water using the MODIS SST composites within the 4-km WRF runs will result in improved sea fluxes and hence, more accurate e\\olutiono f coastal mesoscale circulations and the associated sensible weather elements. SPoRT conducted parallel WRF EMS runs from February to August 2007 identical to the operational runs at NWS MFL except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water. During the course of this evaluation, an intriguing case was examined from 6 May 2007, in which lake breezes and convection around Lake Okeechobee evolved quite differently when using the high-resolution SPoRT MODIS SST composites versus the lower-resolution RTG SSTs. This paper will analyze the differences in the 6 May simulations, as well as examine other cases from the summer 2007 in which the WRF-simulated Lake Okeechobee breezes evolved differently due to the SST initialization. The effects on wind fields and precipitation systems will be emphasized, including validation against surface mesonet observations and Stage IV precipitation grids.

Sampling theory for asynoptic satellite observations. I Space-time spectra, resolution, and aliasing. II - Fast Fourier synoptic mapping

NASA Technical Reports Server (NTRS)

Salby, M. L.

1982-01-01

An evaluation of the information content of asynoptic data taken in the form of nadir sonde and limb scan observations is presented, and a one-to-one correspondence is established between the alias-free data and twice-daily synoptic maps. Attention is given to space and time limitations of sampling and the orbital geometry is discussed. The sampling pattern is demonstrated to determine unique space-time spectra at all wavenumbers and frequencies. Spectral resolution and aliasing are explored, while restrictions on sampling and information content are defined. It is noted that irregular sampling at high latitudes produces spurious contamination effects. An Asynoptic Sampling Theorem is thereby formulated, as is a Synoptic Retrieval Theorem, in the second part of the article. In the latter, a procedure is developed for retrieving the unique correspondence between the asymptotic data and the synoptic maps. Applications examples are provided using data from the Nimbus-6 satellite.

Bulk and export production fluxes from sediment traps in the Gulf of Aqaba, north Red Sea

NASA Astrophysics Data System (ADS)

Torfstein, A.; Kienast, S.; Shaked, Y.

2016-12-01

Real time observations of the dynamics between dust input, primary production, and export production in deep oligotrophic waters are extremely rare. This is especially true in the context of the direct response and lag time between nutrient supply (e.g., dust), the oceanic biogeochemical response and the signal transfer from the water to sedimentary record. Here, we present the first direct measurments of bulk and export production fluxes in the deep oligotrophic Gulf of Aqaba (GOA), northern Red Sea, located between the hyper-arid Sahara and Arabia Deserts. This study is based on a coupled sediment trap array that provides daily- and monthly- resolution since January 2014. This coupled configuration allows for a unique collection of marine particulates, whereby the annual and seasonal patterns can be evaluated in the context of discrete (daily-timescale) events such as abrupt dust storms, floods and biological blooms. The marine organic C and N fluxes range annually between 0.02-0.25 and 0.001-0.1 g d-1 m-2, respectively. Both show a sharp decay with depth, corresponding to the "Martin curve" (Martin et al., 1987, Deep-Sea Research, 34, 267-285). Importantly, the daily-resolution sampling provides insights to the seasonal increase in export production during the winter and early spring. Rather than a smooth seasonal cycle, this increase is driven by only very few short events, lasting no more than a few days, during which export production increases by an order of magnitude above the baseline. Yet, the nature of these export production "spikes" is non-unique because they reflect different "trigger" events such as dust storms or water column mixing. Accordingly, we present a quantitative evaluation of the observations in the context of coeval dust flux records and the physical and chemical configuration of the GOA over the time of sampling period, and present and quantitative mass balance of particle fluxes in this deep yet land-locked marine setting.

Large uncertainties in observed daily precipitation extremes over land

NASA Astrophysics Data System (ADS)

Herold, Nicholas; Behrangi, Ali; Alexander, Lisa V.

2017-01-01

We explore uncertainties in observed daily precipitation extremes over the terrestrial tropics and subtropics (50°S-50°N) based on five commonly used products: the Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) dataset, the Global Precipitation Climatology Centre-Full Data Daily (GPCC-FDD) dataset, the Tropical Rainfall Measuring Mission (TRMM) multi-satellite research product (T3B42 v7), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), and the Global Precipitation Climatology Project's One-Degree Daily (GPCP-1DD) dataset. We use the precipitation indices R10mm and Rx1day, developed by the Expert Team on Climate Change Detection and Indices, to explore the behavior of "moderate" and "extreme" extremes, respectively. In order to assess the sensitivity of extreme precipitation to different grid sizes we perform our calculations on four common spatial resolutions (0.25° × 0.25°, 1° × 1°, 2.5° × 2.5°, and 3.75° × 2.5°). The impact of the chosen "order of operation" in calculating these indices is also determined. Our results show that moderate extremes are relatively insensitive to product and resolution choice, while extreme extremes can be very sensitive. For example, at 0.25° × 0.25° quasi-global mean Rx1day values vary from 37 mm in PERSIANN-CDR to 62 mm in T3B42. We find that the interproduct spread becomes prominent at resolutions of 1° × 1° and finer, thus establishing a minimum effective resolution at which observational products agree. Without improvements in interproduct spread, these exceedingly large observational uncertainties at high spatial resolution may limit the usefulness of model evaluations. As has been found previously, resolution sensitivity can be largely eliminated by applying an order of operation where indices are calculated prior to regridding. However, this approach is not appropriate when true area averages are desired (e.g., for model evaluations).

Real-Time Eddy-Resolving Ocean Prediction in the Caribbean

NASA Astrophysics Data System (ADS)

Hurlburt, H. E.; Smedstad, O. M.; Shriver, J. F.; Townsend, T. L.; Murphy, S. J.

2001-12-01

A {1/16}o eddy-resolving, nearly global ocean prediction system has been developed by the Naval Research Laboratory (NRL), Stennis Space Center, MS. It has been run in real-time by the Naval Oceanographic Office (NAVO), Stennis Space Center, MS since 18 Oct 2000 with daily updates for the nowcast and 30-day forecasts performed every Wednesday. The model has ~8 km resolution in the Caribbean region and assimilates real-time altimeter sea surface height (SSH) data from ERS-2, GFO and TOPEX/POSEIDON plus multi-channel sea surface temperature (MCSST) from satellite IR. Real-time and archived results from the system can be seen at web site: http://www7320.nrlssc.navy.mil/global\

High-resolution daily gridded datasets of air temperature and wind speed for Europe

NASA Astrophysics Data System (ADS)

Brinckmann, S.; Krähenmann, S.; Bissolli, P.

2015-08-01

New high-resolution datasets for near surface daily air temperature (minimum, maximum and mean) and daily mean wind speed for Europe (the CORDEX domain) are provided for the period 2001-2010 for the purpose of regional model validation in the framework of DecReg, a sub-project of the German MiKlip project, which aims to develop decadal climate predictions. The main input data sources are hourly SYNOP observations, partly supplemented by station data from the ECA&D dataset (http://www.ecad.eu). These data are quality tested to eliminate erroneous data and various kinds of inhomogeneities. Grids in a resolution of 0.044° (5 km) are derived by spatial interpolation of these station data into the CORDEX area. For temperature interpolation a modified version of a regression kriging method developed by Krähenmann et al. (2011) is used. At first, predictor fields of altitude, continentality and zonal mean temperature are chosen for a regression applied to monthly station data. The residuals of the monthly regression and the deviations of the daily data from the monthly averages are interpolated using simple kriging in a second and third step. For wind speed a new method based on the concept used for temperature was developed, involving predictor fields of exposure, roughness length, coastal distance and ERA Interim reanalysis wind speed at 850 hPa. Interpolation uncertainty is estimated by means of the kriging variance and regression uncertainties. Furthermore, to assess the quality of the final daily grid data, cross validation is performed. Explained variance ranges from 70 to 90 % for monthly temperature and from 50 to 60 % for monthly wind speed. The resulting RMSE for the final daily grid data amounts to 1-2 °C and 1-1.5 m s-1 (depending on season and parameter) for daily temperature parameters and daily mean wind speed, respectively. The datasets presented in this article are published at http://dx.doi.org/10.5676/DWD_CDC/DECREG0110v1.

Modelling of human exposure to air pollution in the urban environment: a GPS-based approach.

PubMed

Dias, Daniela; Tchepel, Oxana

2014-03-01

The main objective of this work was the development of a new modelling tool for quantification of human exposure to traffic-related air pollution within distinct microenvironments by using a novel approach for trajectory analysis of the individuals. For this purpose, mobile phones with Global Positioning System technology have been used to collect daily trajectories of the individuals with higher temporal resolution and a trajectory data mining, and geo-spatial analysis algorithm was developed and implemented within a Geographical Information System to obtain time-activity patterns. These data were combined with air pollutant concentrations estimated for several microenvironments. In addition to outdoor, pollutant concentrations in distinct indoor microenvironments are characterised using a probabilistic approach. An example of the application for PM2.5 is presented and discussed. The results obtained for daily average individual exposure correspond to a mean value of 10.6 and 6.0-16.4 μg m(-3) in terms of 5th-95th percentiles. Analysis of the results shows that the use of point air quality measurements for exposure assessment will not explain the intra- and inter-variability of individuals' exposure levels. The methodology developed and implemented in this work provides time-sequence of the exposure events thus making possible association of the exposure with the individual activities and delivers main statistics on individual's air pollution exposure with high spatio-temporal resolution.

An improved bias correction method of daily rainfall data using a sliding window technique for climate change impact assessment

NASA Astrophysics Data System (ADS)

Smitha, P. S.; Narasimhan, B.; Sudheer, K. P.; Annamalai, H.

2018-01-01

Regional climate models (RCMs) are used to downscale the coarse resolution General Circulation Model (GCM) outputs to a finer resolution for hydrological impact studies. However, RCM outputs often deviate from the observed climatological data, and therefore need bias correction before they are used for hydrological simulations. While there are a number of methods for bias correction, most of them use monthly statistics to derive correction factors, which may cause errors in the rainfall magnitude when applied on a daily scale. This study proposes a sliding window based daily correction factor derivations that help build reliable daily rainfall data from climate models. The procedure is applied to five existing bias correction methods, and is tested on six watersheds in different climatic zones of India for assessing the effectiveness of the corrected rainfall and the consequent hydrological simulations. The bias correction was performed on rainfall data downscaled using Conformal Cubic Atmospheric Model (CCAM) to 0.5° × 0.5° from two different CMIP5 models (CNRM-CM5.0, GFDL-CM3.0). The India Meteorological Department (IMD) gridded (0.25° × 0.25°) observed rainfall data was considered to test the effectiveness of the proposed bias correction method. The quantile-quantile (Q-Q) plots and Nash Sutcliffe efficiency (NSE) were employed for evaluation of different methods of bias correction. The analysis suggested that the proposed method effectively corrects the daily bias in rainfall as compared to using monthly factors. The methods such as local intensity scaling, modified power transformation and distribution mapping, which adjusted the wet day frequencies, performed superior compared to the other methods, which did not consider adjustment of wet day frequencies. The distribution mapping method with daily correction factors was able to replicate the daily rainfall pattern of observed data with NSE value above 0.81 over most parts of India. Hydrological simulations forced using the bias corrected rainfall (distribution mapping and modified power transformation methods that used the proposed daily correction factors) was similar to those simulated by the IMD rainfall. The results demonstrate that the methods and the time scales used for bias correction of RCM rainfall data have a larger impact on the accuracy of the daily rainfall and consequently the simulated streamflow. The analysis suggests that the distribution mapping with daily correction factors can be preferred for adjusting RCM rainfall data irrespective of seasons or climate zones for realistic simulation of streamflow.

Using Global Positioning Systems (GPS) and temperature data to generate time-activity classifications for estimating personal exposure in air monitoring studies: an automated method.

PubMed

Nethery, Elizabeth; Mallach, Gary; Rainham, Daniel; Goldberg, Mark S; Wheeler, Amanda J

2014-05-08

Personal exposure studies of air pollution generally use self-reported diaries to capture individuals' time-activity data. Enhancements in the accuracy, size, memory and battery life of personal Global Positioning Systems (GPS) units have allowed for higher resolution tracking of study participants' locations. Improved time-activity classifications combined with personal continuous air pollution sampling can improve assessments of location-related air pollution exposures for health studies. Data was collected using a GPS and personal temperature from 54 children with asthma living in Montreal, Canada, who participated in a 10-day personal air pollution exposure study. A method was developed that incorporated personal temperature data and then matched a participant's position against available spatial data (i.e., road networks) to generate time-activity categories. The diary-based and GPS-generated time-activity categories were compared and combined with continuous personal PM2.5 data to assess the impact of exposure misclassification when using diary-based methods. There was good agreement between the automated method and the diary method; however, the automated method (means: outdoors = 5.1%, indoors other =9.8%) estimated less time spent in some locations compared to the diary method (outdoors = 6.7%, indoors other = 14.4%). Agreement statistics (AC1 = 0.778) suggest 'good' agreement between methods over all location categories. However, location categories (Outdoors and Transit) where less time is spent show greater disagreement: e.g., mean time "Indoors Other" using the time-activity diary was 14.4% compared to 9.8% using the automated method. While mean daily time "In Transit" was relatively consistent between the methods, the mean daily exposure to PM2.5 while "In Transit" was 15.9 μg/m3 using the automated method compared to 6.8 μg/m3 using the daily diary. Mean times spent in different locations as categorized by a GPS-based method were comparable to those from a time-activity diary, but there were differences in estimates of exposure to PM2.5 from the two methods. An automated GPS-based time-activity method will reduce participant burden, potentially providing more accurate and unbiased assessments of location. Combined with continuous air measurements, the higher resolution GPS data could present a different and more accurate picture of personal exposures to air pollution.

Using Global Positioning Systems (GPS) and temperature data to generate time-activity classifications for estimating personal exposure in air monitoring studies: an automated method

PubMed Central

2014-01-01

Background Personal exposure studies of air pollution generally use self-reported diaries to capture individuals’ time-activity data. Enhancements in the accuracy, size, memory and battery life of personal Global Positioning Systems (GPS) units have allowed for higher resolution tracking of study participants’ locations. Improved time-activity classifications combined with personal continuous air pollution sampling can improve assessments of location-related air pollution exposures for health studies. Methods Data was collected using a GPS and personal temperature from 54 children with asthma living in Montreal, Canada, who participated in a 10-day personal air pollution exposure study. A method was developed that incorporated personal temperature data and then matched a participant’s position against available spatial data (i.e., road networks) to generate time-activity categories. The diary-based and GPS-generated time-activity categories were compared and combined with continuous personal PM2.5 data to assess the impact of exposure misclassification when using diary-based methods. Results There was good agreement between the automated method and the diary method; however, the automated method (means: outdoors = 5.1%, indoors other =9.8%) estimated less time spent in some locations compared to the diary method (outdoors = 6.7%, indoors other = 14.4%). Agreement statistics (AC1 = 0.778) suggest ‘good’ agreement between methods over all location categories. However, location categories (Outdoors and Transit) where less time is spent show greater disagreement: e.g., mean time “Indoors Other” using the time-activity diary was 14.4% compared to 9.8% using the automated method. While mean daily time “In Transit” was relatively consistent between the methods, the mean daily exposure to PM2.5 while “In Transit” was 15.9 μg/m3 using the automated method compared to 6.8 μg/m3 using the daily diary. Conclusions Mean times spent in different locations as categorized by a GPS-based method were comparable to those from a time-activity diary, but there were differences in estimates of exposure to PM2.5 from the two methods. An automated GPS-based time-activity method will reduce participant burden, potentially providing more accurate and unbiased assessments of location. Combined with continuous air measurements, the higher resolution GPS data could present a different and more accurate picture of personal exposures to air pollution. PMID:24885722

The interplay of couple's shared time, women's intimacy, and intradyadic stress.

PubMed

Milek, Anne; Butler, Emily A; Bodenmann, Guy

2015-12-01

Theoretically, spending time together should be central for couples to build intimacy and should be associated with less relationship stress; however, few empirical studies have examined these links. The present study used 14 days of diary data from 92 women to investigate the interplay between the amount of time they spent with their partner (shared time), intimacy, and daily stress originating inside the relationship (intradyadic stress) on a within- and between-personal level. Multilevel analyses revealed moderation patterns: For example, when women spent more time with their partners than usual on a weekday with low levels of intradyadic stress, they reported higher intimacy. These associations varied substantially between women and were weaker on the weekend or on days with high levels of intradyadic stress. At the between-person level, higher average shared time appeared to buffer the negative association between intradyadic stress and intimacy. Our results suggest that daily fluctuations in intradyadic stress, intimacy, and shared time may have different implications compared with aggregated amounts of those variables. Spending more time together on a weekday with low intimacy might be linked to more intradyadic stress, but aggregated over the long run, spending more time together may provide opportunities for stress resolution and help couples to maintain their intimacy. (c) 2015 APA, all rights reserved).

Development of a MODIS-Derived Surface Albedo Data Set: An Improved Model Input for Processing the NSRDB

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

Maclaurin, Galen; Sengupta, Manajit; Xie, Yu

A significant source of bias in the transposition of global horizontal irradiance to plane-of-array (POA) irradiance arises from inaccurate estimations of surface albedo. The current physics-based model used to produce the National Solar Radiation Database (NSRDB) relies on model estimations of surface albedo from a reanalysis climatalogy produced at relatively coarse spatial resolution compared to that of the NSRDB. As an input to spectral decomposition and transposition models, more accurate surface albedo data from remotely sensed imagery at finer spatial resolutions would improve accuracy in the final product. The National Renewable Energy Laboratory (NREL) developed an improved white-sky (bi-hemispherical reflectance)more » broadband (0.3-5.0 ..mu..m) surface albedo data set for processing the NSRDB from two existing data sets: a gap-filled albedo product and a daily snow cover product. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Terra and Aqua satellites have provided high-quality measurements of surface albedo at 30 arc-second spatial resolution and 8-day temporal resolution since 2001. The high spatial and temporal resolutions and the temporal coverage of the MODIS sensor will allow for improved modeling of POA irradiance in the NSRDB. However, cloud and snow cover interfere with MODIS observations of ground surface albedo, and thus they require post-processing. The MODIS production team applied a gap-filling methodology to interpolate observations obscured by clouds or ephemeral snow. This approach filled pixels with ephemeral snow cover because the 8-day temporal resolution is too coarse to accurately capture the variability of snow cover and its impact on albedo estimates. However, for this project, accurate representation of daily snow cover change is important in producing the NSRDB. Therefore, NREL also used the Integrated Multisensor Snow and Ice Mapping System data set, which provides daily snow cover observations of the Northern Hemisphere for the temporal extent of the NSRDB (1998-2015). We provide a review of validation studies conducted on these two products and describe the methodology developed by NREL to remap the data products to the NSRDB grid and integrate them into a seamless daily data set.« less

Downscaling Surface Temperature Image with TsHARP

USDA-ARS?s Scientific Manuscript database

Daily evapotranspiration (ET) maps would significantly improve assessing crop water requirements, especially in the Texas High Plains (THP) where the supply of irrigation water is limited. Evapotranspireation maps derived from satellite data with daily coverage such as MODIS (Moderate Resolution Ima...

Validation of a new SAFRAN-based gridded precipitation product for Spain and comparisons to Spain02 and ERA-Interim

NASA Astrophysics Data System (ADS)

Quintana-Seguí, Pere; Turco, Marco; Herrera, Sixto; Miguez-Macho, Gonzalo

2017-04-01

Offline land surface model (LSM) simulations are useful for studying the continental hydrological cycle. Because of the nonlinearities in the models, the results are very sensitive to the quality of the meteorological forcing; thus, high-quality gridded datasets of screen-level meteorological variables are needed. Precipitation datasets are particularly difficult to produce due to the inherent spatial and temporal heterogeneity of that variable. They do, however, have a large impact on the simulations, and it is thus necessary to carefully evaluate their quality in great detail. This paper reports the quality of two high-resolution precipitation datasets for Spain at the daily time scale: the new SAFRAN-based dataset and Spain02. SAFRAN is a meteorological analysis system that was designed to force LSMs and has recently been extended to the entirety of Spain for a long period of time (1979/1980-2013/2014). Spain02 is a daily precipitation dataset for Spain and was created mainly to validate regional climate models. In addition, ERA-Interim is included in the comparison to show the differences between local high-resolution and global low-resolution products. The study compares the different precipitation analyses with rain gauge data and assesses their temporal and spatial similarities to the observations. The validation of SAFRAN with independent data shows that this is a robust product. SAFRAN and Spain02 have very similar scores, although the latter slightly surpasses the former. The scores are robust with altitude and throughout the year, save perhaps in summer when a diminished skill is observed. As expected, SAFRAN and Spain02 perform better than ERA-Interim, which has difficulty capturing the effects of the relief on precipitation due to its low resolution. However, ERA-Interim reproduces spells remarkably well in contrast to the low skill shown by the high-resolution products. The high-resolution gridded products overestimate the number of precipitation days, which is a problem that affects SAFRAN more than Spain02 and is likely caused by the interpolation method. Both SAFRAN and Spain02 underestimate high precipitation events, but SAFRAN does so more than Spain02. The overestimation of low precipitation events and the underestimation of intense episodes will probably have hydrological consequences once the data are used to force a land surface or hydrological model.

Estimation of Coastal Freshwater Discharge into Prince William Sound using a High-Resolution Hydrological Model

NASA Astrophysics Data System (ADS)

Beamer, J. P.; Hill, D. F.; Liston, G. E.; Arendt, A. A.; Hood, E. W.

2013-12-01

In Prince William Sound (PWS), Alaska, there is a pressing need for accurate estimates of the spatial and temporal variations in coastal freshwater discharge (FWD). FWD into PWS originates from streamflow due to rainfall, annual snowmelt, and changes in stored glacier mass and is important because it helps establish spatial and temporal patterns in ocean salinity and temperature, and is a time-varying boundary condition for oceanographic circulation models. Previous efforts to model FWD into PWS have been heavily empirical, with many physical processes absorbed into calibration coefficients that, in many cases, were calibrated to streams and rivers not hydrologically similar to those discharging into PWS. In this work we adapted and validated a suite of high-resolution (in space and time), physically-based, distributed weather, snowmelt, and runoff-routing models designed specifically for snow melt- and glacier melt-dominated watersheds like PWS in order to: 1) provide high-resolution, real-time simulations of snowpack and FWD, and 2) provide a record of historical variations of FWD. SnowModel, driven with gridded topography, land cover, and 32 years (1979-2011) of 3-hourly North American Regional Reanalysis (NARR) atmospheric forcing data, was used to simulate snowpack accumulation and melt across a PWS model domain. SnowModel outputs of daily snow water equivalent (SWE) depth and grid-cell runoff volumes were then coupled with HydroFlow, a runoff-routing model which routed snowmelt, glacier-melt, and rainfall to each watershed outlet (PWS coastline) in the simulation domain. The end product was a continuous 32-year simulation of daily FWD into PWS. In order to validate the models, SWE and snow depths from SnowModel were compared with observed SWE and snow depths from SnoTel and snow survey data, and discharge from HydroFlow was compared with observed streamflow measurements. As a second phase of this research effort, the coupled models will be set-up to run in real-time, where daily measurements from weather stations in the PWS will be used to drive simulations of snow cover and streamflow. In addition, we will deploy a strategic array of instrumentation aimed at validating the simulated weather estimates and the calculations of freshwater discharge. Upon successful implementation and validation of the modeling system, it will join established and ongoing computational and observational efforts that have a common goal of establishing a comprehensive understanding of the physical behavior of PWS.

Carbon fluxes in tropical forest ecosystems: the value of Eddy-covariance data for individual-based dynamic forest gap models

NASA Astrophysics Data System (ADS)

Roedig, Edna; Cuntz, Matthias; Huth, Andreas

2015-04-01

The effects of climatic inter-annual fluctuations and human activities on the global carbon cycle are uncertain and currently a major issue in global vegetation models. Individual-based forest gap models, on the other hand, model vegetation structure and dynamics on a small spatial (<100 ha) and large temporal scale (>1000 years). They are well-established tools to reproduce successions of highly-diverse forest ecosystems and investigate disturbances as logging or fire events. However, the parameterizations of the relationships between short-term climate variability and forest model processes are often uncertain in these models (e.g. daily variable temperature and gross primary production (GPP)) and cannot be constrained from forest inventories. We addressed this uncertainty and linked high-resolution Eddy-covariance (EC) data with an individual-based forest gap model. The forest model FORMIND was applied to three diverse tropical forest sites in the Amazonian rainforest. Species diversity was categorized into three plant functional types. The parametrizations for the steady-state of biomass and forest structure were calibrated and validated with different forest inventories. The parameterizations of relationships between short-term climate variability and forest model processes were evaluated with EC-data on a daily time step. The validations of the steady-state showed that the forest model could reproduce biomass and forest structures from forest inventories. The daily estimations of carbon fluxes showed that the forest model reproduces GPP as observed by the EC-method. Daily fluctuations of GPP were clearly reflected as a response to daily climate variability. Ecosystem respiration remains a challenge on a daily time step due to a simplified soil respiration approach. In the long-term, however, the dynamic forest model is expected to estimate carbon budgets for highly-diverse tropical forests where EC-measurements are rare.

Global intensification in observed short-duration rainfall extremes

NASA Astrophysics Data System (ADS)

Fowler, H. J.; Lewis, E.; Guerreiro, S.; Blenkinsop, S.; Barbero, R.; Westra, S.; Lenderink, G.; Li, X.

2017-12-01

Extreme rainfall events are expected to intensify with a warming climate and this is currently driving extensive research. While daily rainfall extremes are widely thought to have increased globally in recent decades, changes in rainfall extremes on shorter timescales, often associated with flash flooding, have not been documented at global scale due to surface observational limitations and the lack of a global sub-daily rainfall database. The access to and use of such data remains a challenge. For the first time, we have synthesized across multiple data sources providing gauge-based sub-daily rainfall observations across the globe over the last 6 decades. This forms part of the INTENSE project (part of the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges (GEWEX) Hydroclimate Project cross-cut on sub-daily rainfall). A set of global hydroclimatic indices have been produced based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. This will provide a unique global data resource on sub-daily precipitation whose derived indices will be freely available to the wider scientific community. Because of the physical connection between global warming and the moisture budget, we also sought to infer long-term changes in sub-daily rainfall extremes contingent on global mean temperature. Whereas the potential influence of global warming is uncertain at regional scales, where natural variability dominates, aggregating surface stations across parts of the world may increase the global warming-induced signal. Changes in terms of annual maximum rainfall across various resolutions ranging from 1-h to 24-h are presented and discussed.

Biomass burning emissions of reactive gases estimated from satellite data analysis and ecosystem modeling for the Brazilian Amazon region

NASA Astrophysics Data System (ADS)

Potter, Christopher; Brooks-Genovese, Vanessa; Klooster, Steven; Torregrosa, Alicia

2002-10-01

To produce a new daily record of trace gas emissions from biomass burning events for the Brazilian Legal Amazon, we have combined satellite advanced very high resolution radiometer (AVHRR) data on fire counts together for the first time with vegetation greenness imagery as inputs to an ecosystem biomass model at 8 km spatial resolution. This analysis goes beyond previous estimates for reactive gas emissions from Amazon fires, owing to a more detailed geographic distribution estimate of vegetation biomass, coupled with daily fire activity for the region (original 1 km resolution), and inclusion of fire effects in extensive areas of the Legal Amazon (defined as the Brazilian states of Acre, Amapá, Amazonas, Maranhao, Mato Grosso, Pará, Rondônia, Roraima, and Tocantins) covered by open woodland, secondary forests, savanna, and pasture vegetation. Results from our emissions model indicate that annual emissions from Amazon deforestation and biomass burning in the early 1990s total to 102 Tg yr-1 carbon monoxide (CO) and 3.5 Tg yr-1 nitrogen oxides (NOx). Peak daily burning emissions, which occurred in early September 1992, were estimated at slightly more than 3 Tg d-1for CO and 0.1 Tg d-1for NOx flux to the atmosphere. Other burning source fluxes of gases with relatively high emission factors are reported, including methane (CH4), nonmethane hydrocarbons (NMHC), and sulfur dioxide (SO2), in addition to total particulate matter (TPM). We estimate the Brazilian Amazon region to be a source of between one fifth and one third for each of these global emission fluxes to the atmosphere. The regional distribution of burning emissions appears to be highest in the Brazilian states of Maranhao and Tocantins, mainly from burning outside of moist forest areas, and in Pará and Mato Grosso, where we identify important contributions from primary forest cutting and burning. These new daily emission estimates of reactive gases from biomass burning fluxes are designed to be used as detailed spatial and temporal inputs to computer models and data analysis of tropospheric chemistry over the tropical region.

PDF added value of a high resolution climate simulation for precipitation

NASA Astrophysics Data System (ADS)

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

2015-04-01

General Circulation Models (GCMs) are models suitable to study the global atmospheric system, its evolution and response to changes in external forcing, namely to increasing emissions of CO2. However, the resolution of GCMs, of the order of 1o, is not sufficient to reproduce finer scale features of the atmospheric flow related to complex topography, coastal processes and boundary layer processes, and higher resolution models are needed to describe observed weather and climate. The latter are known as Regional Climate Models (RCMs) and are widely used to downscale GCMs results for many regions of the globe and are able to capture physically consistent regional and local circulations. Most of the RCMs evaluations rely on the comparison of its results with observations, either from weather stations networks or regular gridded datasets, revealing the ability of RCMs to describe local climatic properties, and assuming most of the times its higher performance in comparison with the forcing GCMs. The additional climatic details given by RCMs when compared with the results of the driving models is usually named as added value, and it's evaluation is still scarce and controversial in the literuature. Recently, some studies have proposed different methodologies to different applications and processes to characterize the added value of specific RCMs. A number of examples reveal that some RCMs do add value to GCMs in some properties or regions, and also the opposite, elighnening that RCMs may add value to GCM resuls, but improvements depend basically on the type of application, model setup, atmospheric property and location. The precipitation can be characterized by histograms of daily precipitation, or also known as probability density functions (PDFs). There are different strategies to evaluate the quality of both GCMs and RCMs in describing the precipitation PDFs when compared to observations. Here, we present a new method to measure the PDF added value obtained from dynamical downscaling, based on simple PDF skill scores. The measure can assess the full quality of the PDFs and at the same time integrates a flexible manner to weight differently the PDF tails. In this study we apply the referred method to characaterize the PDF added value of a high resolution simulation with the WRF model. Results from a WRF climate simulation centred at the Iberian Penisnula with two nested grids, a larger one at 27km and a smaller one at 9km. This simulation is forced by ERA-Interim. The observational data used covers from rain gauges precipitation records to observational regular grids of daily precipitation. Two regular gridded precipitation datasets are used. A Portuguese grid precipitation dataset developed at 0.2°× 0.2°, from observed rain gauges daily precipitation. A second one corresponding to the ENSEMBLES observational gridded dataset for Europe, which includes daily precipitation values at 0.25°. The analisys shows an important PDF added value from the higher resolution simulation, regarding the full PDF and the extremes. This method shows higher potential to be applied to other simulation exercises and to evaluate other variables.

Estimating Soil Moisture at High Spatial Resolution with Three Radiometric Satellite Products: A Study from a South-Eastern Australian Catchment

NASA Astrophysics Data System (ADS)

Senanayake, I. P.; Yeo, I. Y.; Tangdamrongsub, N.; Willgoose, G. R.; Hancock, G. R.; Wells, T.; Fang, B.; Lakshmi, V.

2017-12-01

Long-term soil moisture datasets at high spatial resolution are important in agricultural, hydrological, and climatic applications. The soil moisture estimates can be achieved using satellite remote sensing observations. However, the satellite soil moisture data are typically available at coarse spatial resolutions ( several tens of km), therefore require further downscaling. Different satellite soil moisture products have to be conjointly employed in developing a consistent time-series of high resolution soil moisture, while the discrepancies amongst different satellite retrievals need to be resolved. This study aims to downscale three different satellite soil moisture products, the Soil Moisture and Ocean Salinity (SMOS, 25 km), the Soil Moisture Active Passive (SMAP, 36 km) and the SMAP-Enhanced (9 km), and to conduct an inter-comparison of the downscaled results. The downscaling approach is developed based on the relationship between the diurnal temperature difference and the daily mean soil moisture content. The approach is applied to two sub-catchments (Krui and Merriwa River) of the Goulburn River catchment in the Upper Hunter region (NSW, Australia) to estimate soil moisture at 1 km resolution for 2015. The three coarse spatial resolution soil moisture products and their downscaled results will be validated with the in-situ observations obtained from the Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS) network. The spatial and temporal patterns of the downscaled results will also be analysed. This study will provide the necessary insights for data selection and bias corrections to maintain the consistency of a long-term high resolution soil moisture dataset. The results will assist in developing a time-series of high resolution soil moisture data over the south-eastern Australia.

The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

2014-12-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

A high-resolution conceptual model for diffuse organic micropollutant loads in streams

NASA Astrophysics Data System (ADS)

Stamm, Christian; Honti, Mark; Ghielmetti, Nico

2013-04-01

The ecological state of surface waters has become the dominant aspect in water quality assessments. Toxicity is a key determinant of the ecological state, but organic micropollutants (OMP) are seldom monitored with the same spatial and temporal frequency as for example nutrients, mainly due the demanding analytical methods and costs. However, diffuse transport pathways are at least equally complex for OMPs as for nutrients and there are still significant knowledge gaps. Moreover, concentrations of the different compounds would need to be known with fairly high temporal resolution because acute toxicity can be as important as the chronic one. Fully detailed mechanistic models of diffuse OMP loads require an immense set of site-specific knowledge and are rarely applicable for catchments lacking an exceptional monitoring coverage. Simple empirical methods are less demanding but usually work with more temporal aggregation and that's why they have limited possibilities to support the estimation of the ecological state. This study presents a simple conceptual model that aims to simulate the concentrations of selected organic micropollutants with daily resolution at 11 locations in the stream network of a small catchment (46 km2). The prerequisite is a known hydrological and meteorological background (daily discharge, precipitation and air temperature time series), a land use map and some historic measurements of the desired compounds. The model is conceptual in the sense that all important diffuse transport pathways are simulated separately, but each with a simple empirical process rate. Consequently, some site-specific observations are required to calibrate the model, but afterwards the model can be used for forecasting and scenario analysis as the calibrated process rates typically describe invariant properties of the catchment. We simulated 6 different OMPs from the categories of agricultural and urban pesticides and urban biocides. The application of agricultural pesticides was also simulated with the model using a heat-sum approach. Calibration was carried out with weekly aggregated samples covering the growing season in 2 years. The model could reproduce the observed OMP concentrations with varying success. Compounds that are less persistent in the environment and thus have a dominant temporal dynamics (pesticides with a short half-life) could be simulated in general better than the persistent ones. For the latter group the relatively stable available stock meant that there were no clear seasonal dynamics, which revealed that transport processes are quite uncertain even when daily rainfall is used as the main driver. Nevertheless the daily concentration distribution could still be simulated with higher accuracy than the individual peaks. Thus we can model the concentration-duration relationship for daily resolution in an acceptable way for each compound.

Constructing Synoptic Maps of Stratospheric Column Ozone from HALOE, SAGE and Balloonsonde Data Using Potential Vorticity Isentropic Coordinate Transformations

NASA Technical Reports Server (NTRS)

Hollandsworth, Stacey M.; Schoeberl, Mark R.; Morris, Gary A.; Long, Craig; Zhou, Shuntai; Miller, Alvin J.

1999-01-01

In this study we utilize potential vorticity - isentropic (PVI) coordinate transformations as a means of combining ozone data from different sources to construct daily, synthetic three-dimensional ozone fields. This methodology has been used successfully to reconstruct ozone maps in particular regions from aircraft data over the period of the aircraft campaign. We expand this method to create high-resolution daily global maps of profile ozone data, particularly in the lower stratosphere, where high-resolution ozone data are sparse. Ozone climatologies in PVI-space are constructed from satellite-based SAGE II and UARS/HALOE data, both of which-use solar occultation techniques to make high vertical resolution ozone profile measurements, but with low spatial resolution. A climatology from ground-based balloonsonde data is also created. The climatologies are used to establish the relationship between ozone and dynamical variability, which is defined by the potential vorticity (in the form of equivalent latitude) and potential temperature fields. Once a PVI climatology has been created from data taken by one or more instruments, high-resolution daily profile ozone field estimates are constructed based solely on the PVI fields, which are available on a daily basis from NCEP analysis. These profile ozone maps could be used for a variety of applications, including use in conjunction with total ozone maps to create a daily tropospheric ozone product, as input to forecast models, or as a tool for validating independent ozone measurements when correlative data are not available. This technique is limited to regions where the ozone is a long-term tracer and the flow is adiabatic. We evaluate the internal consistency of the technique by transforming the ozone back to physical space and comparing to the original profiles. Biases in the long-term average of the differences are used to identify regions where the technique is consistently introducing errors. Initial results show the technique is useful in the lower stratosphere at most latitudes throughout the year,and in the winter hemisphere in the middle stratosphere. The results are problematic in the summer hemisphere middle stratosphere due to increased ozone photochemistry and weak PV gradients. Alternate techniques in these regions will be discussed. An additional limitation is the quality and resolution of the meteorological data.

Lightning Forcing in Global Fire Models: The Importance of Temporal Resolution

NASA Astrophysics Data System (ADS)

Felsberg, A.; Kloster, S.; Wilkenskjeld, S.; Krause, A.; Lasslop, G.

2018-01-01

In global fire models, lightning is typically prescribed from observational data with monthly mean temporal resolution while meteorological forcings, such as precipitation or temperature, are prescribed in a daily resolution. In this study, we investigate the importance of the temporal resolution of the lightning forcing for the simulation of burned area by varying from daily to monthly and annual mean forcing. For this, we utilize the vegetation fire model JSBACH-SPITFIRE to simulate burned area, forced with meteorological and lightning data derived from the general circulation model ECHAM6. On a global scale, differences in burned area caused by lightning forcing applied in coarser temporal resolution stay below 0.55% compared to the use of daily mean forcing. Regionally, however, differences reach up to 100%, depending on the region and season. Monthly averaged lightning forcing as well as the monthly lightning climatology cause differences through an interaction between lightning ignitions and fire prone weather conditions, accounted for by the fire danger index. This interaction leads to decreased burned area in the boreal zone and increased burned area in the Tropics and Subtropics under the coarser temporal resolution. The exclusion of interannual variability, when forced with the lightning climatology, has only a minor impact on the simulated burned area. Annually averaged lightning forcing causes differences as a direct result of the eliminated seasonal characteristics of lightning. Burned area is decreased in summer and increased in winter where fuel is available. Regions with little seasonality, such as the Tropics and Subtropics, experience an increase in burned area.

3D Orbit Visualization for Earth-Observing Missions

NASA Technical Reports Server (NTRS)

Jacob, Joseph C.; Plesea, Lucian; Chafin, Brian G.; Weiss, Barry H.

2011-01-01

This software visualizes orbit paths for the Orbiting Carbon Observatory (OCO), but was designed to be general and applicable to any Earth-observing mission. The software uses the Google Earth user interface to provide a visual mechanism to explore spacecraft orbit paths, ground footprint locations, and local cloud cover conditions. In addition, a drill-down capability allows for users to point and click on a particular observation frame to pop up ancillary information such as data product filenames and directory paths, latitude, longitude, time stamp, column-average dry air mole fraction of carbon dioxide, and solar zenith angle. This software can be integrated with the ground data system for any Earth-observing mission to automatically generate daily orbit path data products in Google Earth KML format. These KML data products can be directly loaded into the Google Earth application for interactive 3D visualization of the orbit paths for each mission day. Each time the application runs, the daily orbit paths are encapsulated in a KML file for each mission day since the last time the application ran. Alternatively, the daily KML for a specified mission day may be generated. The application automatically extracts the spacecraft position and ground footprint geometry as a function of time from a daily Level 1B data product created and archived by the mission s ground data system software. In addition, ancillary data, such as the column-averaged dry air mole fraction of carbon dioxide and solar zenith angle, are automatically extracted from a Level 2 mission data product. Zoom, pan, and rotate capability are provided through the standard Google Earth interface. Cloud cover is indicated with an image layer from the MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the Aqua satellite, which is automatically retrieved from JPL s OnEarth Web service.

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Aqua-FM3_Edition1)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_FM1+FM4_Edition2)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF ( CER_ES9_Aqua-FM4_Edition1-CV)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF ( CER_ES9_Terra-FM1_Edition1-CV)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-09-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_TRMM-PFM_Edition1)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=1998-08-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Aqua-FM4_Edition1)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_PFM+FM2_Edition1)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Terra-FM1_Edition1)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CERES:CER_ES9_PFM+FM1_Edition2)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Aqua-FM4_Edition2)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_PFM+FM1_Edition1)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF ( CER_ES9_Aqua-FM3_Edition1-CV)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_Terra-FM2_Edition1)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

Linking Time and Space Scales in Distributed Hydrological Modelling - a case study for the VIC model

NASA Astrophysics Data System (ADS)

Melsen, Lieke; Teuling, Adriaan; Torfs, Paul; Zappa, Massimiliano; Mizukami, Naoki; Clark, Martyn; Uijlenhoet, Remko

2015-04-01

One of the famous paradoxes of the Greek philosopher Zeno of Elea (~450 BC) is the one with the arrow: If one shoots an arrow, and cuts its motion into such small time steps that at every step the arrow is standing still, the arrow is motionless, because a concatenation of non-moving parts does not create motion. Nowadays, this reasoning can be refuted easily, because we know that motion is a change in space over time, which thus by definition depends on both time and space. If one disregards time by cutting it into infinite small steps, motion is also excluded. This example shows that time and space are linked and therefore hard to evaluate separately. As hydrologists we want to understand and predict the motion of water, which means we have to look both in space and in time. In hydrological models we can account for space by using spatially explicit models. With increasing computational power and increased data availability from e.g. satellites, it has become easier to apply models at a higher spatial resolution. Increasing the resolution of hydrological models is also labelled as one of the 'Grand Challenges' in hydrology by Wood et al. (2011) and Bierkens et al. (2014), who call for global modelling at hyperresolution (~1 km and smaller). A literature survey on 242 peer-viewed articles in which the Variable Infiltration Capacity (VIC) model was used, showed that the spatial resolution at which the model is applied has decreased over the past 17 years: From 0.5 to 2 degrees when the model was just developed, to 1/8 and even 1/32 degree nowadays. On the other hand the literature survey showed that the time step at which the model is calibrated and/or validated remained the same over the last 17 years; mainly daily or monthly. Klemeš (1983) stresses the fact that space and time scales are connected, and therefore downscaling the spatial scale would also imply downscaling of the temporal scale. Is it worth the effort of downscaling your model from 1 degree to 1/24 degree, if in the end you only look at monthly runoff? In this study an attempt is made to link time and space scales in the VIC model, to study the added value of a higher spatial resolution-model for different time steps. In order to do this, four different VIC models were constructed for the Thur basin in North-Eastern Switzerland (1700 km²), a tributary of the Rhine: one lumped model, and three spatially distributed models with a resolution of respectively 1x1 km, 5x5 km, and 10x10 km. All models are run at an hourly time step and aggregated and calibrated for different time steps (hourly, daily, monthly, yearly) using a novel Hierarchical Latin Hypercube Sampling Technique (Vořechovský, 2014). For each time and space scale, several diagnostics like Nash-Sutcliffe efficiency, Kling-Gupta efficiency, all the quantiles of the discharge etc., are calculated in order to compare model performance over different time and space scales for extreme events like floods and droughts. Next to that, the effect of time and space scale on the parameter distribution can be studied. In the end we hope to find a link for optimal time and space scale combinations.

Interpolated Sounding and Gridded Sounding Value-Added Products

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

Toto, T.; Jensen, M.

Standard Atmospheric Radiation Measurement (ARM) Climate Research Facility sounding files provide atmospheric state data in one dimension of increasing time and height per sonde launch. Many applications require a quick estimate of the atmospheric state at higher time resolution. The INTERPOLATEDSONDE (i.e., Interpolated Sounding) Value-Added Product (VAP) transforms sounding data into continuous daily files on a fixed time-height grid, at 1-minute time resolution, on 332 levels, from the surface up to a limit of approximately 40 km. The grid extends that high so the full height of soundings can be captured; however, most soundings terminate at an altitude between 25more » and 30 km, above which no data is provided. Between soundings, the VAP linearly interpolates atmospheric state variables in time for each height level. In addition, INTERPOLATEDSONDE provides relative humidity scaled to microwave radiometer (MWR) observations.The INTERPOLATEDSONDE VAP, a continuous time-height grid of relative humidity-corrected sounding data, is intended to provide input to higher-order products, such as the Merged Soundings (MERGESONDE; Troyan 2012) VAP, which extends INTERPOLATEDSONDE by incorporating model data. The INTERPOLATEDSONDE VAP also is used to correct gaseous attenuation of radar reflectivity in products such as the KAZRCOR VAP.« less

Flood Mapping in the Lower Mekong River Basin Using Daily MODIS Observations

NASA Technical Reports Server (NTRS)

Fayne, Jessica V.; Bolten, John D.; Doyle, Colin S.; Fuhrmann, Sven; Rice, Matthew T.; Houser, Paul R.; Lakshmi, Venkat

2017-01-01

In flat homogenous terrain such as in Cambodia and Vietnam, the monsoon season brings significant and consistent flooding between May and November. To monitor flooding in the Lower Mekong region, the near real-time NASA Flood Extent Product (NASA-FEP) was developed using seasonal normalized difference vegetation index (NDVI) differences from the 250 m resolution Moderate Resolution Imaging Spectroradiometer (MODIS) sensor compared to daily observations. The use of a percentage change interval classification relating to various stages of flooding reduces might be confusing to viewers or potential users, and therefore reducing the product usage. To increase the product usability through simplification, the classification intervals were compared with other commonly used change detection schemes to identify the change classification scheme that best delineates flooded areas. The percentage change method used in the NASA-FEP proved to be helpful in delineating flood boundaries compared to other change detection methods. The results of the accuracy assessments indicate that the -75% NDVI change interval can be reclassified to a descriptive 'flood' classification. A binary system was used to simplify the interpretation of the NASA-FEP by removing extraneous information from lower interval change classes.

Present-Day Kinematics of the Central Mediterranean Plate Boundary Region from Large GPS Network Analysis Using the Ambizap Algorithm

NASA Astrophysics Data System (ADS)

D'Anastasio, E.; D'Agostino, N.; Avallone, A.; Blewitt, G.

2008-12-01

The large, recent increase of continuous GPS (CGPS) stations in the Central Mediterranean plate boundary zone offers the opportunity to study in detail the present-day kinematics of this actively deforming region. CGPS data from scientific and commercial networks in the Italian region is now available from more than 350 stations, including more than 130 from the RING network deployed by the Istituto Nazionale di Geofisica e Vulcanologia. The RING stations all have high quality GPS monuments and are co- located with broadband or very broadband seismometers and strong motion sensors. The analysis presented here also uses far-field data to provide reference frame control, bringing the total to over 580 CGPS stations. GPS ambiguity resolution of such a large amount of data presents a serious challenge in terms of processing time. Many scientific GPS data processing software packages address this problem by dividing the network into several clusters. In contrast, this analysis uses the new Ambizap GPS processing algorithm (Blewitt, 2008) to obtain unique, self-consistent daily ambiguity-fixed solutions for the entire network. Ambizap allows for a rapid and multiple reanalysis of large regional networks such the one presented in this work. Tests show that Ambizap reproduces solutions from time-prohibitive full-network ambiguity resolution to much less than 1 mm. Single station GPS data are first processed with the GIPSY-OASIS II software by the precise point positioning (PPP) strategy (Zumberge et al., 1997) using JPL products from ftp://sideshow.jpl.nasa.gov. Integer ambiguity resolution is then applied using Ambizap. The resulting daily solutions are aligned to the ITRF2005 reference frame. Then, using the CATS software (Williams, 2007), time series are cleaned to remove outliers and are analyzed for their noise properties, linear velocities, periodic signals and antenna jumps. Stable plate reference frames are realized by minimizing the horizontal velocities at more than 70 and 20 sites on the Eurasia and Nubia plates, respectively. The daily RMS scatter for the east coordinates (derived from PPP) in this frame is typically in the range 2-4 mm before applying Ambizap, and 1-2 mm after applying Ambizap. The solutions are then evaluated with regard to the numerous scientific motivations behind this project, ranging from the definition of strain distribution and microplate kinematics within the plate boundary, to the evaluation of tectonic strain accumulation on active faults. References: Blewitt, G. (2008), Fixed-point theorems of GPS carrier phase ambiguity resolution and their application to massive network processing: 'Ambizap', J. Geophys. Res., doi:10.1029/2008JB005736, in press. Williams, S.D.P. (2007), CATS: GPS coordinate time series analysis software, GPS solut., doi:10.1007/s10291-007-0086-4 Zumberge, J. F., M. B. Heflin, D. C. Jefferson, M. M. Watkins, and F. H. Webb (1997), Precise point positioning for the efficient and robust analysis of GPS data from large networks, J. Geophys. Res., 102, 5005-501

A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents

USGS Publications Warehouse

McShane, Ryan R.; Driscoll, Katelyn P.; Sando, Roy

2017-09-27

Many approaches have been developed for measuring or estimating actual evapotranspiration (ETa), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ETa. Several remote sensing methods can be used to estimate ETa at the high spatial resolution of agricultural fields and the large extent of river basins. More complex remote sensing methods apply an analytical approach to ETa estimation using physically based models of varied complexity that require a combination of ground-based and remote sensing data, and are grounded in the theory behind the surface energy balance model. This report, funded through cooperation with the International Joint Commission, provides an overview of selected remote sensing methods used for estimating water consumed through ETa and focuses on Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Operational Simplified Surface Energy Balance (SSEBop), two energy balance models for estimating ETa that are currently applied successfully in the United States. The METRIC model can produce maps of ETa at high spatial resolution (30 meters using Landsat data) for specific areas smaller than several hundred square kilometers in extent, an improvement in practice over methods used more generally at larger scales. Many studies validating METRIC estimates of ETa against measurements from lysimeters have shown model accuracies on daily to seasonal time scales ranging from 85 to 95 percent. The METRIC model is accurate, but the greater complexity of METRIC results in greater data requirements, and the internalized calibration of METRIC leads to greater skill required for implementation. In contrast, SSEBop is a simpler model, having reduced data requirements and greater ease of implementation without a substantial loss of accuracy in estimating ETa. The SSEBop model has been used to produce maps of ETa over very large extents (the conterminous United States) using lower spatial resolution (1 kilometer) Moderate Resolution Imaging Spectroradiometer (MODIS) data. Model accuracies ranging from 80 to 95 percent on daily to annual time scales have been shown in numerous studies that validated ETa estimates from SSEBop against eddy covariance measurements. The METRIC and SSEBop models can incorporate low and high spatial resolution data from MODIS and Landsat, but the high spatiotemporal resolution of ETa estimates using Landsat data over large extents takes immense computing power. Cloud computing is providing an opportunity for processing an increasing amount of geospatial “big data” in a decreasing period of time. For example, Google Earth EngineTM has been used to implement METRIC with automated calibration for regional-scale estimates of ETa using Landsat data. The U.S. Geological Survey also is using Google Earth EngineTM to implement SSEBop for estimating ETa in the United States at a continental scale using Landsat data.

Downscaled soil moisture from SMAP evaluated using high density observations

USDA-ARS?s Scientific Manuscript database

Recently, a soil moisture downscaling algorithm based on a regression relationship between daily temperature changes and daily average soil moisture was developed to produce an enhanced spatial resolution on soil moisture product for the Advanced Microwave Scanning Radiometer–EOS (AMSR-E) satellite ...

Cloud removing method for daily snow mapping over Central Asia and Xinjiang, China

NASA Astrophysics Data System (ADS)

Yu, Xiaoqi; Qiu, Yubao; Guo, Huadong; Chen, Lijuan

2017-02-01

Central Asia and Xinjiang, China are conjunct areas, located in the hinterland of the Eurasian continent, where the snowfall is an important water resource supplement form. The induced seasonal snow cover is vita factors to the regional energy and water balance, remote sensing plays a key role in the snow mapping filed, while the daily remote sensing products are normally contaminated by the occurrence of cloud, that obviously obstacles the utility of snow cover parameters. In this paper, based on the daily snow product from Moderate Resolution Imaging Spectroradiometer (MODIS A1), a cloud removing method was developed by considering the regional snow distribution characteristics with latitude and altitude dependence respectively. In the end, the daily cloud free products was compared with the same period of eight days MODIS standard product, revealing that the cloud free snow products are reasonable, while could provide higher temporal resolution, and more details over Center Asia and Xinjiang Province.

A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958-2015)

NASA Astrophysics Data System (ADS)

Noël, Brice; van de Berg, Willem Jan; Machguth, Horst; Lhermitte, Stef; Howat, Ian; Fettweis, Xavier; van den Broeke, Michiel R.

2016-10-01

This study presents a data set of daily, 1 km resolution Greenland ice sheet (GrIS) surface mass balance (SMB) covering the period 1958-2015. Applying corrections for elevation, bare ice albedo and accumulation bias, the high-resolution product is statistically downscaled from the native daily output of the polar regional climate model RACMO2.3 at 11 km. The data set includes all individual SMB components projected to a down-sampled version of the Greenland Ice Mapping Project (GIMP) digital elevation model and ice mask. The 1 km mask better resolves narrow ablation zones, valley glaciers, fjords and disconnected ice caps. Relative to the 11 km product, the more detailed representation of isolated glaciated areas leads to increased precipitation over the southeastern GrIS. In addition, the downscaled product shows a significant increase in runoff owing to better resolved low-lying marginal glaciated regions. The combined corrections for elevation and bare ice albedo markedly improve model agreement with a newly compiled data set of ablation measurements.

Remote sensing of desert dust aerosols over the Sahel : potential use for health impact studies

NASA Astrophysics Data System (ADS)

Deroubaix, A. D.; Martiny, N. M.; Chiapello, I. C.; Marticorena, B. M.

2012-04-01

Since the end of the 70's, remote sensing monitors the desert dust aerosols due to their absorption and scattering properties and allows to make long time series which are necessary for air quality or health impact studies. In the Sahel, a huge health problem is the Meningitis Meningococcal (MM) epidemics that occur during the dry season : the dust has been suspected to be crucial to understand their onsets and dynamics. The Aerosol absorption Index (AI) is a semi-quantitative index derived from TOMS and OMI observations in the UV available at a spatial resolution of 1° (1979-2005) and 0.25° (2005-today) respectively. The comparison of the OMI-AI and AERONET Aerosol Optical thickness (AOT) shows a good agreement at a daily time-step (correlation ~0.7). The comparison of the OMI-AI with the Particle Matter (PM) measurement of the Sahelian Dust Transect is lower (~0.4) at a daily time-step but it increases at a weekly time-step (~0.6). The OMI-AI reproduces the dust seasonal cycle over the Sahel and we conclude that the OMI-AI product at a 0.25° spatial resolution is suitable for health impact studies, especially at a weekly epidemiological time-step. Despite the AI is sensitive to the aerosol altitude, it provides a daily spatial information on dust. A preliminary investigation analysis of the link between weekly OMI AI and weekly WHO epidemiological data sets is presented in Mali and Niger, showing a good agreement between the AI and the onset of the MM epidemics with a constant lag (between 1 and 2 week). The next of this study is to analyse a deeper AI time series constituted by TOMS and OMI data sets. Based on the weekly ratios PM/AI at 2 stations of the Sahelian Dust Transect, a spatialized proxy for PM from the AI has been developed. The AI as a proxy for PM and other climate variables such as Temperature (T°), Relative Humidity (RH%) and the wind (intensity and direction) could then be used to analyze the link between those variables and the MM epidemics in the most concerned countries in Western Africa, which would be an important step towards a forecasting tool for the epidemics risks in Western Africa.

Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2.

NASA Astrophysics Data System (ADS)

Devarakonda, R.

2014-12-01

Daymet: Daily Surface Weather Data and Climatological Summaries provides gridded estimates of daily weather parameters for North America, including daily continuous surfaces of minimum and maximum temperature, precipitation occurrence and amount, humidity, shortwave radiation, snow water equivalent, and day length. The current data product (Version 2) covers the period January 1, 1980 to December 31, 2013 [1]. Data are available on a daily time step at a 1-km x 1-km spatial resolution in Lambert Conformal Conic projection with a spatial extent that covers the North America as meteorological station density allows. Daymet data can be downloaded from 1) the ORNL Distributed Active Archive Center (DAAC) search and order tools (http://daac.ornl.gov/cgi-bin/cart/add2cart.pl?add=1219) or directly from the DAAC FTP site (http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1219) and 2) the Single Pixel Tool (http://daymet.ornl.gov/singlepixel.html) and THREDDS (Thematic Real-time Environmental Data Services) Data Server (TDS) (http://daymet.ornl.gov/thredds_mosaics.html). The Single Pixel Data Extraction Tool [2] allows users to enter a single geographic point by latitude and longitude in decimal degrees. A routine is executed that translates the (lon, lat) coordinates into projected Daymet (x,y) coordinates. These coordinates are used to access the Daymet database of daily-interpolated surface weather variables. The Single Pixel Data Extraction Tool also provides the option to download multiple coordinates programmatically. The ORNL DAAC's TDS provides customized visualization and access to Daymet time series of North American mosaics. Users can subset and download Daymet data via a variety of community standards, including OPeNDAP, NetCDF Subset service, and Open Geospatial Consortium (OGC) Web Map/Coverage Service. References: [1] Thornton, P. E., Thornton, M. M., Mayer, B. W., Wilhelmi, N., Wei, Y., Devarakonda, R., & Cook, R. (2012). "Daymet: Daily surface weather on a 1 km grid for North America, 1980-2008". Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center for Biogeochemical Dynamics (DAAC), 1. [2] Devarakonda R., et al. 2012. Daymet: Single Pixel Data Extraction Tool. Available [http://daymet.ornl.go/singlepixel.html].

Progress towards daily "swath" solutions from GRACE

NASA Astrophysics Data System (ADS)

Save, H.; Bettadpur, S. V.; Sakumura, C.

2015-12-01

The GRACE mission has provided invaluable and the only data of its kind that measures the total water column in the Earth System over the past 13 years. The GRACE solutions available from the project have been monthly average solutions. There have been attempts by several groups to produce shorter time-window solutions with different techniques. There is also an experimental quick-look GRACE solution available from CSR that implements a sliding window approach while applying variable daily data weights. All of these GRACE solutions require special handling for data assimilation. This study explores the possibility of generating a true daily GRACE solution by computing a daily "swath" total water storage (TWS) estimate from GRACE using the Tikhonov regularization and high resolution monthly mascon estimation implemented at CSR. This paper discusses the techniques for computing such a solution and discusses the error and uncertainty characterization. We perform comparisons with official RL05 GRACE solutions and with alternate mascon solutions from CSR to understand the impact on the science results. We evaluate these solutions with emphasis on the temporal characteristics of the signal content and validate them against multiple models and in-situ data sets.

The use of EO Optical data for the Italian Supersites volcanoes monitoring

NASA Astrophysics Data System (ADS)

Silvestri, Malvina

2016-04-01

This work describes the INGV experience in the capability to import many different EO optical data into in house developed systems and to maintain a repository where the acquired data have been stored. These data are used for generating selected products which are functional to face the different volcanic activity phases. Examples on the processing of long time series based EO data of Mt Etna activity and Campi Flegrei observation by using remote sensing techniques and at different spatial resolution data (ASTER - 90mt, AVHRR -1km, MODIS-1km, MSG SEVIRI-3km) are also showed. Both volcanoes belong to Italian Supersites initiative of the geohazard scientific community. In the frame of the EC FP7 MED-SUV project (call FP7 ENV.2012.6.4-2), this work wants to describe the main activities concerning the generation of brightness temperature map from the satellite data acquired in real-time from INGV MEOS Multi-mission Antenna (for MODIS, Moderate Resolution Imaging Spectroradiometer and geostationary satellite data) and AVHRR-TERASCAN (for AVHRR, Advanced Very High Resolution Radiometer data). The advantage of direct download of EO data by means INGV antennas (with particular attention to AVHRR and MODIS) even though low spatial resolution offers the possibility of a systematic data processing having a daily updating of information for prompt response and hazard mitigation. At the same time it has been necessary the use of large archives to inventory and monitor dynamic and dangerous phenomena, like volcanic activity, globally.

New statistical downscaling for Canada

NASA Astrophysics Data System (ADS)

Murdock, T. Q.; Cannon, A. J.; Sobie, S.

2013-12-01

This poster will document the production of a set of statistically downscaled future climate projections for Canada based on the latest available RCM and GCM simulations - the North American Regional Climate Change Assessment Program (NARCCAP; Mearns et al. 2007) and the Coupled Model Intercomparison Project Phase 5 (CMIP5). The main stages of the project included (1) downscaling method evaluation, (2) scenarios selection, (3) production of statistically downscaled results, and (4) applications of results. We build upon a previous downscaling evaluation project (Bürger et al. 2012, Bürger et al. 2013) in which a quantile-based method (Bias Correction/Spatial Disaggregation - BCSD; Werner 2011) provided high skill compared with four other methods representing the majority of types of downscaling used in Canada. Additional quantile-based methods (Bias-Correction/Constructed Analogues; Maurer et al. 2010 and Bias-Correction/Climate Imprint ; Hunter and Meentemeyer 2005) were evaluated. A subset of 12 CMIP5 simulations was chosen based on an objective set of selection criteria. This included hemispheric skill assessment based on the CLIMDEX indices (Sillmann et al. 2013), historical criteria used previously at the Pacific Climate Impacts Consortium (Werner 2011), and refinement based on a modified clustering algorithm (Houle et al. 2012; Katsavounidis et al. 1994). Statistical downscaling was carried out on the NARCCAP ensemble and a subset of the CMIP5 ensemble. We produced downscaled scenarios over Canada at a daily time resolution and 300 arc second (~10 km) spatial resolution from historical runs for 1951-2005 and from RCP 2.6, 4.5, and 8.5 projections for 2006-2100. The ANUSPLIN gridded daily dataset (McKenney et al. 2011) was used as a target. It has national coverage, spans the historical period of interest 1951-2005, and has daily time resolution. It uses interpolation of station data based on thin-plate splines. This type of method has been shown to have superior skill in interpolating RCM data over North America (McGinnis et al. 2012). An early application of the new dataset was to provide projections of climate extremes for adaptation planning by the British Columbia Ministry of Transportation and Infrastructure. Recently, certain stretches of highway have experienced extreme precipitation events resulting in substantial damage to infrastructure. As part of the planning process to refurbish or replace components of these highways, information about the magnitude and frequency of future extreme events are needed to inform the infrastructure design. The increased resolution provided by downscaling improves the representation of topographic features, particularly valley temperature and precipitation effects. A range of extreme values, from simple daily maxima and minima to complex multi-day and threshold-based climate indices were computed and analyzed from the downscaled output. Selected results from this process and how the projections of precipitation extremes are being used in the context of highway infrastructure planning in British Columbia will be presented.

Fatigue Moderates the Relationship Between Perceived Stress and Suicidal Ideation: Evidence From Two High-Resolution Studies.

PubMed

Kleiman, Evan M; Turner, Brianna J; Chapman, Alexander L; Nock, Matthew K

2018-01-01

Theoretical models of self-harm suggest that high perceived stress and high fatigue (which might affect the ability to cope with stress) may interact to predict the short-term occurrence of suicidal ideation and nonsuicidal self-injury (NSSI). We tested 3 approaches to examining this interaction, each of which provided a different understanding of the specific nature of these associations: comparing each individual's daily stress/fatigue to the entire sample's overall average (i.e., grand-mean centering), comparing each individual's daily perceived stress/fatigue to his or her overall average (i.e., group- or participant-mean centering), and comparing each individual's average perceived stress/fatigue to the sample's overall average (i.e., centering participant means on overall grand mean). In 2 studies, adolescents (n = 30; 574 daily reports, M age = 17.3 years, range = 12-19; 87.6% female) and young adults (n = 60; 698 daily reports; M age = 23.25 years, range = 18-35; 85% female) completed daily measures of perceived stress, fatigue, suicidal ideation, and NSSI. In both samples, the interaction between high daily perceived stress and high daily fatigue predicted greater odds of daily suicidal ideation (but not NSSI). Only the model comparing each individual's daily stress/fatigue to the entire sample's overall average was consistently significant across the two studies. Participants were most likely to experience suicidal ideation on days when both perceived stress and fatigue were elevated relative to the average level experienced across people and time points. Studies should build upon these findings with more in-depth examination of the temporal nature of stability and change in these factors as they relate to sustained suicidal ideation.

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM2-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM2-MODIS_Edition2C)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM1-MODIS_Edition2B)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Aqua-FM3-MODIS_Edition2A)

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A. (Principal Investigator)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

Integrating expert- and algorithm-derived data to generate a hemispheric ice edge

NASA Astrophysics Data System (ADS)

Tsatsoulis, C.; Komp, E.

The Arctic ice edge is the area of the Arctic where sea ice concentration is less than 15%, and is considered navigable by most vessels. Experts at the National Ice Center generate a daily ice edge product that is available to the public. Data of preference is that of active, high resolution satellite sensors such as RADARSAT which yields all-weather images of 100m resolution, and a second source is OLS data with 550m resolution. Unfortunately, RADARSAT does not provide full, daily coverage of the Arctic and OLS can be obscured by clouds. The SSM/I sensor provides complete coverage of the Arctic at 25km resolution and is independent of cloud cover and solar illumination during the Arctic winter. SSM/I data is analyzed by the NASA Team algorithm to establish ice concentration. Our work integrates the ice edge created by experts using high resolution data with the ice edge generated out of the coarser SSM/I microwave data. The result is a product that combines human and algorithmic outputs, deals with gross differences in resolution of the underlying data sets, and results in a useful, operational product.

Analysis of 2-Week Data from Two Randomized, Controlled Trials Conducted in Subjects with Frequent Heartburn Treated with Esomeprazole 20 mg.

PubMed

Katz, Philip O; Le Moigne, Anne; Pollack, Charles

2017-05-01

These secondary analyses used data from 2 similarly designed studies in subjects experiencing frequent heartburn to evaluate the efficacy of esomeprazole 20 mg once daily for 2 weeks, which reflects the approved over-the-counter dosage and duration. Subjects without endoscopically identified erosive esophagitis who were experiencing heartburn for ≥6 months and ≥4 of 7 days prior to baseline (study 1, N = 368; study 2, N = 349) were randomly assigned to receive double-blind treatment with esomeprazole 40 or 20 mg (administered as esomeprazole magnesium trihydrate 44.5 and 22.3 mg, respectively) or placebo once daily for 4 weeks. Subjects recorded the severity of heartburn in a daily diary, and investigators assessed subjects at each study visit. Two-week assessments were the primary end points of interest in these analyses and included the percentage of subjects with complete heartburn resolution (no episodes during 7 consecutive days), time to sustained complete heartburn resolution (the first of 7 consecutive episode-free days), and heartburn relief (no episodes other than ≤1 mild episode during 7 consecutive days). At week 2, the percentages of subjects who experienced complete heartburn resolution were significantly greater with esomeprazole 40 mg (study 1, 26.1%; study 2, 35.3%) and 20 mg (study 1, 25.2%; study 2, 35.7%) compared with placebo (study 1, 9.0%; study 2, 3.4%) (all, P ≤ 0.001). Beginning on day 1, the percentages of subjects who experienced sustained heartburn resolution was significantly greater in the groups treated with esomeprazole 40 mg (study 1, 19%; study 2, 19%; P < 0.0001) and 20 mg (study 1, 10%; study 2, 15%; P < 0.05) compared with the group that received placebo (study 1, 2%; study 2, 1%). Additionally, at week 2, the percentages of subjects experiencing heartburn relief were significantly greater with esomeprazole 40 mg (study 1, 35.3%; study 2, 40.5%) and 20 mg (study 1, 34.5%; study 2, 46.4%) compared with placebo (study 1, 16.5%; study 2, 8.6%) (all, P ≤ 0.001). The results of this study demonstrate that once-daily treatment with esomeprazole 20 mg for 2 weeks effectively resolved subjects׳ heartburn compared with placebo, beginning on day 1. Studies precede FDA Act 801 clinical trial registration and results submission requirements. Copyright © 2017 Elsevier HS Journals, Inc. All rights reserved.

Real Time Agricultural Monitoring with the Planet SmallSat Constellation

NASA Astrophysics Data System (ADS)

Mascaro, J.

2017-12-01

Planet—an aerospace and data analytics company (www.planet.com)—now operates 190 earth observation satellites, collecting approximately 85% of the land-surface of the Earth every day in multispectral, 3.7m-resolution imagery. This frequency and spatial resolution provides for unique monitoring of global agriculture, especially billions of smallholder farms that feed much of the world. Through our Education and Research Program, anyone at a university is eligible to access a portion of Planet data to power their research at no cost. Here, we present innovative results from our research partners. Most critically, several users have undertaken the development of models for regularizing spectrally disparate data feeds from Planet, Sentinel and Landsat; these approaches have generated standardized, 3.7m-resolution, daily data feeds for NDVI, LAI and (in combination with eddy covariance data) crop water use. The key breakthrough is interoperability: ingesting multiple, disparate satellite information fields for the generation of actionable agricultural indicators. This foundational methodology, aided by computer vision, can provide near real-time updates on the yield, health and welfare of smallholder farms. Storms, drought and disease can be detected faster than ever before, enabling smart intervention and enhancing the effectiveness of insurance and disaster relief mechanisms.

MSE commissioning and other major diagnostic updates on KSTAR

NASA Astrophysics Data System (ADS)

Ko, Jinseok; Kstar Team

2015-11-01

The motional Stark effect (MSE) diagnostic based on the photoelastic-modulator (PEM) approach has been commissioned for the Korea Superconducting Tokamak Advanced Research (KSTAR). The 25-channel MSE system with the polarization-preserving front optics and precise tilt-tuning narrow bandpass filters provides the spatial resolution less than 1 cm in most of the plasma cross section and about 10 millisecond of time resolution. The polarization response curves with the daily Faraday rotation correction provides reliable pitch angle profiles for the KSTAR discharges with the MSE-optimized energy combination in the three-ion-source neutral beam injection. Some major diagnostic advances such as the poloidal charge exchange spectroscopy, the improved Thomson-scatting system, and the divertor infrared TV are reported as well. Work supported by the Ministry of Science, ICT and Future Planning, Korea.

Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

NASA Astrophysics Data System (ADS)

Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

2017-04-01

General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All approaches underline the technical difficulties of snow cover modelling during the monsoon season, in accordance with previous studies. The developed methods in combination with continuous in situ measurements provide a basis for further downscaling approaches.

Low, fixed dose defibrotide in management of hepatic veno-occlusive disease post stem cell transplantation.

PubMed

Bagal, Bhausaheb; Chandrasekharan, Arun; Chougle, Aliya; Khattry, Navin

2018-03-01

Hepatic veno-occlusive disease (VOD) is well recognized potentially serious regimen-related toxicity seen after stem cell transplantation. Severe VOD is associated with poor long-term outcomes with very high mortality. Besides supportive care, only defibrotide has been found to be effective in the management of VOD. The recommended dose of defibrotide is 25mg/kg/d but there has been no classical dose finding study done for this drug. A higher dose of defibrotide is associated with increased risk of bleeding and this drug is prohibitively expensive. We report our experience of using fixed low dose of defibrotide in patients with VOD. We retrospectively evaluated 511 patients who underwent stem cell transplant at our center from November 2007 and December 2015. All patients received ursodeoxycholic acid as VOD prophylaxis. Modified Seattle criterion was used for diagnosis and severity grading of VOD. Patients developing VOD were initially treated with furosemide and adequate analgesia. Defibrotide was started within 12 to 24 hours of diagnosis of VOD. All adult patients received defibrotide at a fixed dose of 200mg twice daily while two children were given dose of 100mg and 50mg twice daily. Nine (1.7%) of our patients developed VOD. Daily dose of defibrotide ranged from 5mg/kg/d to 20mg/kg/d till resolution of VOD. All patients had complete resolution of VOD. None of our patients required ventilator support or dialysis. No episodes of bleeding were observed. No dose response relationship was observed between defibrotide dose and time to resolution of VOD. Low fixed dose defibrotide initiated early seems to be effective and safe in treatment of VOD. This is relevant in a resource limited setting and warrants prospective evaluation. Copyright © 2017 King Faisal Specialist Hospital & Research Centre. Published by Elsevier B.V. All rights reserved.

Assessing the performance and reliability of PERSIANN-CDR satellite-based rainfall estimates over Spain: case study of rainfall Dry Spell Lengths (DSL)

NASA Astrophysics Data System (ADS)

Garcia Galiano, S. G.; Giraldo Osorio, J. D.; Nguyen, P.; Hsu, K. L.; Braithwaite, D.; Olmos, P.; Sorooshian, S.

2015-12-01

Studying Spain's long-term variability and changing trends in rainfall, due to its unique position in the Mediterranean basin (i.e., the latitudinal gradient from North to South and its orographic variation), can provide a valuable insight into how hydroclimatology of the region has changed. A recently released high resolution satellite-based global daily precipitation climate dataset PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network - Climate Data Record), provided the opportunity to conduct such study. It covers the period 01/01/1983 - to date, at 0.25° resolution. In areas without a dense network of rain-gauges, the PERSIANN-CDR dataset could be useful for identifying the reliability of regional climate models (RCMs), in order to build robust RCMs ensemble for reducing the uncertainties in the climate and hydrological projections. However, before using this data set for RCM evaluation, an assessment of performance of PERSIANN-CDR dataset against in-situ observations is necessary. The high-resolution gridded daily rain-gauge dataset, named Spain02, was employed in this study. The variable Dry Spell Lengths (DSL) considering 1 mm and 10 mm as thresholds of daily rainfall, and the time period 1988-2007 was defined for the study. A procedure for improving the consistency and homogeneity between the two datasets was applied. The assessment is based on distributional similarity and the well-known statistical tests (Smirnov-Kolmogorov of two samples and Chi-Square) are used as fitting criteria. The results demonstrate good fit of PERSIANN-CDR over whole Spain, for threshold 10 mm/day. However, for threshold 1 mm/day PERSIANN-CDR compares well with Spain02 dataset for areas with high values of rainfall (North of Spain); while in semiarid areas (South East of Spain) there is strong overestimation of short DSLs. Overall, PERSIANN-CDR demonstrate its robustness in the simulation of DSLs for the highest thresholds.

Estimation of daily Snow Cover Area combining MODIS and LANDSAT information by using cellular automata

NASA Astrophysics Data System (ADS)

Pardo-Iguzquiza, Eulogio; Juan Collados Lara, Antonio; Pulido-Velazquez, David

2016-04-01

The snow availability in Alpine catchments is essential for the economy of these areas. It plays an important role in tourist development but also in the management of the Water Resources Snow is an important water resource in many river basins with mountains in the catchment area. The determination of the snow water equivalent requires the estimation of the evolution of the snow pack (cover area, thickness and snow density) along the time. Although there are complex physical models of the dynamics of the snow pack, sometimes the data available are scarce and a stochastic model like the cellular automata (CA) can be of great practical interest. CA can be used to model the dynamics of growth and wane of the snow pack. The CA is calibrated with historical data. This requires the determination of transition rules that are capable of modeling the evolution of the spatial pattern of snow cover area. Furthermore, CA requires the definition of states and neighborhoods. We have included topographical variables and climatological variables in order to define the state of each pixel. The evolution of snow cover in a pixel depends on its state, the state of the neighboring pixels and the transition rules. The calibration of the CA is done using daily MODIS data, available for the period 24/02/2002 to present with a spatial resolution of 500 m, and the LANDSAT information available with a sixteen-day periodicity from 1984 to the present and with spatial resolution of 30 m. The methodology has been applied to estimation of the snow cover area of Sierra Nevada mountain range in the Southern of Spain to obtain snow cover area daily information with 500 m spatial resolution for the period 1980-2014. Acknowledgments: This research has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank NASA DAAC and LANDSAT project for the data provided for this study.

Validation and Temporal Analysis of Lai and Fapar Products Derived from Medium Resolution Sensor

NASA Astrophysics Data System (ADS)

Claverie, M.; Vermote, E. F.; Baret, F.; Weiss, M.; Hagolle, O.; Demarez, V.

2012-12-01

Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) have been defined as Essential Climate Variables. Many Earth surface monitoring applications are based on global estimation combined with a relatively high frequency. The medium spatial resolution sensors (MRS), such as SPOT-VGT, MODIS or MERIS, have been widely used to provide land surface products (mainly LAI and FAPAR) to the scientific community. These products require quality assessment and consistency. However, due to consistency of the ground measurements spatial sampling, the medium resolution is not appropriate for direct validation with in situ measurements sampling. It is thus more adequate to use high spatial resolution sensors which can integrate the spatial variability. The recent availability of combined high spatial (8 m) and temporal resolutions (daily) Formosat-2 data allows to evaluate the accuracy and the temporal consistency of medium resolution sensors products. In this study, we proposed to validate MRS products over a cropland area and to analyze their spatial and temporal consistency. As a matter of fact, this study belongs to the Stage 2 of the validation, as defined by the Land Product Validation sub-group of the Earth Observation Satellites. Reference maps, derived from the aggregation of Formosat-2 data (acquired during the 2006-2010 period over croplands in southwest of France), were compared with (i) two existing global biophysical variables products (GEOV1/VGT and MODIS-15 coll. 5), and (ii) a new product (MODdaily) derived from the inversion of PROSAIL radiative transfer model (EMMAH, INRA Avignon) applied on MODIS BRDF-corrected daily reflectance. Their uncertainty was calculated with 105 LAI and FAPAR reference maps, which uncertainties (22 % for LAI and 12% for FAPAR) were evaluated with in situ measurements performed over maize, sunflower and soybean. Inter-comparison of coarse resolution (0.05°) products showed that LAI and FAPAR have consistent phenology (Figure). The GEOLAND-2 showed the smoothest time series due to a 30-day composite, while MODdaily noise was satisfactory (<12%). The RMSE of LAI calculated for the period 2006-2010 were 0.46 for GEOV1/VGT, 0.19 for MODIS-15 and 0.16 for MODdaily. A significant overestimation (bias=0.43) of the LAI peak were observed for GEOV1/VGT products, while MOD-15 showed a small underestimation (bias=-0.14) of highest LAI. Finally, over a larger area (a quarter of France) covered by cropland, grassland and forest, the products displayed a good spatial consistency.; LAI 2006-2010 time-series of a coarse resolution pixel of cropland (extent in upper-left corner). Products are compared to Formosat-2 reference maps.

Coastal and Inland Water Applications of High Resolution Optical Satellite Data from Landsat-8 and Sentinel-2

NASA Astrophysics Data System (ADS)

Vanhellemont, Q.

2016-02-01

Since the launch of Landsat-8 (L8) in 2013, a joint NASA/USGS programme, new applications of high resolution imagery for coastal and inland waters have become apparent. The optical imaging instrument on L8, the Operational Land Imager (OLI), is much improved compared to its predecessors on L5 and L7, especially with regards to SNR and digitization, and is therefore well suited for retrieving water reflectances and derived parameters such as turbidity and suspended sediment concentration. In June 2015, the European Space Agency (ESA) successfully launched a similar instrument, the MultiSpectral Imager (MSI), on board of Sentinel-2A (S2A). Imagery from both L8 and S2A are free of charge and publicly available (S2A starting at the end of 2015). Atmospheric correction schemes and processing software is under development in the EC-FP7 HIGHROC project. The spatial resolution of these instruments (10-60 m) is a great improvement over typical moderate resolution ocean colour sensors such as MODIS and MERIS (0.25 - 1 km). At higher resolution, many more lakes, rivers, ports and estuaries are spatially resolved, and can thus now be studied using satellite data, unlocking potential for mandatory monitoring e.g. under European Directives such as the Marine Strategy Framework Directive and the Water Framework Directive. We present new applications of these high resolution data, such as monitoring of offshore constructions, wind farms, sediment transport, dredging and dumping, shipping and fishing activities. The spatial variability at sub moderate resolution (0.25 - 1 km) scales can be assessed, as well as the impact of sub grid scale variability (including ships and platforms used for validation) on the moderate pixel retrieval. While the daily revisit time of the moderate resolution sensors is vastly superior to those of the high resolution satellites, at the equator respectively 16 and 10 days for L8 and S2A, the low revisit times can be partially mitigated by combining data streams. Time-series of L8 and S2A imagery are presented to show the power of combining the two satellite missions. With the launch of Sentinel-2B (expected mid-2016), the time-series will be extended with another high resolution sensor. S2B will be on the same orbit as S2A, spaced 180 degrees apart, bringing the S2A+B combined revisit time down to 5 days.

High Resolution Time Series of Plankton Communities: From Early Warning of Harmful Blooms to Sentinels of Climate Change

NASA Astrophysics Data System (ADS)

Sosik, H. M.; Campbell, L.; Olson, R. J.

2016-02-01

The combination of ocean observatory infrastructure and automated submersible flow cytometry provides an unprecedented capability for sustained high resolution time series of plankton, including taxa that are harmful or early indicators of ecosystem response to environmental change. On-going time series produced with the FlowCytobot series of instruments document important ways this challenge is already being met for phytoplankton and microzooplankton. FlowCytobot and Imaging FlowCytobot use a combination of laser-based scattering and fluorescence measurements and video imaging of individual particles to enumerate and characterize cells ranging from picocyanobacteria to large chaining-forming diatoms. Over a decade of observations at the Martha's Vineyard Coastal Observatory (MVCO), a cabled facility on the New England Shelf, have been compiled from repeated instrument deployments, typically 6 months or longer in duration. These multi-year high resolution (hourly to daily) time series are providing new insights into dynamics of community structure such as blooms, seasonality, and multi-year trends linked to regional climate-related variables. Similar observations in Texas coastal waters at the Texas Observatory for Algal Succession Time series (TOAST) have repeatedly provided early warning of harmful algal bloom events that threaten human and ecosystem health. As coastal ocean observing systems mature and expand, the continued integration of these type of detailed observations of the plankton will provide unparalleled information about variability and patterns of change at the base of the marine food webs, with direct implications for informed ecosystem-based management.

MODIS-derived EVI, NDVI and WDRVI time series to estimate phenological metrics in French deciduous forests

NASA Astrophysics Data System (ADS)

Testa, S.; Soudani, K.; Boschetti, L.; Borgogno Mondino, E.

2018-02-01

Monitoring forest phenology allows us to study the effects of climate change on vegetated land surfaces. Daily and composite time series (TS) of several vegetation indices (VIs) from MODerate resolution Imaging Spectroradiometer (MODIS) data have been widely used in scientific works for phenological studies since the beginning of the MODIS mission. The objective of this work was to use MODIS data to find the best VI/TS combination to estimate start-of-season (SOS) and end-of-season (EOS) dates across 50 temperate deciduous forests. Our research used as inputs 2001-2012 daily reflectance from MOD09GQ/MOD09GA products and 16-day composite VIs from the MOD13Q1 dataset. The 50 pixels centered on the 50 forest plots were extracted from the above-mentioned MODIS imagery; we then generated 5 different types of TS (1 daily from MOD09 and 4 composite from MOD13Q1) and used all of them to implement 6 VIs, obtaining 30 VI/TS combinations. SOS and EOS estimates were determined for each pixel/year and each VI/TS combination. SOS/EOS estimations were then validated against ground phenological observations. Results showed that, in our test areas, composite TS, if actual acquisition date is considered, performed mostly better than daily TS. EVI, WDRVI0.20 and NDVI were more suitable to SOS estimation, while WDRVI0.05 and EVI were more convenient in estimating early and advanced EOS, respectively.

Evaluating synoptic systems in the CMIP5 climate models over the Australian region

NASA Astrophysics Data System (ADS)

Gibson, Peter B.; Uotila, Petteri; Perkins-Kirkpatrick, Sarah E.; Alexander, Lisa V.; Pitman, Andrew J.

2016-10-01

Climate models are our principal tool for generating the projections used to inform climate change policy. Our confidence in projections depends, in part, on how realistically they simulate present day climate and associated variability over a range of time scales. Traditionally, climate models are less commonly assessed at time scales relevant to daily weather systems. Here we explore the utility of a self-organizing maps (SOMs) procedure for evaluating the frequency, persistence and transitions of daily synoptic systems in the Australian region simulated by state-of-the-art global climate models. In terms of skill in simulating the climatological frequency of synoptic systems, large spread was observed between models. A positive association between all metrics was found, implying that relative skill in simulating the persistence and transitions of systems is related to skill in simulating the climatological frequency. Considering all models and metrics collectively, model performance was found to be related to model horizontal resolution but unrelated to vertical resolution or representation of the stratosphere. In terms of the SOM procedure, the timespan over which evaluation was performed had some influence on model performance skill measures, as did the number of circulation types examined. These findings have implications for selecting models most useful for future projections over the Australian region, particularly for projections related to synoptic scale processes and phenomena. More broadly, this study has demonstrated the utility of the SOMs procedure in providing a process-based evaluation of climate models.

Merging Satellite Optical Sensors and Radar Altimetry for Daily River Discharge Estimation

NASA Astrophysics Data System (ADS)

Tarpanelli, A.; Santi, E. S.; Tourian, M. J.; Filippucci, P.; Amarnath, G.; Brocca, L.; Benveniste, J.

2017-12-01

River discharge is a fundamental physical variable of the hydrological cycle and notwithstanding its importance the monitoring of the flow in many parts of the Earth is still an open issue. Satellite sensors have great potential in offering new ways to monitor river discharge, because they guarantees regular, uniform and global measurements for long period thanks to the large number of satellites launched during the last twenty-five years. The multi-mission approach has been becoming a useful tool to integrate measurements and intensify the number of samples in space and time. In this study, we investigated the possibility to merge data from optical, i.e. Near InfraRed bands (from MODIS, MERIS, Landsat, and OLCI) and altimetry data (from Topex-Poseidon, Envisat/RA-2, Jason-2, SARAL/AltiKa and CryoSat-2) for estimating daily river discharge in Nigeria and Italy. The merging procedure is carried out by using artificial neural networks. Regarding the optical sensors, results are more affected by the temporal resolution than the spatial resolution. Landsat fails in the estimation of extreme events missing most of the peak values because of the long revisit time (14-16 days). Better performances are obtained with the Near InfraRed bands from MODIS and MERIS that give similar results in river discharge estimation. Finally, the multi-mission approach involving also radar altimetry data is found to be the most reliable tool to estimate river discharge in medium to large rivers.

TES/Aura L3 Atmospheric Temperatures Daily V5 (TL3ATD)

Atmospheric Science Data Center

2018-05-08

... Platform:  TES Aura L1B Nadir/Limb Spatial Coverage:  (-180, 180)(-90, 90) Spatial Resolution:  0.5 x 5 km nadir 2.3 x 23 km limb Temporal Coverage:  07/15/2004 - Present Temporal Resolution:  ...

Time correlations between low and high energy gamma rays from discrete sources

NASA Technical Reports Server (NTRS)

Ellsworth, R. W.

1995-01-01

Activities covered the following areas: (1) continuing analysis of the Cygnus Experiment data on the shadowing of cosmic rays by the moon and sun, which led to a direct confirmation of the angular resolution of the CYGNUS EAS array; and (2) development of analysis methods for the daily search overlapping with EGRET targets. To date, no steady emission of ultrahigh energy (UHE) gamma rays from any source has been detected by the Cygnus Experiment, but some evidence for sporadic emission had been found. Upper limits on steady fluxes from 49 sources in the northern hemisphere have been published. In addition, a daily search of 51 possible sources over the interval April 1986 to June 1992 found no evidence for emission. From these source lists, four candidates were selected for comparison with EGRET data.

Use of global positioning system measurements to determine geocentric coordinates and variations in Earth orientation

NASA Technical Reports Server (NTRS)

Malla, R. P.; Wu, S.-C.; Lichten, S. M.

1993-01-01

Geocentric tracking station coordinates and short-period Earth-orientation variations can be measured with Global Positioning System (GPS) measurements. Unless calibrated, geocentric coordinate errors and changes in Earth orientation can lead to significant deep-space tracking errors. Ground-based GPS estimates of daily and subdaily changes in Earth orientation presently show centimeter-level precision. Comparison between GPS-estimated Earth-rotation variations, which are the differences between Universal Time 1 and Universal Coordinated Time (UT1-UTC), and those calculated from ocean tide models suggests that observed subdaily variations in Earth rotation are dominated by oceanic tidal effects. Preliminary GPS estimates for the geocenter location (from a 3-week experiment) agree with independent satellite laser-ranging estimates to better than 10 cm. Covariance analysis predicts that temporal resolution of GPS estimates for Earth orientation and geocenter improves significantly when data collected from low Earth-orbiting satellites as well as from ground sites are combined. The low Earth GPS tracking data enhance the accuracy and resolution for measuring high-frequency global geodynamical signals over time scales of less than 1 day.

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

NASA Technical Reports Server (NTRS)

Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping; Stackhouse, Paul W., Jr.

2013-01-01

A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

Using Dynamically Downscaled Climate Model Outputs to Inform Projections of Extreme Precipitation Events

NASA Technical Reports Server (NTRS)

Wobus, Cameron; Reynolds, Lara; Jones, Russell; Horton, Radley; Smith, Joel; Fries, J. Stephen; Tryby, Michael; Spero, Tanya; Nolte, Chris

2015-01-01

Many of the storms that generate damaging floods are caused by locally intense, sub-daily precipitation, yet the spatial and temporal resolution of the most widely available climate model outputs are both too coarse to simulate these events. Thus there is often a disconnect between the nature of the events that cause damaging floods and the models used to project how climate change might influence their magnitude. This could be a particular problem when developing scenarios to inform future storm water management options under future climate scenarios. In this study we sought to close this gap, using sub-daily outputs from the Weather Research and Forecasting model (WRF) from each of the nine climate regions in the United States. Specifically, we asked 1) whether WRF outputs projected consistent patterns of change for sub-daily and daily precipitation extremes; and 2) whether this dynamically downscaled model projected different magnitudes of change for 3-hourly vs 24-hourly extreme events. We extracted annual maximum values for 3-hour through 24-hour precipitation totals from an 11-year time series of hindcast (1995-2005) and mid-century (2045-2055) climate, and calculated the direction and magnitude of change for 3-hour and 24-hour extreme events over this timeframe. The model results project that the magnitude of both 3-hour and 24-hour events will increase over most regions of the United States, but there was no clear or consistent difference in the relative magnitudes of change for sub-daily vs daily events.

A comparison of methods to estimate future sub-daily design rainfall

NASA Astrophysics Data System (ADS)

Li, J.; Johnson, F.; Evans, J.; Sharma, A.

2017-12-01

Warmer temperatures are expected to increase extreme short-duration rainfall due to the increased moisture-holding capacity of the atmosphere. While attention has been paid to the impacts of climate change on future design rainfalls at daily or longer time scales, the potential changes in short duration design rainfalls have been often overlooked due to the limited availability of sub-daily projections and observations. This study uses a high-resolution regional climate model (RCM) to predict the changes in sub-daily design rainfalls for the Greater Sydney region in Australia. Sixteen methods for predicting changes to sub-daily future extremes are assessed based on different options for bias correction, disaggregation and frequency analysis. A Monte Carlo cross-validation procedure is employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It is found that bias correction significantly improves the accuracy of the design rainfall estimated for the current climate. For 1 h events, bias correcting the hourly annual maximum rainfall simulated by the RCM produces design rainfall closest to observations, whereas for multi-hour events, disaggregating the daily rainfall total is recommended. This suggests that the RCM fails to simulate the observed multi-duration rainfall persistence, which is a common issue for most climate models. Despite the significant differences in the estimated design rainfalls between different methods, all methods lead to an increase in design rainfalls across the majority of the study region.

Remote sensing of mesospheric winds with the High-Resolution Doppler Imager

NASA Technical Reports Server (NTRS)

Hays, Paul B.; Abreu, V. J.; Burrage, M. D.; Gell, D. A.; Grassi, H. J.; Marshall, A. R.; Morton, Y. T.; Ortland, D. A.; Skinner, W. R.; Wu, D. L.

1992-01-01

Observations of the winds in the upper atmosphere obtained with the High-Resolution Doppler Imager (HRDI) on the Upper Atmosphere Research Satellite (UARS) are discussed. This instrument is a very stable high-resolution triple-etalon Fabry-Perot interferometer, which is used to observe the slight Doppler shifts of absorption and emission lines in the O2 Atmospheric bands induced by atmospheric motions. Preliminary observations indicate that the winds in the mesosphere and lower thermosphere are a mixture of migrating and non-migrating tides, and planetary-scale waves. The mean meridional winds are dominated by the 1,1 diurnal tide which is easily extracted from the daily zonal means of the satellite observations. The daily mean zonal winds are a mixture of the diurnal tide and a zonal flow which is consistent with theoretical expectations.

The iPot Project: improved potato monitoring in Belgium using remote sensing and crop growth modelling

NASA Astrophysics Data System (ADS)

Piccard, Isabelle; Nackaerts, Kris; Gobin, Anne; Goffart, Jean-Pierre; Planchon, Viviane; Curnel, Yannick; Tychon, Bernard; Wellens, Joost; Cools, Romain; Cattoor, Nele

2015-04-01

Belgian potato processors, traders and packers are increasingly working with potato contracts. The close follow up of contracted parcels on the land as well as from above is becoming an important tool to improve the quantity and quality of the potato crop and reduce risks in order to plan the storage, packaging or processing and as such to strengthen the competitiveness of the Belgian potato chain in a global market. At the same time, precision agriculture continues to gain importance and progress. Farmers are obligated to invest in new technologies. Between mid-May and the end of June 2014 potato fields in Gembloux were monitored from emergence till canopy closure. UAV images (RGB) and digital (hemispherical) photographs were taken at ten-daily intervals. Crop emergence maps show the time (date) and degree of crop emergence and crop closure (in terms of % cover). For three UAV flights during the growing season RGB images at 3 cm resolution were processed using a K-means clustering algorithm to classify the crop according to its greenness. Based on the greenness %cover and daily cover growth were derived for 5x5m pixels and 25x25m pixels. The latter resolution allowed for comparison with high resolution satellite imagery. Vegetation indices such as %Cover and LAI were calculated with the Cyclopes algorithm (INRA-EMMAH) from high resolution satellite images (DMC/Deimos, 22m pixel size). DMC based cover maps showed similar patterns as compared with the UAV-based cover maps, and allows for further applications of the data in crop management. Today the use of geo-information by the (private) agricultural sector in Belgium is rather limited, notwithstanding the great benefits this type of information may offer, as recognized by the sector. The iPot project, financed by the Belgian Science Policy Office (BELSPO), aims to provide the Belgian potato sector, represented by Belgapom, with near real time information on field condition (weather-soil) and crop development and with early yield estimates, derived from a combination of satellite images and crop growth models. An intuitive web based geo-information platform is being developed to allow both the Belgian potato industry and the potato research centres to access, analyse and combine the data with their own field observations in close collaboration with the farmers, for improved decision-making.

Hydropeaking in Nordic rivers - combined analysis from effects of changing climate conditions and energy demands to river regimes

NASA Astrophysics Data System (ADS)

Ashraf, Faisal Bin; Marttila, Hannu; Torabi Haghighi, Ali; Alfredsen, Knut; Riml, Joakim; Kløve, Bjørn

2017-04-01

Increasing national and international demands for more flexible management of the energy resources with more non-storable renewables being used in adapting to the ongoing climate change will influence hydropower operations. Damming and regulation practices of river systems causes homogenization of long term river dynamics but also higher temporal sub-daily flow variations i.e. hydropeaking. In Nordic countries, many major rivers and lakes are regulated for hydropower purposes, which have caused considerable changes in river biotic, hydrologic and morphologic structures. Due to rapidly changing energy markets in the Nordic countries (deregulation of the power market and adding of renewable but intermittent sources of energy like, wind, solar, etc.) sub-daily flow conditions are under change within regulated river systems due to the increased demand on hydropower for providing balancing power. However, holistic analysis from changes in energy markets and its effect on sub-daily river regimes is lacking. This study analyzes the effects of hydropeaking on river regime in Finland, Sweden and Norway using long term high resolution data (15 minutes to hourly time interval) from 72 pristine and 136 regulated rivers with large spatial coverage across Fennoscandia. Since the sub-daily discharge variation is masked through the monthly or daily analyzes, in order to quantify these changes high resolution data is needed. In our study we will document, characterize and classify the impacts of sub-daily flow variation due to regulation and climatic variation on various river systems in Fennoscandia. Further, with increasing social demands for ecosystem services in regulated rivers, it is important to evaluate the new demand and update hydropower operation plan accordingly. We will analyse ecological response relationships along gradients of hydrological alteration for the biological communities, processes of river ecosystems and climate boundaries together with considering the new energy demands and consumptions in the Nordic energy market. For assessing sub-daily flow data various already available indices will be used which measure the magnitude of hydropeaking and temporal rate of discharge changes. For the impact quantification, the hydropeaking pressure will be calculated and set for each of the impact class. Also work will be done to formulate some new indices which will specifically quantify sub-daily change in the boreal rivers. We select representative case-studies, future scenarios and develop optimization methods to reduce impacts on aquatic ecosystems and maximizing the economic benefits from hydropower generation for stakeholders.

Predictors of heartburn resolution and erosive esophagitis in patients with GERD.

PubMed

Orlando, Roy C; Monyak, John T; Silberg, Debra G

2009-09-01

The primary objective was to assess gastroesophageal reflux disease (GERD) symptom resolution rates with esomeprazole by erosive esophagitis (EE) status, and the secondary objective was to evaluate potential predictors of the presence of EE and heartburn resolution. Patients with GERD who have EE have higher reported symptom resolution rates than those with nonerosive reflux disease (NERD) when treated with proton pump inhibitors (PPIs). This open-label multicenter study included adults with GERD symptoms. Patients were stratified by EE status after endoscopy and received once-daily esomeprazole 40 mg for 4 weeks. Questionnaires determined symptom response rates, and baseline predictors of EE or heartburn resolution were evaluated. Potential predictors, including years with GERD, history of EE, and time to relief with antacids, were examined. Heartburn resolution rates at 4 weeks were higher for patients with EE than NERD (69% [124/179] vs. 48% [85/177]; p < 0.0001). Multivariate models had moderate predictive ability for EE (c-index, 0.76) and poor predictive ability (c-index, 0.57) for heartburn resolution. However, faster heartburn relief with antacid use, particularly within 15 min, was predictive of EE and heartburn resolution. Patients with EE have higher heartburn resolution rates than patients with NERD after treatment, although recall bias may be possible. Fast relief with antacid use is predictive of EE and heartburn resolution with a PPI and suggests that a history of antacid relief may provide corroborative evidence to empiric PPI therapy in determining whether patients with heartburn have acid reflux disease. ClinicalTrials.Gov IDENTIFIER: NCT00242736.

Prediction of global solar irradiance based on time series analysis: Application to solar thermal power plants energy production planning

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

Martin, Luis; Marchante, Ruth; Cony, Marco

2010-10-15

Due to strong increase of solar power generation, the predictions of incoming solar energy are acquiring more importance. Photovoltaic and solar thermal are the main sources of electricity generation from solar energy. In the case of solar thermal energy plants with storage energy system, its management and operation need reliable predictions of solar irradiance with the same temporal resolution as the temporal capacity of the back-up system. These plants can work like a conventional power plant and compete in the energy stock market avoiding intermittence in electricity production. This work presents a comparisons of statistical models based on time seriesmore » applied to predict half daily values of global solar irradiance with a temporal horizon of 3 days. Half daily values consist of accumulated hourly global solar irradiance from solar raise to solar noon and from noon until dawn for each day. The dataset of ground solar radiation used belongs to stations of Spanish National Weather Service (AEMet). The models tested are autoregressive, neural networks and fuzzy logic models. Due to the fact that half daily solar irradiance time series is non-stationary, it has been necessary to transform it to two new stationary variables (clearness index and lost component) which are used as input of the predictive models. Improvement in terms of RMSD of the models essayed is compared against the model based on persistence. The validation process shows that all models essayed improve persistence. The best approach to forecast half daily values of solar irradiance is neural network models with lost component as input, except Lerida station where models based on clearness index have less uncertainty because this magnitude has a linear behaviour and it is easier to simulate by models. (author)« less

Extracting Hydrologic Understanding from the Unique Space-time Sampling of the Surface Water and Ocean Topography (SWOT) Mission

NASA Astrophysics Data System (ADS)

Nickles, C.; Zhao, Y.; Beighley, E.; Durand, M. T.; David, C. H.; Lee, H.

2017-12-01

The Surface Water and Ocean Topography (SWOT) satellite mission is jointly developed by NASA, the French space agency (CNES), with participation from the Canadian and UK space agencies to serve both the hydrology and oceanography communities. The SWOT mission will sample global surface water extents and elevations (lakes/reservoirs, rivers, estuaries, oceans, sea and land ice) at a finer spatial resolution than is currently possible enabling hydrologic discovery, model advancements and new applications that are not currently possible or likely even conceivable. Although the mission will provide global cover, analysis and interpolation of the data generated from the irregular space/time sampling represents a significant challenge. In this study, we explore the applicability of the unique space/time sampling for understanding river discharge dynamics throughout the Ohio River Basin. River network topology, SWOT sampling (i.e., orbit and identified SWOT river reaches) and spatial interpolation concepts are used to quantify the fraction of effective sampling of river reaches each day of the three-year mission. Streamflow statistics for SWOT generated river discharge time series are compared to continuous daily river discharge series. Relationships are presented to transform SWOT generated streamflow statistics to equivalent continuous daily discharge time series statistics intended to support hydrologic applications using low-flow and annual flow duration statistics.

Property Analysis of the Real-Time Uncalibrated Phase Delay Product Generated by Regional Reference Stations and Its Influence on Precise Point Positioning Ambiguity Resolution

PubMed Central

Zhang, Yong; Wang, Qing; Jiang, Xinyuan

2017-01-01

The real-time estimation of the wide-lane and narrow-lane Uncalibrated Phase Delay (UPD) of satellites is realized by real-time data received from regional reference station networks; The properties of the real-time UPD product and its influence on real-time precise point positioning ambiguity resolution (RTPPP-AR) are experimentally analyzed according to real-time data obtained from the regional Continuously Operating Reference Stations (CORS) network located in Tianjin, Shanghai, Hong Kong, etc. The results show that the real-time wide-lane and narrow-lane UPD products differ significantly from each other in time-domain characteristics; the wide-lane UPDs have daily stability, with a change rate of less than 0.1 cycle/day, while the narrow-lane UPDs have short-term stability, with significant change in one day. The UPD products generated by different regional networks have obvious spatial characteristics, thus significantly influencing RTPPP-AR: the adoption of real-time UPD products employing the sparse stations in the regional network for estimation is favorable for improving the regional RTPPP-AR up to 99%; the real-time UPD products of different regional networks slightly influence PPP-AR positioning accuracy. After ambiguities are successfully fixed, the real-time dynamic RTPPP-AR positioning accuracy is better than 3 cm in the plane and 8 cm in the upward direction. PMID:28534844

Property Analysis of the Real-Time Uncalibrated Phase Delay Product Generated by Regional Reference Stations and Its Influence on Precise Point Positioning Ambiguity Resolution.

PubMed

Zhang, Yong; Wang, Qing; Jiang, Xinyuan

2017-05-19

The real-time estimation of the wide-lane and narrow-lane Uncalibrated Phase Delay (UPD) of satellites is realized by real-time data received from regional reference station networks; The properties of the real-time UPD product and its influence on real-time precise point positioning ambiguity resolution (RTPPP-AR) are experimentally analyzed according to real-time data obtained from the regional Continuously Operating Reference Stations (CORS) network located in Tianjin, Shanghai, Hong Kong, etc. The results show that the real-time wide-lane and narrow-lane UPD products differ significantly from each other in time-domain characteristics; the wide-lane UPDs have daily stability, with a change rate of less than 0.1 cycle/day, while the narrow-lane UPDs have short-term stability, with significant change in one day. The UPD products generated by different regional networks have obvious spatial characteristics, thus significantly influencing RTPPP-AR: the adoption of real-time UPD products employing the sparse stations in the regional network for estimation is favorable for improving the regional RTPPP-AR up to 99%; the real-time UPD products of different regional networks slightly influence PPP-AR positioning accuracy. After ambiguities are successfully fixed, the real-time dynamic RTPPP-AR positioning accuracy is better than 3 cm in the plane and 8 cm in the upward direction.

Capacity Building with CHIRPS Amidst a Station-Recording Crisis

NASA Astrophysics Data System (ADS)

Peterson, P.

2016-12-01

Station data are essential for improving the accuracy of satellite-derived rainfall products. However we face a severe reporting crisis as the number of available stations observations has declined precipitously. For example there were 2400 monthly stations available in Africa (excluding South Africa) in the 1980's, while at present there are about 500 stations (Figure 1). In this talk we describe how partnerships with regional and national collaborators can improve our collective ability to monitor food production and inform decision making. A high quality, long-term, high-resolution precipitation dataset is key for supporting agricultural drought monitoring, food security and early warning. Here we present the Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) v2.0, developed by scientists at the University of California, Santa Barbara and the U.S. Geological Survey Earth Resources Observation and Science Center under the direction of Famine Early Warning Systems Network (FEWS NET). This quasi-global precipitation product is available at daily to seasonal time scales with a spatial resolution of 0.05° and a 1981 to near real-time period of record. The Climate Hazards Group (CHG) has developed an extensive database of in situ daily, pentadal, and monthly precipitation totals with over a billion daily observations worldwide. Under support from the USAID FEWS NET, CHG/USGS has developed a two way strategy for incorporating contributed station data while providing web-based visualization tools to partners in developing nations. For example, we are currently working with partners in Mexico (Conagua), Southern Africa (SASSCAL), Colombia (IDEAM), Somalia (SWALIM) and Ethiopia (NMA). These institutions provide in situ observations which enhance the CHIRPS. The CHIRPS is then placed in a web accessible geospatial database. Partners in these countries can then access and display this information using web based mapping tools. This provides a win-win collaboration, leading to improved globally accessible precipitation estimates and improved climate services in developing nations.

Generating daily high spatial land surface temperatures by combining ASTER and MODIS land surface temperature products for environmental process monitoring.

PubMed

Wu, Mingquan; Li, Hua; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-08-01

There is a shortage of daily high spatial land surface temperature (LST) data for use in high spatial and temporal resolution environmental process monitoring. To address this shortage, this work used the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), and the Spatial and Temporal Data Fusion Approach (STDFA) to estimate high spatial and temporal resolution LST by combining Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) LST and Moderate Resolution Imaging Spectroradiometer (MODIS) LST products. The actual ASTER LST products were used to evaluate the precision of the combined LST images using the correlation analysis method. This method was tested and validated in study areas located in Gansu Province, China. The results show that all the models can generate daily synthetic LST image with a high correlation coefficient (r) of 0.92 between the synthetic image and the actual ASTER LST observations. The ESTARFM has the best performance, followed by the STDFA and the STARFM. Those models had better performance in desert areas than in cropland. The STDFA had better noise immunity than the other two models.

Level 4 Global and European Chl-a Daily Analyses for End Users and Data Assimilation in the Frame of the Copernicus-Marine Environment Monitoring Service

NASA Astrophysics Data System (ADS)

Saulquin, Bertrand; Gohin, Francis; Garnesson, Philippe; Demaria, Julien; Mangin, Antoine; Fanton d'Andon, Odile

2016-08-01

The level-4 daily chl-a products are a combination of a water typed merge of chl-a estimates and an optimal interpolation based on the kriging method with regional anisotropic models [1, 2]. The Level 4 products basically pro- vide a global continuous (cloud free) estimation of the surface chl-a concentration at 4 km resolution over the world and 1 km resolution over the Europe. The level-4 products gather MODIS, MERIS, SeaWiFS, VIIRS and OLCI daily observations from 1998 to now.The Level 4 product avoids end users to consider typical lack of data as observed during cloudy conditions and the historical multiplicity of available algorithms such as involved by case 1 (oligotrophic) and case 2 (turbid) water issues in ocean colour. [3, 4].A total product uncertainty, i.e. a combination of the interpolation and the estimation error, is provided for each daily product. The L4 products are freely distributed in the frame of the Copernicus - Marine environment monitoring service.

Hypertension and exposure to noise near airports: the HYENA study.

PubMed

Jarup, Lars; Babisch, Wolfgang; Houthuijs, Danny; Pershagen, Göran; Katsouyanni, Klea; Cadum, Ennio; Dudley, Marie-Louise; Savigny, Pauline; Seiffert, Ingeburg; Swart, Wim; Breugelmans, Oscar; Bluhm, Gösta; Selander, Jenny; Haralabidis, Alexandros; Dimakopoulou, Konstantina; Sourtzi, Panayota; Velonakis, Manolis; Vigna-Taglianti, Federica

2008-03-01

An increasing number of people are exposed to aircraft and road traffic noise. Hypertension is an important risk factor for cardiovascular disease, and even a small contribution in risk from environmental factors may have a major impact on public health. The HYENA (Hypertension and Exposure to Noise near Airports) study aimed to assess the relations between noise from aircraft or road traffic near airports and the risk of hypertension. We measured blood pressure and collected data on health, socioeconomic, and lifestyle factors, including diet and physical activity, via questionnaire at home visits for 4,861 persons 45-70 years of age, who had lived at least 5 years near any of six major European airports. We assessed noise exposure using detailed models with a resolution of 1 dB (5 dB for United Kingdom road traffic noise), and a spatial resolution of 250 x 250 m for aircraft and 10 x 10 m for road traffic noise. We found significant exposure-response relationships between night-time aircraft as well as average daily road traffic noise exposure and risk of hypertension after adjustment for major confounders. For night-time aircraft noise, a 10-dB increase in exposure was associated with an odds ratio (OR) of 1.14 [95% confidence interval (CI), 1.01-1.29]. The exposure-response relationships were similar for road traffic noise and stronger for men with an OR of 1.54 (95% CI, 0.99-2.40) in the highest exposure category (> 65 dB; p(trend) = 0.008). Our results indicate excess risks of hypertension related to long-term noise exposure, primarily for night-time aircraft noise and daily average road traffic noise.

Intercomparison of Streamflow Simulations between WRF-Hydro and Hydrology Laboratory-Research Distributed Hydrologic Model Frameworks

NASA Astrophysics Data System (ADS)

KIM, J.; Smith, M. B.; Koren, V.; Salas, F.; Cui, Z.; Johnson, D.

2017-12-01

The National Oceanic and Atmospheric Administration (NOAA)-National Weather Service (NWS) developed the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) framework as an initial step towards spatially distributed modeling at River Forecast Centers (RFCs). Recently, the NOAA/NWS worked with the National Center for Atmospheric Research (NCAR) to implement the National Water Model (NWM) for nationally-consistent water resources prediction. The NWM is based on the WRF-Hydro framework and is run at a 1km spatial resolution and 1-hour time step over the contiguous United States (CONUS) and contributing areas in Canada and Mexico. In this study, we compare streamflow simulations from HL-RDHM and WRF-Hydro to observations from 279 USGS stations. For streamflow simulations, HL-RDHM is run on 4km grids with the temporal resolution of 1 hour for a 5-year period (Water Years 2008-2012), using a priori parameters provided by NOAA-NWS. The WRF-Hydro streamflow simulations for the same time period are extracted from NCAR's 23 retrospective run of the NWM (version 1.0) over CONUS based on 1km grids. We choose 279 USGS stations which are relatively less affected by dams or reservoirs, in the domains of six different RFCs. We use the daily average values of simulations and observations for the convenience of comparison. The main purpose of this research is to evaluate how HL-RDHM and WRF-Hydro perform at USGS gauge stations. We compare daily time-series of observations and both simulations, and calculate the error values using a variety of error functions. Using these plots and error values, we evaluate the performances of HL-RDHM and WRF-Hydro models. Our results show a mix of model performance across geographic regions.

High resolution fossil fuel combustion CO2 emission fluxes for the United States.

PubMed

Gurney, Kevin R; Mendoza, Daniel L; Zhou, Yuyu; Fischer, Marc L; Miller, Chris C; Geethakumar, Sarath; de la Rue du Can, Stephane

2009-07-15

Quantification of fossil fuel CO2 emissions at fine space and time resolution is emerging as a critical need in carbon cycle and climate change research. As atmospheric CO2 measurements expand with the advent of a dedicated remote sensing platform and denser in situ measurements, the ability to close the carbon budget at spatial scales of approximately 100 km2 and daily time scales requires fossil fuel CO2 inventories at commensurate resolution. Additionally, the growing interest in U.S. climate change policy measures are best served by emissions that are tied to the driving processes in space and time. Here we introduce a high resolution data product (the "Vulcan" inventory: www.purdue.edu/eas/carbon/vulcan/) that has quantified fossil fuel CO2 emissions for the contiguous U.S. at spatial scales less than 100 km2 and temporal scales as small as hours. This data product completed for the year 2002, includes detail on combustion technology and 48 fuel types through all sectors of the U.S. economy. The Vulcan inventory is built from the decades of local/regional air pollution monitoring and complements these data with census, traffic, and digital road data sets. The Vulcan inventory shows excellent agreement with national-level Department of Energy inventories, despite the different approach taken by the DOE to quantify U.S. fossil fuel CO2 emissions. Comparison to the global 1degree x 1 degree fossil fuel CO2 inventory, used widely by the carbon cycle and climate change community prior to the construction of the Vulcan inventory, highlights the space/time biases inherent in the population-based approach.

Increasing Advisor Effectiveness by Understanding Conflict and Conflict Resolution

ERIC Educational Resources Information Center

McClellan, Jeffrey

2005-01-01

On a daily basis, advisors encounter various types of interpersonal and intrapersonal conflict. Through this article, the reader will better understand conflict, its positive and negative impacts and the approaches of the actors experiencing conflict, and the means whereby conflicts arise, escalate, and come to resolution in advising situations.…

Recovering NOAA 1,2,3,4 Infrared and visible high resolution data, 1974-1977.

NASA Astrophysics Data System (ADS)

Campbell, G. G.

2017-12-01

The NOAA satellites 1 to 4 (1974-1977) had high resolution visible and infrared detectors which made daily observations of the Earth from sun-synchronous orbits so both day and night observations were made. Here we describe the recovery of this data at 25 km resolution by digitizing the half tome prints from publication NOAA #54 which provides daily composites of the scan observations. The infrared images can be calibrated using the 280 km resolution digital archive still maintained by NOAA from this Scanning Radiometer data. This is an extension of our recovery of the ESSA 1,3,5,7 and 9 data from 1966 to 1974. This much higher resolution product provides much richer detail about the Earth in the 1970's. As a particular example we will discuss the large polynya in the sea ice in the Wedell sea first noted in the Electrically Scanned Microwave Radiometer observations from 1974 to 1976. The visible data verify the presence of the large open water region in the middle of the pack ice in the winters of 1974, 5 and 6. In addition we will discuss the cloud fields and motions over this region apparent from the recovered high resolution observations. One can also see hints of this phenomenon occurring in 2016 and 2017.

Scale effects on the evapotranspiration estimation over a water-controlled Mediterranean ecosystem and its influence on hydrological modelling

NASA Astrophysics Data System (ADS)

Carpintero, Elisabet; González-Dugo, María P.; José Polo, María; Hain, Christopher; Nieto, Héctor; Gao, Feng; Andreu, Ana; Kustas, William; Anderson, Martha

2017-04-01

The integration of currently available satellite data into surface energy balance models can provide estimates of evapotranspiration (ET) with spatial and temporal resolutions determined by sensor characteristics. The use of data fusion techniques may increase the temporal resolution of these estimates using multiple satellites, providing a more frequent ET monitoring for hydrological purposes. The objective of this work is to analyze the effects of pixel resolution on the estimation of evapotranspiration using different remote sensing platforms, and to provide continuous monitoring of ET over a water-controlled ecosystem, the Holm oak savanna woodland known as dehesa. It is an agroforestry system with a complex canopy structure characterized by widely-spaced oak trees combined with crops, pasture and shrubs. The study was carried out during two years, 2013 and 2014, combining ET estimates at different spatial and temporal resolutions and applying data fusion techniques for a frequent monitoring of water use at fine spatial resolution. A global and daily ET product at 5 km resolution, developed with the ALEXI model using MODIS day-night temperature difference (Anderson et al., 2015a) was used as a starting point. The associated flux disaggregation scheme, DisALEXI (Norman et al., 2003), was later applied to constrain higher resolution ET from both MODIS and Landsat 7/8 images. The Climate Forecast System Reanalysis (CFSR) provided the meteorological data. Finally, a data fusion technique, the STARFM model (Gao et al., 2006), was applied to fuse MODIS and Landsat ET maps in order to obtain daily ET at 30 m resolution. These estimates were validated and analyzed at two different scales: at local scale over a dehesa experimental site and at watershed scale with a predominant Mediterranean oak savanna landscape, both located in Southern Spain. Local ET estimates from the modeling system were validated with measurements provided by an eddy covariance tower installed in the dehesa (38 ° 12 'N, 4 ° 17' W, 736 m a.s.l.). The results supported the ability of ALEXI/DisALEXI model to accurately estimate turbulent and radiative fluxes over this complex landscape, both at 1 Km and at 30 m spatial resolution. The application of the STARFM model gave significant improvement in capturing the spatio-temporal heterogeneity of ET over the different seasons, compared with traditional interpolation methods using MODIS and Landsat ET data. At basin scale, the physically-based distributed hydrological model WiMMed has been applied to evaluate ET estimates. This model focuses on the spatial interpolation of the meteorological variables and the physical modelling of the daily water balance at the cell and watershed scale, using daily streamflow rates measured at the watershed outlet for final comparison.

A dynamic urban air pollution population exposure assessment study using model and population density data derived by mobile phone traffic

NASA Astrophysics Data System (ADS)

Gariazzo, Claudio; Pelliccioni, Armando; Bolignano, Andrea

2016-04-01

A dynamic city-wide air pollution exposure assessment study has been carried out for the urban population of Rome, Italy, by using time resolved population distribution maps, derived by mobile phone traffic data, and modelled air pollutants (NO2, O3 and PM2.5) concentrations obtained by an integrated air dispersion modelling system. More than a million of persons were tracked during two months (March and April 2015) for their position within the city and its surroundings areas, with a time resolution of 15 min and mapped over an irregular grid system with a minimum resolution of 0.26 × 0.34 Km2. In addition, demographics information (as gender and age ranges) were available in a separated dataset not connected with the total population one. Such BigData were matched in time and space with air pollution model results and then used to produce hourly and daily resolved cumulative population exposures during the studied period. A significant mobility of population was identified with higher population densities in downtown areas during daytime increasing of up to 1000 people/Km2 with respect to nigh-time one, likely produced by commuters, tourists and working age population. Strong variability (up to ±50% for NO2) of population exposures were detected as an effect of both mobility and time/spatial changing in pollutants concentrations. A comparison with the correspondent stationary approach based on National Census data, allows detecting the inability of latter in estimating the actual variability of population exposure. Significant underestimations of the amount of population exposed to daily PM2.5 WHO guideline was identified for the Census approach. Very small differences (up to a few μg/m3) on exposure were detected for gender and age ranges population classes.

An auxiliary method to reduce potential adverse impacts of projected land developments: subwatershed prioritization.

PubMed

Kalin, Latif; Hantush, Mohamed M

2009-02-01

An index based method is developed that ranks the subwatersheds of a watershed based on their relative impacts on watershed response to anticipated land developments, and then applied to an urbanizing watershed in Eastern Pennsylvania. Simulations with a semi-distributed hydrologic model show that computed low- and high-flow frequencies at the main outlet increase significantly with the projected landscape changes in the watershed. The developed index is utilized to prioritize areas in the urbanizing watershed based on their contributions to alterations in the magnitude of selected flow characteristics at two spatial resolutions. The low-flow measure, 7Q10, rankings are shown to mimic the spatial trend of groundwater recharge rates, whereas average annual maximum daily flow, QAMAX, and average monthly median of daily flows, QMMED, rankings are influenced by both recharge and proximity to watershed outlet. Results indicate that, especially with the higher resolution, areas having quicker responses are not necessarily the more critical areas for high-flow scenarios. Subwatershed rankings are shown to vary slightly with the location of water quality/quantity criteria enforcement. It is also found that rankings of subwatersheds upstream from the site of interest, which could be the main outlet or any interior point in the watershed, may be influenced by the time scale of the hydrologic processes.

Global Operational Remotely Sensed Evapotranspiration System for Water Resources Management: Case Study for the State of New Mexico

NASA Astrophysics Data System (ADS)

Halverson, G. H.; Fisher, J.; Magnuson, M.; John, L.

2017-12-01

An operational system to produce and disseminate remotely sensed evapotranspiration using the PT-JPL model and support its analysis and use in water resources decision making is being integrated into the New Mexico state government. A partnership between the NASA Western Water Applications Office (WWAO), the Jet Propulsion Laboratory (JPL), and the New Mexico Office of the State Engineer (NMOSE) has enabled collaboration with a variety of state agencies to inform decision making processes for agriculture, rangeland, and forest management. This system improves drought understanding and mobilization, litigation support, and economic, municipal, and ground-water planning through interactive mapping of daily rates of evapotranspiration at 1 km spatial resolution with near real-time latency. This is facilitated by daily remote sensing acquisitions of land-surface temperature and near-surface air temperature and humidity from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite as well as the short-term composites of Normalized Difference Vegetation Index (NDVI) and albedo provided by MODIS. Incorporating evapotranspiration data into agricultural water management better characterizes imbalances between water requirements and supplies. Monitoring evapotranspiration over rangeland areas improves remediation and prevention of aridification. Monitoring forest evapotranspiration improves wildlife management and response to wildfire risk. Continued implementation of this decision support system should enhance water and food security.

Snowmelt runoff in the Green River basin derived from MODIS snow extent

NASA Astrophysics Data System (ADS)

Barton, J. S.; Hall, D. K.

2011-12-01

The Green River represents a vital water supply for southwestern Wyoming, northern Colorado, eastern Utah, and the Lower Colorado River Compact states (Arizona, Nevada, and California). Rapid development in the southwestern United States combined with the recent drought has greatly stressed the water supply of the Colorado River system, and concurrently increased the interest in long-term variations in stream flow. Modeling of snowmelt runoff represents a means to predict flows and reservoir storage, which is useful for water resource planning. An investigation is made into the accuracy of the Snowmelt Runoff Model of Martinec and Rango, driven by Moderate Resolution Imaging Spectroradiometer (MODIS) snow maps for predicting stream flow within the Green River basin. While the moderate resolution of the MODIS snow maps limits the spatial detail that can be captured, the daily coverage is an important advantage of the MODIS imagery. The daily MODIS snow extent is measured using the most recent clear observation for each 500-meter pixel. Auxiliary data used include temperature and precipitation time series from the Snow Telemetry (SNOTEL) and Remote Automated Weather Station (RAWS) networks as well as from National Weather Service records. Also from the SNOTEL network, snow-water equivalence data are obtained to calibrate the conversion between snow extent and runoff potential.

Evolution of precipitation extremes in two large ensembles of climate simulations

NASA Astrophysics Data System (ADS)

Martel, Jean-Luc; Mailhot, Alain; Talbot, Guillaume; Brissette, François; Ludwig, Ralf; Frigon, Anne; Leduc, Martin; Turcotte, Richard

2017-04-01

Recent studies project significant changes in the future distribution of precipitation extremes due to global warming. It is likely that extreme precipitation intensity will increase in a future climate and that extreme events will be more frequent. In this work, annual maxima daily precipitation series from the Canadian Earth System Model (CanESM2) 50-member large ensemble (spatial resolution of 2.8°x2.8°) and the Community Earth System Model (CESM1) 40-member large ensemble (spatial resolution of 1°x1°) are used to investigate extreme precipitation over the historical (1980-2010) and future (2070-2100) periods. The use of these ensembles results in respectively 1 500 (30 years x 50 members) and 1200 (30 years x 40 members) simulated years over both the historical and future periods. These large datasets allow the computation of empirical daily extreme precipitation quantiles for large return periods. Using the CanESM2 and CESM1 large ensembles, extreme daily precipitation with return periods ranging from 2 to 100 years are computed in historical and future periods to assess the impact of climate change. Results indicate that daily precipitation extremes generally increase in the future over most land grid points and that these increases will also impact the 100-year extreme daily precipitation. Considering that many public infrastructures have lifespans exceeding 75 years, the increase in extremes has important implications on service levels of water infrastructures and public safety. Estimated increases in precipitation associated to very extreme precipitation events (e.g. 100 years) will drastically change the likelihood of flooding and their extent in future climate. These results, although interesting, need to be extended to sub-daily durations, relevant for urban flooding protection and urban infrastructure design (e.g. sewer networks, culverts). Models and simulations at finer spatial and temporal resolution are therefore needed.

Spatial downscaling and correction of precipitation and temperature time series to high resolution hydrological response units in the Canadian Rocky Mountains

NASA Astrophysics Data System (ADS)

Kienzle, Stefan

2015-04-01

Precipitation is the central driving force of most hydrological processes, and is also the most variable element of the hydrological cycle. As the precipitation to runoff ratio is non-linear, errors in precipitation estimations are amplified in streamflow simulations. Therefore, the accurate estimate of areal precipitation is essential for watershed models and relevant impacts studies. A procedure is presented to demonstrate the spatial distribution of daily precipitation and temperature estimates across the Rocky Mountains within the framework of the ACRU agro-hydrological modelling system (ACRU). ACRU (Schulze, 1995) is a physical-conceptual, semi-distributed hydrological modelling system designed to be responsive to changes in land use and climate. The model has been updated to include specific high-mountain and cold climate routines and is applied to simulate impacts of land cover and climate change on the hydrological behaviour of numerous Rocky Mountain watersheds in Alberta, Canada. Both air temperature and precipitation time series need to be downscaled to hydrological response units (HRUs), as they are the spatial modelling units for the model. The estimation of accurate daily air temperatures is critical for the separation of rain and snow. The precipitation estimation procedure integrates a spatially distributed daily precipitation database for the period 1950 to 2010 at a scale of 10 by 10 km with a 1971-2000 climate normal database available at 2 by 2 km (PRISM). Resulting daily precipitation time series are further downscaled to the spatial resolution of hydrological response units, defined by 100 m elevation bands, land cover, and solar radiation, which have an average size of about 15 km2. As snow measurements are known to have a potential under-catch of up to 40%, further adjustment of snowfall may need to be increased using a procedure by Richter (1995). Finally, precipitation input to HRUs with slopes steeper than 10% need to be further corrected, because the true, sloped area, has a larger area than the planimetric area derived from a GIS. The omission of correcting for sloped areas would result in incorrect calculations of interception volumes, soil moisture storages, groundwater recharge rates, actual evapotranspiration volumes, and runoff coefficients. Daily minimum and maximum air temperatures are estimated for each HRU by downscaling the 10km time series to the HRUs by (a) applying monthly mean lapse rates, estimated either from surrounding climate stations or from the PRISM climate normal dataset in combination with a digital elevation model, (b) adjusting further for aspect of the HRU based on monthly mean incoming solar radiation, and (c) adjusting for canopy cover using the monthly mean leaf area indices. Precipitation estimates can be verified using independent snow water equivalent measurements derived from snow pillow or snow course observations, while temperature estimates are verified against either independent temperature measurements from climate stations, or from fire observation towers.

Global surface mass time variations by using a two-step inversion for cumulating daily satellite gravity information

NASA Astrophysics Data System (ADS)

Ramillien, Guillaume; Frappart, Frappart; Seoane, Lucia

2015-04-01

We propose a new method to produce time series of global maps of surface mass variations by progressive integration of daily geopotential variations measured by orbiting satellites. In the case of the GRACE mission (2002 - 2012), these geopotential variations can be determined from very accurate inter-satellite K-Band Range Rate (KBRR) measurements of 5-second daily orbits. In particular, the along-track gravity contribution of hydrology is extracted by removing de-aliasing models for static field, atmosphere, oceans mass variations (including periodical tides), as well as polar movements. Our determination of surface mass sources consists of two successive dependent Kalman filter stages. The first one consists of reducing the satellite-based potential anomalies by adjusting the longest spatial wavelengths (i.e., low-degree spherical harmonics less than 5-6). In the second stage, the residual potential anomalies from the previous stage are used to recover surface mass density changes - in terms of Equivalent-Water Height (EWH) - over a global network of juxtaposed triangular elements. These surface tiles of ~40,000 km x km are imposed to be identical and homogeneously-distributed over the terrestrial sphere, however they can be adapted to the local geometry of the surface mass. Our global approach was tested by inverting simulated hydrology-related geopotential data, and successfully applied to estimate time-varying surface mass densities from real GRACE-based residuals. This strategy of combined Kalman filter-type inversions can also be useful for exploring the possibility of reaching better time and space resolutions for hydrology, that would be hopefully brought by future low altitude geodetic missions.

Highly Efficient Conservative Treatment of Pectus Carinatum in Compliant Patients.

PubMed

Loff, Steffan; Sauter, Hartwig; Wirth, Thomas; Otte, Ralf

2015-10-01

Pectus carinatum is a thoracic deformity, which causes severe psychological problems for affected patients but almost no physical limitations. Invasive procedures are difficult to justify for this reason. We present a conservative therapy which leads to complete resolution in most cases when performed properly. Between January 2008 and December 2012, 69 patients from 4 to 17 years with pectus carinatum were treated with a custom-fitted brace. Patients were stratified in children, adolescents, and adults. Mean therapy time was 7 months. Mean time of daily brace wearing was 12 to 15 hours. The results were evaluated by pictures taken before and after the therapy and from a patient interview. Standardized lateral views revealed a mean correction angle of 10 degrees in the children's group and 5 degrees in the adolescent group. In the adolescent group, 82% of patients judged the result as "excellent" or "good." In this large group with 56 patients, those who reported the result "unchanged" had a mean daily brace wearing time of 8.73 hours, those who judged the result as "good" 14.53 hours, and those who judged the result as "excellent" 18.36 hours. Our results show that pectus carinatum is efficiently treated with a customized brace therapy within 7 to 12 months. Best correction can be achieved in children and young adolescents. Daily brace-wearing time should be above 14 hours, ideally 24 hours. Duration of the treatment should be around 1 year. Treatment results correlate directly with the cooperation of the patients. Georg Thieme Verlag KG Stuttgart · New York.

Disaggregation of remotely sensed soil moisture under all sky condition using machine learning approach in Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, S.; Kim, H.; Choi, M.; Kim, K.

2016-12-01

Estimating spatiotemporal variation of soil moisture is crucial to hydrological applications such as flood, drought, and near real-time climate forecasting. Recent advances in space-based passive microwave measurements allow the frequent monitoring of the surface soil moisture at a global scale and downscaling approaches have been applied to improve the spatial resolution of passive microwave products available at local scale applications. However, most downscaling methods using optical and thermal dataset, are valid only in cloud-free conditions; thus renewed downscaling method under all sky condition is necessary for the establishment of spatiotemporal continuity of datasets at fine resolution. In present study Support Vector Machine (SVM) technique was utilized to downscale a satellite-based soil moisture retrievals. The 0.1 and 0.25-degree resolution of daily Land Parameter Retrieval Model (LPRM) L3 soil moisture datasets from Advanced Microwave Scanning Radiometer 2 (AMSR2) were disaggregated over Northeast Asia in 2015. Optically derived estimates of surface temperature (LST), normalized difference vegetation index (NDVI), and its cloud products were obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) for the purpose of downscaling soil moisture in finer resolution under all sky condition. Furthermore, a comparison analysis between in situ and downscaled soil moisture products was also conducted for quantitatively assessing its accuracy. Results showed that downscaled soil moisture under all sky condition not only preserves the quality of AMSR2 LPRM soil moisture at 1km resolution, but also attains higher spatial data coverage. From this research we expect that time continuous monitoring of soil moisture at fine scale regardless of weather conditions would be available.

The Effect of Laparoscopic Sleeve Gastrectomy with Concomitant Hiatal Hernia Repair on Gastroesophageal Reflux Disease in the Morbidly Obese.

PubMed

Samakar, Kamran; McKenzie, Travis J; Tavakkoli, Ali; Vernon, Ashley H; Robinson, Malcolm K; Shikora, Scott A

2016-01-01

The effect of laparoscopic sleeve gastrectomy (LSG) on gastroesophageal reflux disease (GERD) is controversial. Although concomitant hiatal hernia repair (HHR) at the time of LSG is common and advocated by many, there are few data on the outcomes of GERD symptoms in these patients. The aim of this study was to evaluate the effect of concomitant HHR on GERD symptoms in morbidly obese patients undergoing LSG. A single institution, multi-surgeon, prospectively maintained database was examined to identify patients who underwent LSG and concomitant HHR from December 2010 to October 2013. Patient characteristics, operative details, and postoperative outcomes were analyzed. Standardized patient questionnaires administered both pre- and postoperatively were utilized. Primary endpoints included subjective reflux symptoms and the need for antisecretory therapy. Weight loss was considered a secondary endpoint. Fifty-eight patients were identified meeting inclusion criteria (LSG + HHR), with a mean follow-up of 97.5 weeks (range 44-172 weeks). The mean age of the cohort was 49.5 ± 11.2 years, with 74.1 % being female. Mean preoperative BMI was 44.2 ± 6.6 kg/m(2). Preoperative upper gastrointestinal contrast series was performed in all patients and demonstrated a hiatal hernia in 34.5 % of patients and reflux in 15.5 % of patients. Preoperatively, 44.8 % (n = 26) of patients reported subjective symptoms of reflux and/or required daily antisecretory therapy [Corrected]. After LSG + HHR, 34.6 % of symptomatic patients had resolution of their symptoms off therapy while the rest remained symptomatic and required daily antisecretory therapy; 84.4 % of patients that were asymptomatic preoperatively remained asymptomatic after surgery. New onset reflux symptoms requiring daily antisecretory therapy was seen in 15.6 % of patients who were previously asymptomatic. Post surgical weight loss did not correlate with the presence or resolution of reflux symptoms. Based on our data, LSG with concomitant HHR improved GERD symptoms or the need for daily antisecretory therapy only in a third of symptomatic patients. Furthermore, 15.6 % of asymptomatic patients developed de novo GERD symptoms despite a HHR. In patients with a documented hiatal hernia, HHR does not lead to GERD resolution or prevention after LSG, indicating the need for appropriate patient counseling and further study.

Passive Microwave Remote Sensing of Colorado Watersheds Using Calibrated, Enhanced-Resolution Brightness Temperatures (CETB) from AMSR-E and SSM/I for Estimation of Snowmelt Timing

NASA Astrophysics Data System (ADS)

Johnson, M.; Ramage, J. M.; Troy, T. J.; Brodzik, M. J.

2017-12-01

Understanding the timing of snowmelt is critical for water resources management in snow-dominated watersheds. Passive microwave remote sensing has been used to estimate melt-refreeze events through brightness temperature satellite observations taken with sensors like the Special Sensor Microwave Imager (SSM/I) and the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). Previous studies were limited to lower resolution ( 25 km) datasets, making it difficult to quantify the snowpack in heterogeneous, high-relief areas. This study investigates the use of newly available passive microwave calibrated, enhanced-resolution brightness temperatures (CETB) produced at the National Snow and Ice Data Center to estimate melt timing at much higher spatial resolution ( 3-6 km). CETB datasets generated from SSM/I and AMSR-E records will be used to examine three mountainous basins in Colorado. The CETB datasets retain twice-daily (day/night) observations of brightness temperatures. Therefore, we employ the diurnal amplitude variation (DAV) method to detect melt onset and melt occurrences to determine if algorithms developed for legacy data are valid with the improved CETB dataset. We compare melt variability with nearby stream discharge records to determine an optimum melt onset algorithm using the newly reprocessed data. This study investigates the effectiveness of the CETB product for several locations in Colorado (North Park, Rabbit Ears, Fraser) that were the sites of previous ground/airborne surveys during the NASA Cold Land Processes Field Experiment (CLPX 2002-2003). In summary, this work lays the foundation for the utilization of higher resolution reprocessed CETB data for snow evolution more broadly in a range of environments. Consequently, the new processing methods and improved spatial resolution will enable hydrologists to better analyze trends in snow-dominated mountainous watersheds for more effective water resources management.

Climate Change Signals in the EURO-CORDEX Simulations

NASA Astrophysics Data System (ADS)

Jacob, Daniela; Preuschmann, Swantje

2014-05-01

A new high-resolution regional climate change ensemble has been established for Europe within the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX) initiative. Within this presentation, the first results on climate change signals based on simulations with a horizontal resolution of 12.5 km for the new emission scenarios RCP4.5 and RCP8.5 will be presented. The new EURO-CORDEX ensemble results have been compared to the SRES A1B simulation results achieved within the ENSEMBLES project. The presentation is based on the results of the Paper JACOB et al. (2013). We concentrated on the statistical analysis of robustness and significance of the climate change signals for mean annual and seasonal temperature, total annual and seasonal precipitation, heavy precipitation, heat waves and dry spells, by using daily data for three time periods: 1971-2000, 2021-2050 and 2071-2100. The analysis of impact indices shows that for RCP8.5, there is a substantially larger change projected for temperature-based indices than for RCP4.5. The difference is less pronounced for precipitation-based indices. Two effects of the increased resolution can be regarded as an added value of regional climate simulations. Regional climate model simulations provide higher daily precipitation intensities, which are completely missing in the global climate model simulations, and they provide a significantly different climate change of daily precipitation intensities resulting in a smoother shift from weak to moderate and high intensities. The analysis of projected changes in the 95th percentile of the mean length of dry spells shows similar patterns for all scenarios. The climate projections from the new ensemble indicate a reduced northwards shift of Mediterranean drying evolution and slightly stronger mean precipitation increases over most of Europe. Within the high-resolution simulations in the EURO-CORDEX changes of the pattern for heavy precipitation events are clearly visible. (Jacob2013) Jacob, D.; Petersen, J.; Eggert, B.; Alias, A.; Christensen, O. B.; Bouwer, L.; Braun, A.; Colette, A.; Déqué, M.; Georgievski, G.; Georgopoulou, E.; Gobiet, A.; Menut, L.; Nikulin, G.; Haensler, A.; Hempelmann, N.; Jones, C.; Keuler, K.; Kovats, S.; Kröner, N.; Kotlarski, S.; Kriegsmann, A.; Martin, E.; Meijgaard, E.; Moseley, C.; Pfeifer, S.; Preuschmann, S.; Radermacher, C.; Radtke, K.; Rechid, D.; Rounsevell, M.; Samuelsson, P.; Somot, S.; Soussana, J.-F.; Teichmann, C.; Valentini, R.; Vautard, R.; Weber, B. & Yiou, P.( 2013): EURO-CORDEX: new high-resolution climate change projections for European impact research Regional Environmental Change, Springer Berlin Heidelberg, 2013, 1-16.

Generating High-Temporal and Spatial Resolution TIR Image Data

NASA Astrophysics Data System (ADS)

Herrero-Huerta, M.; Lagüela, S.; Alfieri, S. M.; Menenti, M.

2017-09-01

Remote sensing imagery to monitor global biophysical dynamics requires the availability of thermal infrared data at high temporal and spatial resolution because of the rapid development of crops during the growing season and the fragmentation of most agricultural landscapes. Conversely, no single sensor meets these combined requirements. Data fusion approaches offer an alternative to exploit observations from multiple sensors, providing data sets with better properties. A novel spatio-temporal data fusion model based on constrained algorithms denoted as multisensor multiresolution technique (MMT) was developed and applied to generate TIR synthetic image data at both temporal and spatial high resolution. Firstly, an adaptive radiance model is applied based on spectral unmixing analysis of . TIR radiance data at TOA (top of atmosphere) collected by MODIS daily 1-km and Landsat - TIRS 16-day sampled at 30-m resolution are used to generate synthetic daily radiance images at TOA at 30-m spatial resolution. The next step consists of unmixing the 30 m (now lower resolution) images using the information about their pixel land-cover composition from co-registered images at higher spatial resolution. In our case study, TIR synthesized data were unmixed to the Sentinel 2 MSI with 10 m resolution. The constrained unmixing preserves all the available radiometric information of the 30 m images and involves the optimization of the number of land-cover classes and the size of the moving window for spatial unmixing. Results are still being evaluated, with particular attention for the quality of the data streams required to apply our approach.

Probing AGN Structure on Microarcsecond Scales: The Space Telescope and Optical Reverberation Mapping Program

NASA Astrophysics Data System (ADS)

De Rosa, Gisella

2015-08-01

The unknown dynamics of the broad line region (BLR) gas represents a serious gap in our understanding of active galactic nuclei (AGNs) and, consequently, of the black-hole/host-galaxy co-evolution. By using time resolution as a substitute for spatial resolution, reverberation mapping (RM) is the only technique that allows us to infer both the geometry and the kinematics of the BLR gas, shading light on the BLR role on accretion/feedback processes. In 2014, the AGN STORM team used HST/COS for a RM program for which we obtained 170 UV spectra of the Seyfert 1 galaxy NGC 5548 at a near daily cadence. These data and contemporaneous observations with Swift and ground-based telescopes make this the most intensive RM program ever undertaken. I will report first results of this unique RM experiment.

Using MODIS Terra 250 m Imagery to Map Concentrations of Total Suspended Matter in Coastal Waters

NASA Technical Reports Server (NTRS)

Miller, Richard L.; McKee, Brent A.

2004-01-01

High concentrations of suspended particulate matter in coastal waters directly effect or govern numerous water column and benthic processes. The concentration of suspended sediments derived from bottom sediment resuspension or discharge of sediment-laden rivers is highly variable over a wide range of time and space scales. Although there has been considerable effort to use remotely sensed images to provide synoptic maps of suspended particulate matter, there are limited routine applications of this technology due in-part to the low spatial resolution, long revisit period, or cost of most remotely sensed data. In contrast, near daily coverage of medium-resolution data is available from the MODIS Terra instrument without charge from several data distribution gateways. Equally important, several display and processing programs are available that operate on low cost computers.

Characterization of precipitation features over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2013-12-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme precipitation events is also provided. Furthermore, this work is part of a broader effort to evaluate long-term multi-sensor QPEs in the perspective of developing Climate Data Records (CDRs) for precipitation.

A machine learning method to estimate PM2.5 concentrations across China with remote sensing, meteorological and land use information.

PubMed

Chen, Gongbo; Li, Shanshan; Knibbs, Luke D; Hamm, N A S; Cao, Wei; Li, Tiantian; Guo, Jianping; Ren, Hongyan; Abramson, Michael J; Guo, Yuming

2018-09-15

Machine learning algorithms have very high predictive ability. However, no study has used machine learning to estimate historical concentrations of PM 2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) at daily time scale in China at a national level. To estimate daily concentrations of PM 2.5 across China during 2005-2016. Daily ground-level PM 2.5 data were obtained from 1479 stations across China during 2014-2016. Data on aerosol optical depth (AOD), meteorological conditions and other predictors were downloaded. A random forests model (non-parametric machine learning algorithms) and two traditional regression models were developed to estimate ground-level PM 2.5 concentrations. The best-fit model was then utilized to estimate the daily concentrations of PM 2.5 across China with a resolution of 0.1° (≈10 km) during 2005-2016. The daily random forests model showed much higher predictive accuracy than the other two traditional regression models, explaining the majority of spatial variability in daily PM 2.5 [10-fold cross-validation (CV) R 2  = 83%, root mean squared prediction error (RMSE) = 28.1 μg/m 3 ]. At the monthly and annual time-scale, the explained variability of average PM 2.5 increased up to 86% (RMSE = 10.7 μg/m 3 and 6.9 μg/m 3 , respectively). Taking advantage of a novel application of modeling framework and the most recent ground-level PM 2.5 observations, the machine learning method showed higher predictive ability than previous studies. Random forests approach can be used to estimate historical exposure to PM 2.5 in China with high accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.

"I want a normal life like everyone else": Daily life of asylum seekers in Iceland.

PubMed

Ingvarsson, Lilja; Egilson, Snæfrídur Thóra; Skaptadottir, Unnur Dís

2016-11-01

An ever-increasing number of people seek asylum in Iceland. The wait for resolution on application for asylum can take up to three years. During this time participation in daily occupations is disrupted. This study was carried out to gain an understanding of the experience of living as an asylum seeker in Iceland. It explored asylum seekers' opportunities for participation in occupations as well as their overall experiences while waiting for the processing of their application. Eleven semi-structured interviews were conducted with nine participants, of whom six were asylum seekers. A constructivist grounded theory approach was applied to categorize and synthesize data. Four major categories emerged that reflected the participants' difficult living conditions, lack of opportunities for participation, lack of belonging, and feelings of powerlessness. The long processing time of their applications was enormously stressful as well as not being in charge of one's life, living conditions, or income. The results indicate that the long processing time of application for asylum has deteriorating effects on health. In order to promote asylum seekers' well-being and occupational rights attention needs to be focused on their living conditions and opportunities for participation in meaningful occupations, including work.

Computation of rainfall erosivity from daily precipitation amounts.

PubMed

Beguería, Santiago; Serrano-Notivoli, Roberto; Tomas-Burguera, Miquel

2018-10-01

Rainfall erosivity is an important parameter in many erosion models, and the EI30 defined by the Universal Soil Loss Equation is one of the best known erosivity indices. One issue with this and other erosivity indices is that they require continuous breakpoint, or high frequency time interval, precipitation data. These data are rare, in comparison to more common medium-frequency data, such as daily precipitation data commonly recorded by many national and regional weather services. Devising methods for computing estimates of rainfall erosivity from daily precipitation data that are comparable to those obtained by using high-frequency data is, therefore, highly desired. Here we present a method for producing such estimates, based on optimal regression tools such as the Gamma Generalised Linear Model and universal kriging. Unlike other methods, this approach produces unbiased and very close to observed EI30, especially when these are aggregated at the annual level. We illustrate the method with a case study comprising more than 1500 high-frequency precipitation records across Spain. Although the original records have a short span (the mean length is around 10 years), computation of spatially-distributed upscaling parameters offers the possibility to compute high-resolution climatologies of the EI30 index based on currently available, long-span, daily precipitation databases. Copyright © 2018 Elsevier B.V. All rights reserved.

Prediction of daily fine particulate matter concentrations using aerosol optical depth retrievals from the Geostationary Operational Environmental Satellite (GOES).

PubMed

Chudnovsky, Alexandra A; Lee, Hyung Joo; Kostinski, Alex; Kotlov, Tanya; Koutrakis, Petros

2012-09-01

Although ground-level PM2.5 (particulate matter with aerodynamic diameter < 2.5 microm) monitoring sites provide accurate measurements, their spatial coverage within a given region is limited and thus often insufficient for exposure and epidemiological studies. Satellite data expand spatial coverage, enhancing our ability to estimate location- and/or subject-specific exposures to PM2.5. In this study, the authors apply a mixed-effects model approach to aerosol optical depth (AOD) retrievals from the Geostationary Operational Environmental Satellite (GOES) to predict PM2.5 concentrations within the New England area of the United States. With this approach, it is possible to control for the inherent day-to-day variability in the AOD-PM2.5 relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles, and ground surface reflectance. The model-predicted PM2.5 mass concentration are highly correlated with the actual observations, R2 = 0.92. Therefore, adjustment for the daily variability in AOD-PM2.5 relationship allows obtaining spatially resolved PM2.5 concentration data that can be of great value to future exposure assessment and epidemiological studies. The authors demonstrated how AOD can be used reliably to predict daily PM2.5 mass concentrations, providing determination of their spatial and temporal variability. Promising results are found by adjusting for daily variability in the AOD-PM2.5 relationship, without the need to account for a wide variety of individual additional parameters. This approach is of a great potential to investigate the associations between subject-specific exposures to PM2.5 and their health effects. Higher 4 x 4-km resolution GOES AOD retrievals comparing with the conventional MODerate resolution Imaging Spectroradiometer (MODIS) 10-km product has the potential to capture PM2.5 variability within the urban domain.

Combining Vegetation Index Derived from PhenoCam with EVI to Estimate Daily GPP in Semi-arid Grassland

NASA Astrophysics Data System (ADS)

Wang, H.; Jia, G.

2017-12-01

Accurate estimation of temporal continuous gross primary production (GPP) plays an important role in mechanistic understanding of global carbon budget and exchange between atmosphere and terrestrial ecosystems. Ground based PhenoCam can provide near surface observations of plant phenology with high temporal resolution and have great potential in modeling seasonal dynamics of GPP. However, due to the empirical approaches for estimating fAPAR, there still exist some uncertainties of adopting PhenoCam images in GPP modeling. In this study, we combined excess green index (EGI) derived from PhenoCam and EVI retrieved from MODIS to generate daily time-series of fAPAR (fAPARcam), and then to estimate daily GPP (GPPpre) with a light use efficiency model in semi-arid grassland from 2012 to 2014. Among the three continuous years, daily fAPARcam exhibited similar temporal behaviors with eddy covariance observed GPP (GPPobs). The overall determination coefficients (R2) were all greater than 0.81. GPPpre agreed well with GPPobs and these agreements showed highly statistically significant (p <0.01). R2 ranged from 0.80 to 0.87, RE ranged from -2.9% to 2.81% and RMSE ranged from 0.83 (gC/m2d-1) to 0.98 (gC/m2d-1). GPPpre was then further evaluated by comparing with MODIS GPP products and VPM modeled GPP. Validation showed the variance explained by GPPpre is still the highest. RMSE and RE were also lower than the other two in general. Explanatory power of inputs in GPP modeling was also explored: fAPAR is the most influential input and PAR takes the second place. Contributions of Tscalar and Wscalar are lower than PAR. These results highlight the potential of PhenoCam images in high temporal resolution GPP modeling. Our GPP modeling method will help to reduce uncertainties of using PhenoCam images in monitoring of seasonal development of vegetation production.

Greenland Ice Sheet Melt from MODIS and Associated Atmospheric Variability

NASA Technical Reports Server (NTRS)

Hakkinen, Sirpa; Hall, Dorothy K.; Shuman, Christopher A.; Worthen, Denise L.; DiGirolamo, Nicolo E.

2014-01-01

Daily June-July melt fraction variations over the Greenland Ice Sheet (GIS) derived from the MODerate-resolution Imaging Spectroradiometer (MODIS) (2000-2013) are associated with atmospheric blocking forming an omega-shape ridge over the GIS at 500hPa height (from NCEPNCAR). Blocking activity with a range of time scales, from synoptic waves breaking poleward ( 5 days) to full-fledged blocks (5 days), brings warm subtropical air masses over the GIS controlling daily surface temperatures and melt. The temperature anomaly of these subtropical air mass intrusions is also important for melting. Based on the largest MODIS melt years (2002 and 2012), the area-average temperature anomaly of 2 standard deviations above the 14-year June-July mean, results in a melt fraction of 40 or more. Summer 2007 had the most blocking days, however atmospheric temperature anomalies were too small to instigate extreme melting.

New global fire emission estimates and evaluation of volatile organic compounds

Treesearch

C. Wiedinmyer; L. K. Emmons; S. K. Akagi; R. J. Yokelson; J. J. Orlando; J. A. Al-Saadi; A. J. Soja

2010-01-01

A daily, high-resolution, global fire emissions model has been built to estimate emissions from open burning for air quality modeling applications: The Fire INventory from NCAR (FINN version 1). The model framework uses daily fire detections from the MODIS instruments and updated emission factors, specifically for speciated non-methane organic compounds (NMOC). Global...

Vegetation Greenness and Its Drivers across Ice-free Greenland

NASA Astrophysics Data System (ADS)

Pedersen, S. H.; Liston, G. E.; Tamstorf, M. P.; Schmidt, N. M.

2017-12-01

The coastal and mountain areas surrounding the Greenland Ice Sheet cover one-fifth of Greenland. This ice-free area spans more than 20 degrees latitude and includes high-, low-, and sub-Arctic climate zones and the terrain varies from sea level to 3700 m elevation. Hence, this area contains a wide range of vegetation growing conditions associated with precipitation, temperature, and incoming solar radiation found across these latitudinal, elevational, and coast-inland gradients. In this study, we mapped the spatial distribution of vegetation at 300-m spatial resolution across ice-free Greenland using the annual maximum vegetation greenness (MaxNDVI) and the timing of MaxNDVI derived from daily Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data from 2000-2015. Further, we investigated the drivers of the annual MaxNDVI and its timing across the diverse vegetation growing conditions in Greenland using modeled climatic variables, including snow quantity and timing, at the same temporal and spatial resolutions. The annual average MaxNDVI varied between 0.3 and 0.5 in North Greenland, and 0.6 and 0.9 in South Greenland. The timing of MaxNDVI differed more than two weeks between North and South Greenland. The potential growing season, e.g., the period with no snow on the ground, was as short as one month in North Greenland (mainly August), and four to five times longer in South Greenland (typically starting in mid-May). The snow-free date varied with elevation, from valley bottoms to the mountain tops, having the same range that existed from South to North Greenland. Our results show that MaxNDVI and its timing are significantly driven by the timing of snow-free ground and the amount of meltwater available from the snowpack during spring snowmelt.

Regional downscaling of temporal resolution in near-surface wind from statistically downscaled Global Climate Models (GCMs) for use in San Francisco Bay coastal flood modeling

NASA Astrophysics Data System (ADS)

O'Neill, A.; Erikson, L. H.; Barnard, P.

2013-12-01

While Global Climate Models (GCMs) provide useful projections of near-surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling. Statistically downscaled GCM projections from Multivariate Adaptive Constructed Analogues (MACA) provide daily near-surface winds at an appropriate spatial resolution for wave modeling within San Francisco Bay. Using 30 years (1975-2004) of climatological data from four representative stations around San Francisco Bay, a library of example daily wind conditions for four corresponding over-water sub-regions is constructed. Empirical cumulative distribution functions (ECDFs) of station conditions are compared to MACA GFDL hindcasts to create correction factors, which are then applied to 21st century MACA wind projections. For each projection day, a best match example is identified via least squares error among all stations from the library. The best match's daily variation in velocity components (u/v) is used as an analogue of representative wind variation and is applied at 3-hour increments about the corresponding sub-region's projected u/v values. High temporal resolution reconstructions using this methodology on hindcast MACA fields from 1975-2004 accurately recreate extreme wind values within the San Francisco Bay, and because these extremes in wind forcing are of key importance in wave and subsequent coastal flood modeling, this represents a valuable method of generating near-surface wind vectors for use in coastal flood modeling.

Evaluation of MODIS NPP and GPP products across multiple biomes.

Treesearch

David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Steve W. Running; Maosheng Zhao; Marcos H. Costa; Al A. Kirschbaum; Jay M. Ham; Scott R. Saleska; Douglas E. Ahl

2006-01-01

Estimates of daily gross primary production (GPP) and annual net primary production (NPP) at the 1 km spatial resolution are now produced operationally for the global terrestrial surface using imagery from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor. Ecosystem-level measurements of GPP at eddy covariance flux towers and plot-level measurements of...

A Wholistic Approach to Conflict Resolution.

ERIC Educational Resources Information Center

Field, Harriet

Conflict, as a natural part of daily life is to some extent inevitable in all child care centers. Children need to develop effective strategies to deal with conflict, and educators need to reduce the amount of conflict present in the total child care environment. Two roles early childhood educators can play in encouraging conflict resolution are…

A gridded hourly rainfall dataset for the UK applied to a national physically-based modelling system

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Blenkinsop, Stephen; Quinn, Niall; Freer, Jim; Coxon, Gemma; Woods, Ross; Bates, Paul; Fowler, Hayley

2016-04-01

An hourly gridded rainfall product has great potential for use in many hydrological applications that require high temporal resolution meteorological data. One important example of this is flood risk management, with flooding in the UK highly dependent on sub-daily rainfall intensities amongst other factors. Knowledge of sub-daily rainfall intensities is therefore critical to designing hydraulic structures or flood defences to appropriate levels of service. Sub-daily rainfall rates are also essential inputs for flood forecasting, allowing for estimates of peak flows and stage for flood warning and response. In addition, an hourly gridded rainfall dataset has significant potential for practical applications such as better representation of extremes and pluvial flash flooding, validation of high resolution climate models and improving the representation of sub-daily rainfall in weather generators. A new 1km gridded hourly rainfall dataset for the UK has been created by disaggregating the daily Gridded Estimates of Areal Rainfall (CEH-GEAR) dataset using comprehensively quality-controlled hourly rain gauge data from over 1300 observation stations across the country. Quality control measures include identification of frequent tips, daily accumulations and dry spells, comparison of daily totals against the CEH-GEAR daily dataset, and nearest neighbour checks. The quality control procedure was validated against historic extreme rainfall events and the UKCP09 5km daily rainfall dataset. General use of the dataset has been demonstrated by testing the sensitivity of a physically-based hydrological modelling system for Great Britain to the distribution and rates of rainfall and potential evapotranspiration. Of the sensitivity tests undertaken, the largest improvements in model performance were seen when an hourly gridded rainfall dataset was combined with potential evapotranspiration disaggregated to hourly intervals, with 61% of catchments showing an increase in NSE between observed and simulated streamflows as a result of more realistic sub-daily meteorological forcing.

High-resolution daily gridded data sets of air temperature and wind speed for Europe

NASA Astrophysics Data System (ADS)

Brinckmann, Sven; Krähenmann, Stefan; Bissolli, Peter

2016-10-01

New high-resolution data sets for near-surface daily air temperature (minimum, maximum and mean) and daily mean wind speed for Europe (the CORDEX domain) are provided for the period 2001-2010 for the purpose of regional model validation in the framework of DecReg, a sub-project of the German MiKlip project, which aims to develop decadal climate predictions. The main input data sources are SYNOP observations, partly supplemented by station data from the ECA&D data set (http://www.ecad.eu). These data are quality tested to eliminate erroneous data. By spatial interpolation of these station observations, grid data in a resolution of 0.044° (≈ 5km) on a rotated grid with virtual North Pole at 39.25° N, 162° W are derived. For temperature interpolation a modified version of a regression kriging method developed by Krähenmann et al.(2011) is used. At first, predictor fields of altitude, continentality and zonal mean temperature are used for a regression applied to monthly station data. The residuals of the monthly regression and the deviations of the daily data from the monthly averages are interpolated using simple kriging in a second and third step. For wind speed a new method based on the concept used for temperature was developed, involving predictor fields of exposure, roughness length, coastal distance and ERA-Interim reanalysis wind speed at 850 hPa. Interpolation uncertainty is estimated by means of the kriging variance and regression uncertainties. Furthermore, to assess the quality of the final daily grid data, cross validation is performed. Variance explained by the regression ranges from 70 to 90 % for monthly temperature and from 50 to 60 % for monthly wind speed. The resulting RMSE for the final daily grid data amounts to 1-2 K and 1-1.5 ms-1 (depending on season and parameter) for daily temperature parameters and daily mean wind speed, respectively. The data sets presented in this article are published at doi:10.5676/DWD_CDC/DECREG0110v2.

Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earths Radiation Budget

NASA Technical Reports Server (NTRS)

Holdaway, Daniel; Yang, Yuekui

2016-01-01

Satellites always sample the Earth-atmosphere system in a finite temporal resolution. This study investigates the effect of sampling frequency on the satellite-derived Earth radiation budget, with the Deep Space Climate Observatory (DSCOVR) as an example. The output from NASA's Goddard Earth Observing System Version 5 (GEOS-5) Nature Run is used as the truth. The Nature Run is a high spatial and temporal resolution atmospheric simulation spanning a two-year period. The effect of temporal resolution on potential DSCOVR observations is assessed by sampling the full Nature Run data with 1-h to 24-h frequencies. The uncertainty associated with a given sampling frequency is measured by computing means over daily, monthly, seasonal and annual intervals and determining the spread across different possible starting points. The skill with which a particular sampling frequency captures the structure of the full time series is measured using correlations and normalized errors. Results show that higher sampling frequency gives more information and less uncertainty in the derived radiation budget. A sampling frequency coarser than every 4 h results in significant error. Correlations between true and sampled time series also decrease more rapidly for a sampling frequency less than 4 h.

High Precision Time Transfer in Space with a Hydrogen Maser on MIR

NASA Technical Reports Server (NTRS)

Mattison, Edward M.; Vessot, Robert F. C.

1996-01-01

An atomic hydrogen maser clock system designed for long term operation in space will be installed on the Russian space station Mir, in late 1997. The H-maser's frequency stability will be measured using pulsed laser time transfer techniques. Daily time comparisons made with a precision of better than 100 picoseconds will allow an assessment of the long term stability of the space maser at a level on the order of 1 part in 10(sup 15) or better. Laser pulse arrival times at the spacecraft will be recorded with a resolution of 10 picoseconds relative to the space clock's time scale. Cube corner reflectors will reflect the pulses back to the Earth laser station to determine the propagation delay and enable comparison with the Earth-based time scale. Data for relativistic and gravitational frequency corrections will be obtained from a Global Positioning System (GPS) receiver.

A cross comparison of spatiotemporally enhanced springtime phenological measurements from satellites and ground in a northern U.S. mixed forest

USGS Publications Warehouse

Liang, Liang; Schwartz, Mark D.; Zhuosen Wang,; Gao, Feng; Schaaf, Crystal B.; Bin Tan,; Morisette, Jeffrey T.; Zhang, Xiaoyang

2014-01-01

Cross comparison of satellite-derived land surface phenology (LSP) and ground measurements is useful to ensure the relevance of detected seasonal vegetation change to the underlying biophysical processes. While standard 16-day and 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index (VI)-based springtime LSP has been evaluated in previous studies, it remains unclear whether LSP with enhanced temporal and spatial resolutions can capture additional details of ground phenology. In this paper, we compared LSP derived from 500-m daily MODIS and 30-m MODIS-Landsat fused VI data with landscape phenology (LP) in a northern U.S. mixed forest. LP was previously developed from intensively observed deciduous and coniferous tree phenology using an upscaling approach. Results showed that daily MODIS-based LSP consistently estimated greenup onset dates at the study area (625 m × 625 m) level with 4.48 days of mean absolute error (MAE), slightly better than that of using 16-day standard VI (4.63 days MAE). For the observed study areas, the time series with increased number of observations confirmed that post-bud burst deciduous tree phenology contributes the most to vegetation reflectance change. Moreover, fused VI time series demonstrated closer correspondences with LP at the community level (0.1-20 ha) than using MODIS alone at the study area level (390 ha). The fused LSP captured greenup onset dates for respective forest communities of varied sizes and compositions with four days of the overall MAE. This study supports further use of spatiotemporally enhanced LSP for more precise phenological monitoring.

A dense camera network for cropland (CropInsight) - developing high spatiotemporal resolution crop Leaf Area Index (LAI) maps through network images and novel satellite data

NASA Astrophysics Data System (ADS)

Kimm, H.; Guan, K.; Luo, Y.; Peng, J.; Mascaro, J.; Peng, B.

2017-12-01

Monitoring crop growth conditions is of primary interest to crop yield forecasting, food production assessment, and risk management of individual farmers and agribusiness. Despite its importance, there are limited access to field level crop growth/condition information in the public domain. This scarcity of ground truth data also hampers the use of satellite remote sensing for crop monitoring due to the lack of validation. Here, we introduce a new camera network (CropInsight) to monitor crop phenology, growth, and conditions that are designed for the US Corn Belt landscape. Specifically, this network currently includes 40 sites (20 corn and 20 soybean fields) across southern half of the Champaign County, IL ( 800 km2). Its wide distribution and automatic operation enable the network to capture spatiotemporal variations of crop growth condition continuously at the regional scale. At each site, low-maintenance, and high-resolution RGB digital cameras are set up having a downward view from 4.5 m height to take continuous images. In this study, we will use these images and novel satellite data to construct daily LAI map of the Champaign County at 30 m spatial resolution. First, we will estimate LAI from the camera images and evaluate it using the LAI data collected from LAI-2200 (LI-COR, Lincoln, NE). Second, we will develop relationships between the camera-based LAI estimation and vegetation indices derived from a newly developed MODIS-Landsat fusion product (daily, 30 m resolution, RGB + NIR + SWIR bands) and the Planet Lab's high-resolution satellite data (daily, 5 meter, RGB). Finally, we will scale up the above relationships to generate high spatiotemporal resolution crop LAI map for the whole Champaign County. The proposed work has potentials to expand to other agro-ecosystems and to the broader US Corn Belt.

Evaluation of sub daily satellite rainfall estimates through flash flood modelling in the Lower Middle Zambezi Basin

NASA Astrophysics Data System (ADS)

Matingo, Thomas; Gumindoga, Webster; Makurira, Hodson

2018-05-01

Flash floods are experienced almost annually in the ungauged Mbire District of the Middle Zambezi Basin. Studies related to hydrological modelling (rainfall-runoff) and flood forecasting require major inputs such as precipitation which, due to shortage of observed data, are increasingly using indirect methods for estimating precipitation. This study therefore evaluated performance of CMORPH and TRMM satellite rainfall estimates (SREs) for 30 min, 1 h, 3 h and daily intensities through hydrologic and flash flood modelling in the Lower Middle Zambezi Basin for the period 2013-2016. On a daily timestep, uncorrected CMORPH and TRMM show Probability of Detection (POD) of 61 and 59 %, respectively, when compared to rain gauge observations. The best performance using Correlation Coefficient (CC) was 70 and 60 % on daily timesteps for CMORPH and TRMM, respectively. The best RMSE for CMORPH was 0.81 % for 30 min timestep and for TRMM was 2, 11 % on 3 h timestep. For the year 2014 to 2015, the HEC-HMS (Hydrological Engineering Centre-Hydrological Modelling System) daily model calibration Nash Sutcliffe efficiency (NSE) for Musengezi sub catchment was 59 % whilst for Angwa it was 55 %. Angwa sub-catchment daily NSE results for the period 2015-2016 was 61 %. HEC-RAS flash flood modeling at 100, 50 and 25 year return periods for Angwa sub catchment, inundated 811 and 867 ha for TRMM rainfall simulated discharge at 3 h and daily timesteps, respectively. For CMORPH generated rainfall, the inundation was 818, 876, 890 and 891 ha at daily, 3 h, 1 h and 30 min timesteps. The 30 min time step for CMORPH effectively captures flash floods with the measure of agreement between simulated flood extent and ground control points of 69 %. For TRMM, the 3 h timestep effectively captures flash floods with coefficient of 67 %. The study therefore concludes that satellite products are most effective in capturing localized hydrological processes such as flash floods for sub-daily rainfall, because of improved spatial and temporal resolution.

Pseudomonas keratitis associated with daily wear of silicone hydrogel contact lenses.

PubMed

Schornack, Muriel M; Faia, Lisa J; Griepentrog, Gregory J

2008-03-01

To report two cases of pseudomonas keratitis associated with daily wear of silicone hydrogel contact lenses. Medical records of two patients who developed pseudomonas keratitis while wearing silicone hydrogel lenses on a daily-wear schedule are reviewed and discussed. A 13-year-old girl who wore ACUVUE Advance lenses (Johnson & Johnson Vision Care, Jacksonville, FL) 12 to 14 hours daily developed a paracentral corneal ulcer in her left eye 4 months after beginning contact lens use. Cultures were positive for Pseudomonas aeruginosa. The ulcer responded to fortified antibiotics and resolved in 10 days. Best-corrected visual acuity after resolution of the ulcer was 20/25. A 58-year-old woman with a 30-year history of rigid gas-permeable contact lens wear was refitted with O2 Optix lenses (CIBA Vision, Duluth, GA). Six months later, she had a 4.9 x 4.0 mm epithelial defect with an underlying stromal infiltrate in the right eye. Cultures were positive for P. aeruginosa. The ulcer responded to fortified antibiotics and resolved in 30 days. Best-corrected visual acuity after resolution of the ulcer was 20/30. Increased oxygen permeability associated with silicone hydrogel contact lenses may reduce, but does not eliminate, the risk of pseudomonas keratitis. Studies have yet to quantify the risk of keratitis associated with daily wear of these lens materials. Further study is necessary to identify the risks of complications with daily wear of silicone hydrogel lenses and to determine which factors may contribute to those risks.

A calibrated, high-resolution goes satellite solar insolation product for a climatology of Florida evapotranspiration

USGS Publications Warehouse

Paech, S.J.; Mecikalski, J.R.; Sumner, D.M.; Pathak, C.S.; Wu, Q.; Islam, S.; Sangoyomi, T.

2009-01-01

Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10-year period (1995-2004). These insolation estimates were developed into well-calibrated half-hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2-week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground-based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three-step process: (1) comparison with ground-based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m-2/day (13%). Calibration reduced errors to 1.7 MJ m -2/day (10%), and also removed temporal-related, seasonal-related, and satellite sensor-related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2-km resolution maps of estimated daily reference and potential evapotranspiration for water management-related activities. ?? 2009 American Water Resources Association.

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

NASA Astrophysics Data System (ADS)

Leonarduzzi, Elena; Molnar, Peter; McArdell, Brian W.

2017-08-01

A high-resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity-duration ID curves and validated their performance. The best predictive performance was obtained by the intensity-duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country-wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high-quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack-knife and cross-validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

Linking innovative measurement technologies (ConMon and Dataflow© systems) for high-resolution temporal and spatial dissolved oxygen criteria assessment.

PubMed

O'Leary, C A; Perry, E; Bayard, A; Wainger, L; Boynton, W R

2015-10-01

One consequence of nutrient-induced eutrophication in shallow estuarine waters is the occurrence of hypoxia and anoxia that has serious impacts on biota, habitats, and biogeochemical cycles of important elements. Because of the important role of dissolved oxygen (DO) on these ecosystem features, a variety of DO criteria have been established as indicators of system condition. However, DO dynamics are complex and vary on time scales ranging from diel to decadal and spatial scales from meters to multiple kilometers. Because of these complexities, determining DO criteria attainment or failure remains difficult. We propose a method for linking two common measurement technologies for shallow water DO criteria assessment using a Chesapeake Bay tributary as a test case. Dataflow© is a spatially intensive (30-60-m collection intervals) system used to map surface water conditions at the whole estuary scale, and ConMon is a high-frequency (15-min collection intervals) fixed station approach. The former technology is effective with spatial descriptions but poor regarding temporal resolution, while the latter provides excellent temporal but very limited spatial resolution. Our methodology for combining the strengths of these measurement technologies involved a sequence of steps. First, a statistical model of surface water DO dynamics, based on temporally intense ConMon data, was developed. The results of this model were used to calculate daily DO minimum concentrations. Second, this model was then inserted into Dataflow©-generated spatial maps of DO conditions and used to adjust measured DO concentrations to daily minimum concentrations. This information was used to assess DO criteria compliance at the full tributary scale. Model results indicated that it is vital to consider the short-term time scale DO criteria across both space and time concurrently. Large fluctuations in DO occurred within a 24-h time period, and DO dynamics varied across the length and width of the tributary. The overall result provided a more detailed and realistic characterization of the shallow water DO minimum conditions that have the potential to be extended to other tributaries and regions. Broader applications of this model include instantaneous DO criteria assessment, utilizing this model in combination with aerial remote sensing, and developing DO amplitude as an indicator of impaired water bodies.

Upper Ocean Mixing Processes and Circulation in the Arabian Sea during Monsoons using Remote Sensing, Hydrographic Observations and HYCOM Simulations

DTIC Science & Technology

2015-09-30

effecting the salinity of the upper layer and the formation of the barrier layer (BL) within the isothermal layer. The BL in turn controls vertical mixing...daily values over a month with a 1° horizontal resolution [Reynolds et al., 2002]. Daily data (from Coriolis project) and Monthly gridded Argo

A multimodel intercomparison of resolution effects on precipitation: simulations and theory

NASA Astrophysics Data System (ADS)

Rauscher, Sara A.; O'Brien, Travis A.; Piani, Claudio; Coppola, Erika; Giorgi, Filippo; Collins, William D.; Lawston, Patricia M.

2016-10-01

An ensemble of six pairs of RCM experiments performed at 25 and 50 km for the period 1961-2000 over a large European domain is examined in order to evaluate the effects of resolution on the simulation of daily precipitation statistics. Application of the non-parametric two-sample Kolmorgorov-Smirnov test, which tests for differences in the location and shape of the probability distributions of two samples, shows that the distribution of daily precipitation differs between the pairs of simulations over most land areas in both summer and winter, with the strongest signal over southern Europe. Two-dimensional histograms reveal that precipitation intensity increases with resolution over almost the entire domain in both winter and summer. In addition, the 25 km simulations have more dry days than the 50 km simulations. The increase in dry days with resolution is indicative of an improvement in model performance at higher resolution, while the more intense precipitation exceeds observed values. The systematic increase in precipitation extremes with resolution across all models suggests that this response is fundamental to model formulation. Simple theoretical arguments suggest that fluid continuity, combined with the emergent scaling properties of the horizontal wind field, results in an increase in resolved vertical transport as grid spacing decreases. This increase in resolution-dependent vertical mass flux then drives an intensification of convergence and resolvable-scale precipitation as grid spacing decreases. This theoretical result could help explain the increasingly, and often anomalously, large stratiform contribution to total rainfall observed with increasing resolution in many regional and global models.

Lagrangian Statistics and Intermittency in Gulf of Mexico.

PubMed

Lin, Liru; Zhuang, Wei; Huang, Yongxiang

2017-12-12

Due to the nonlinear interaction between different flow patterns, for instance, ocean current, meso-scale eddies, waves, etc, the movement of ocean is extremely complex, where a multiscale statistics is then relevant. In this work, a high time-resolution velocity with a time step 15 minutes obtained by the Lagrangian drifter deployed in the Gulf of Mexico (GoM) from July 2012 to October 2012 is considered. The measured Lagrangian velocity correlation function shows a strong daily cycle due to the diurnal tidal cycle. The estimated Fourier power spectrum E(f) implies a dual-power-law behavior which is separated by the daily cycle. The corresponding scaling exponents are close to -1.75 and -2.75 respectively for the time scale larger (resp. 0.1 ≤ f ≤ 0.4 day -1 ) and smaller (resp. 2 ≤ f ≤ 8 day -1 ) than 1 day. A Hilbert-based approach is then applied to this data set to identify the possible multifractal property of the cascade process. The results show an intermittent dynamics for the time scale larger than 1 day, while a less intermittent dynamics for the time scale smaller than 1 day. It is speculated that the energy is partially injected via the diurnal tidal movement and then transferred to larger and small scales through a complex cascade process, which needs more studies in the near future.

Documentation of the Douglas-fir tussock moth outbreak-population model.

Treesearch

J.J. Colbert; W. Scott Overton; Curtis. White

1979-01-01

Documentation of three model versions: the Douglas-fir tussock moth population-branch model on (1) daily temporal resolution, (2) instart temporal resolution, and (3) the Douglas-fir tussock moth stand-outbreak model; the hierarchical framework and the conceptual paradigm used are described. The coupling of the model with a normal-stand model is discussed. The modeling...

Amisulpride Augmentation in Acute Catatonia.

PubMed

Arora, Manu; Banal, Rakesh; Praharaj, Samir K; Mahajan, Vivek

Benzodiazepines are the first-line treatment of catatonia, but a substantial number of patients do not respond to them. Amisulpride is one of the atypical antipsychotic that has been effective for negative symptoms of schizophrenia. We examined the effect of augmentation of oral low doses of amisulpride with lorazepam on resolution of catatonic symptoms. Fifteen patients with catatonia were treated with a combination of oral lorazepam (2-4 mg) with amisulpride (100 mg). Catatonic symptoms were rated using the Bush Francis Catatonia Rating Scale at the baseline and daily thereafter. There was complete resolution of catatonic symptoms on the third day in all patients. There was significant reduction of the total Bush Francis Catatonia Rating Scale score over time (F = 181.38, P < 0.001) with a strong effect size (partial η = 0.96). Augmentation of lorazepam with low-dose amisulpride can be a reliable strategy for management of catatonia.

Production of long-term global water vapor and liquid water data set using ultra-fast methods to assimilate multi-satellite and radiosonde observations

NASA Technical Reports Server (NTRS)

Vonderhaar, Thomas H.; Randel, David L.; Reinke, Donald L.; Stephens, Graeme L.; Ringerud, Mark A.; Combs, Cynthia L.; Greenwald, Thomas J.; Wittmeyer, Ian L.

1994-01-01

In recent years climate research scientists have recognized the need for increased time and space resolution precipitable and liquid water data sets. This project is designed to meet those needs. Specifically, NASA is funding STC-METSAT to develop a total integrated column and layered precipitable water data set. This is complemented by a total column liquid water data set. These data are global in extent, 1 deg x 1 deg in resolution, with daily grids produced. Precipitable water is measured by a combination of in situ radiosonde observations and satellite derived infrared and microwave retrievals from four satellites. This project combines these data into a coherent merged product for use in global climate research. This report is the Year 2 Annual Report from this NASA-sponsored project and includes progress-to-date on the assigned tasks.

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

NASA Astrophysics Data System (ADS)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.

High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

NASA Technical Reports Server (NTRS)

Chudnovsky, A.; Lyapustin, A.; Wang, Y.; Tang, C.; Schwartz, J.; Koutrakis, P.

2013-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment for the daily variability in the AOD-PM(sub 2.5) relationship provides a means for obtaining spatially-resolved PM(sub 2.5) concentrations.

Use of a Weather Generator for analysis of projections of future daily temperature and its validation with climate change indices

NASA Astrophysics Data System (ADS)

Di Piazza, A.; Cordano, E.; Eccel, E.

2012-04-01

The issue of climate change detection is considered a major challenge. In particular, high temporal resolution climate change scenarios are required in the evaluation of the effects of climate change on agricultural management (crop suitability, yields, risk assessment, etc.) energy production and water management. In this work, a "Weather Generator" technique was used for downscaling climate change scenarios for temperature. An R package (RMAWGEN, Cordano and Eccel, 2011 - available on http://cran.r-project.org) was developed aiming to generate synthetic daily weather conditions by using the theory of vectorial auto-regressive models (VAR). The VAR model was chosen for its ability in maintaining the temporal and spatial correlations among variables. In particular, observed time series of daily maximum and minimum temperature are transformed into "new" normally-distributed variable time series which are used to calibrate the parameters of a VAR model by using ordinary least square methods. Therefore the implemented algorithm, applied to monthly mean climatic values downscaled by Global Climate Model predictions, can generate several stochastic daily scenarios where the statistical consistency among series is saved. Further details are present in RMAWGEN documentation. An application is presented here by using a dataset with daily temperature time series recorded in 41 different sites of Trentino region for the period 1958-2010. Temperature time series were pre-processed to fill missing values (by a site-specific calibrated Inverse Distance Weighting algorithm, corrected with elevation) and to remove inhomogeneities. Several climatic indices were taken into account, useful for several impact assessment applications, and their time trends within the time series were analyzed. The indices go from the more classical ones, as annual mean temperatures, seasonal mean temperatures and their anomalies (from the reference period 1961-1990) to the climate change indices selected from the list recommended by the World Meteorological Organization Commission for Climatology (WMO-CCL) and the Research Programme on Climate Variability and Predictability (CLIVAR) project's Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). Each index was applied to both observed (and processed) data and to synthetic time series produced by the Weather Generator, over the thirty year reference period 1981-2010, in order to validate the procedure. Climate projections were statistically downscaled for a selection of sites for the two 30-year periods 2021-2050 and 2071-2099 of the European project "Ensembles" multi-model output (scenario A1B). The use of several climatic indices strengthens the trend analysis of both the generated synthetic series and future climate projections.

Virtual Rain and Stream Gauge Information Service to Support Effective Decision Making in Lower Mekong Countries

NASA Astrophysics Data System (ADS)

Basnayake, S. B.; Jayasinghe, S.; Apirumanekul, C.; Pudashine, J.; Anderson, E.; Cutter, P. G.; Ganz, D.; Towashiraporn, P.

2016-12-01

During 1995-2015, about 47% of all weather related disasters affected 2.3 billion people, and the majority (95%) of them were from Asia. About 89% of the deaths due to storms were reported in lower and middle income courtiers even though they only experienced about 26% of all storms. In most of the developing countries, decision making processes are hampered by sparse hydro-meteorological observation networks. Thus, the virtual rain and stream gauge information service is designed and developed by SERVIR-Mekong of Asian Disaster Preparedness Center (ADPC) to support effective decision making in Cambodia, Lao PDR, Myanmar, Thailand and Vietnam. The information service contains four remotely sensed data streams with regional and country specific sub setting features for easy access in limited internet bandwidths conditions. It provides rainfall data from near real time GPM IMERG (6 hours latency) with 30 minutes and 0.1X0.1 degree resolutions; TRMM daily data of 0.25X0.25 degree resolution from 1998; and CHIRPS daily data of 0.05X0.05 degree resolution since 1981 with the latency of one month. Satellite altimetry-based Jason 2 Interim Geophysical Data Record virtual stream gauge data (water body height) is provided with 12 days latency for 15 identified locations in 5 countries since 2008. To regionalize and further promote uptake of these data, TRMM monthly data has been bias corrected for Myanmar as a pilot study with spatially interpolated 18-year average (1998-2015) observed monthly rainfall data using Standard Deviation (SD) Ratio method. The results encourage to use SD ratio method for monthly bias corrections. Gamma distribution method will be tested for correcting biases of daily rainfall data with the notion that it has some limitations of capturing extreme rainfalls. The virtual rain and stream gauge information service is publically accessible through a web-based user interface hosted at SERVIR-Mekong of ADPC. Usage of the information service by partner agencies is ensured through co-development and capacity building programs. This service helps lower Mekong countries and their relevant organizations effectively use of remotely sensed data for day-to-day operations, contingency and development planning.

Daily simulations of urban heat load in Vienna for 2011

NASA Astrophysics Data System (ADS)

Hollosi, Brigitta; Zuvela-Aloise, Maja; Koch, Roland

2014-05-01

In this study, the dynamical urban climate model MUKLIMO3 (horizontal resolution of 100 m) is uni-directionally coupled with the operational weather forecast model ALARO-ALADIN of the ZAMG (horizontal resolution of 4.8 km) to simulate the development of the urban heat island in Vienna on a daily basis. The aim is to evaluate the performance of the urban climate model applied for climatological studies in a weather prediction mode. The focus of the investigation is on assessment of the urban heat load during day-time. We used the archived daily forecast data for the summer period in 2011 (April - October) as input data for the urban climate model. The high resolution simulations were initialized with vertical profiles of temperature and relative humidity and prevailing wind speed and direction in the rural area near the city in the early morning hours. The model output for hourly temperature and relative humidity has been evaluated against the monitoring data at 9 weather stations in the area of the city. Additionally, spatial gradients in temperature were evaluated by comparing the grid point values with the data collected during a mobile measuring campaign taken on a multi-vehicle bicycle tour on the 7th of July, 2011. The results show a good agreement with observations on a district scale. Particular challenge in the modeling approach is achieving robust and numerically stable model solutions for different weather situation. Therefore, we analyzed modeled wind patterns for different atmospheric conditions in the summer period. We found that during the calm hot days, due to the inhomogeneous surface and complex terrain, the local-scale temperature gradients can induce strong anomalies, which in turn could affect the circulation on a larger scale. However, these results could not be validated due to the lack of observations. In the following years extreme hot conditions are very likely to occur more frequently and with higher intensity. Combining urban climate simulations with the operational meso-scale forecasting model may identify hot spots in urban areas and bring added value in excessive heat warning systems in the future.

Effect of Downscaled Forcings and Soil Texture Properties on Hyperresolution Hydrologic Simulations in a Regional Basin in Northwest Mexico

NASA Astrophysics Data System (ADS)

Ko, A.; Mascaro, G.; Vivoni, E. R.

2017-12-01

Hyper-resolution (< 1 km) hydrological modeling is expected to support a range of studies related to the terrestrial water cycle. A critical need for increasing the utility of hyper-resolution modeling is the availability of meteorological forcings and land surface characteristics at high spatial resolution. Unfortunately, in many areas these datasets are only available at coarse (> 10 km) scales. In this study, we address some of the challenges by applying a parallel version of the Triangulated Irregular Network (TIN)-based Real Time Integrated Basin Simulator (tRIBS) to the Rio Sonora Basin (RSB) in northwest Mexico. The RSB is a large, semiarid watershed ( 21,000 km2) characterized by complex topography and a strong seasonality in vegetation conditions, due to the North American monsoon. We conducted simulations at an average spatial resolution of 88 m over a decadal (2004-2013) period using spatially-distributed forcings from remotely-sensed and reanalysis products. Meteorological forcings were derived from the North American Land Data Assimilation System (NLDAS) at the original resolution of 12 km and were downscaled at 1 km with techniques accounting for terrain effects. Two grids of soil properties were created from different sources, including: (i) CONABIO (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad) at 6 km resolution; and (ii) ISRIC (International Soil Reference Information Centre) at 250 m. Time-varying vegetation parameters were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) composite products. The model was first calibrated and validated through distributed soil moisture data from a network of 20 soil moisture stations during the monsoon season. Next, hydrologic simulations were conducted with five different combinations of coarse and downscaled forcings and soil properties. Outputs in the different configurations were then compared with independent observations of soil moisture, and with estimates of land surface temperature (1 km, daily) and evapotranspiration (1 km, monthly) from MODIS. This study is expected to support the community involved in hyper-resolution hydrologic modeling by identifying the crucial factors that, if available at higher resolution, lead to the largest improvement of the simulation prognostic capability.

Global, Daily, Near Real-Time Satellite-based Flood Monitoring and Product Dissemination

NASA Astrophysics Data System (ADS)

Slayback, D. A.; Policelli, F. S.; Brakenridge, G. R.; Tokay, M. M.; Smith, M. M.; Kettner, A. J.

2013-12-01

Flooding is the most destructive, frequent, and costly natural disaster faced by modern society, and is expected to increase in frequency and damage with climate change and population growth. Some of 2013's major floods have impacted the New York City region, the Midwest, Alberta, Australia, various parts of China, Thailand, Pakistan, and central Europe. The toll of these events, in financial costs, displacement of individuals, and deaths, is substantial and continues to rise as climate change generates more extreme weather events. When these events do occur, the disaster management community requires frequently updated and easily accessible information to better understand the extent of flooding and better coordinate response efforts. With funding from NASA's Applied Sciences program, we developed and are now operating a near real-time global flood mapping system to help provide critical flood extent information within 24-48 hours of events. The system applies a water detection algorithm to MODIS imagery received from the LANCE (Land Atmosphere Near real-time Capability for EOS) system at NASA Goddard within a few hours of satellite overpass. Using imagery from both the Terra (10:30 AM local time overpass) and Aqua (1:30 PM) platforms allows an initial daily assessment of flooding extent by late afternoon, and more robust assessments after accumulating cloud-free imagery over several days. Cloud cover is the primary limitation in detecting surface water from MODIS imagery. Other issues include the relatively coarse scale of the MODIS imagery (250 meters), the difficulty of detecting flood waters in areas with continuous canopy cover, confusion of shadow (cloud or terrain) with water, and accurately identifying detected water as flood as opposed to normal water extents. We have made progress on many of these issues, and are working to develop higher resolution flood detection using alternate sensors, including Landsat and various radar sensors. Although these provide better spatial resolution, this typically comes at the cost of being less timely. Since late 2011, this system has been providing daily flood maps of the global non-antarctic land surface. These data products are generated in raster and vector formats, and provided freely on our website. To better serve the disaster response community, we have recently begun providing the products via live OGC (Open Geospatial Consortium) services, allowing easy access in a variety of platforms (Google Earth, desktop GIS software, mobile phone apps). We are also working with the Pacific Disaster Center to bring our product into their Disaster Alert system (including a mobile app), which will help simplify product distribution to the disaster management community.

Effects of antithrombotic drugs in patients with left ventricular thrombi: assessment with indium-111 platelet imaging and two-dimensional echocardiography

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

Stratton, J.R.; Ritchie, J.L.

Patients with left ventricular thrombi not caused by recent myocardial infarction were prospectively studied by indium-111 platelet imaging and two-dimensional echocardiography to determine the reproducibility of these techniques and the short-term effects of sulfinpyrazone (200 mg four times daily), aspirin (325 mg three times daily) plus dipyridamole (75 mg three times daily), and full-dose warfarin. At baseline, all patients underwent indium-111 platelet imaging and echocardiography, and the results were positive for thrombus. In six patients on no antithrombotic drug therapy, repeat platelet scans and echocardiographic studies at 6.0 +/- 3.3 weeks remained positive and were unchanged. In seven patients studiedmore » on sulfinpyrazone, three platelet scans became negative, two became equivocal, and two were unchanged; the presence and size of thrombus was constant by echocardiography in all seven patients. Of the six patients studied on aspirin plus dipyridamole, one platelet scan became negative, those of three became equivocal, and two were unchanged; all echocardiographic findings remained positive, but one patient had decreased thrombus size. Among four warfarin-treated patients, three had resolution of platelet deposition and one was unchanged; by echocardiography, thrombus resolved in one patient, was decreased in size in one, and was unchanged in two. We conclude that, in the absence of antithrombotic drug therapy, platelet imaging and echocardiographic findings are stable in patients with left ventricular thrombi not caused by recent myocardial infarction. Sulfinpyrazone, aspirin plus dipyridamole, and warfarin all interrupt platelet deposition in some patients with chronic left ventricular thrombi.« less

ERP-Variations on Time Scales Between Hours and Months Derived From GNSS Observations

NASA Astrophysics Data System (ADS)

Weber, R.; Englich, S.; Mendes Cerveira, P.

2007-05-01

Current observations gained by the space geodetic techniques, especially VLBI, GPS and SLR, allow for the determination of Earth Rotation Parameters (ERPs - polar motion, UT1/LOD) with unprecedented accuracy and temporal resolution. This presentation focuses on contributions to the ERP recovery provided by satellite navigation systems (primarily GPS). The IGS (International GNSS Service), for example, currently provides daily polar motion with an accuracy of less than 0.1mas and LOD estimates with an accuracy of a few microseconds. To study more rapid variations in polar motion and LOD we established in a first step a high resolution (hourly resolution) ERP-time series from GPS observation data of the IGS network covering the year 2005. The calculations were carried out by means of the Bernese GPS Software V5.0 considering observations from a subset of 113 fairly stable stations out of the IGS05 reference frame sites. From these ERP time series the amplitudes of the major diurnal and semidiurnal variations caused by ocean tides are estimated. After correcting the series for ocean tides the remaining geodetic observed excitation is compared with variations of atmospheric excitation (AAM). To study the sensitivity of the estimates with respect to the applied mapping function we applied both the widely used NMF (Niell Mapping Function) and the VMF1 (Vienna Mapping Function 1). In addition, based on computations covering two months in 2005, the potential improvement due to the use of additional GLONASS data will be discussed.

Recent Shift of Deforestation to High Elevation Areas from 2001 to 2013 in Borneo Detected by MODIS Data

NASA Astrophysics Data System (ADS)

Nagai, S.; Suzuki, R.

2015-12-01

The biomass of tropical forests sequestrates tons of carbon and plays an important role in the global carbon cycle regulating the climate. Also its high biodiversity ecosystems bring us many valuable resources and cultural and educational ecosystem services. However, large areas of the tropical forest are deforested and converted to oil palm or acacia plantation for the economic benefit of the local society mainly in Southeast Asia. Monitoring of the tropical forest from satellites provides us the information about the deforestation for decadal time period over extensive areas and enables us to discuss it from a scientific point of view. The purpose of this study is to reveal the interannual change and recent trend of deforestation in relation to the land elevation for decadal time period over Borneo by using data from Moderate Resolution Imaging Spectroradiometer (MODIS). We acquired the atmospherically corrected and cloud free Terra-MODIS and Aqua-MODIS daily data products (MOD09GA and MYD09GA; collection 5) from 2001 to 2013 for Borneo. We extracted the pixel values in the 500m surface reflectance bands 1 (red) and 4 (green) products and calculated the green-red vegetation index (GRVI), (band 4 - band 1) / (band 4 + band 1), at a daily time step. GRVI shows a positive value for the land prevailed by green vegetation, while it shows a negative value for the land prevailed by no-green components such as bare land. As for the elevation data, ASTER Global Digital Elevation Model (GDEM) which has 33.3m spatial resolution was employed. The original resolution was resampled to the grid system of MODIS data (i.e. 500m resolution). Pixels which had a negative GRVI ratio more than 80 % (termed as "no green pixel") in each year were regarded as the land characterized by no vegetation, and mapped the distribution for each year. Throughout the 13 years, no green pixels mainly found over the coastal low land below 20m of the elevation and the area was almost constant (around 3000km2). It is considered the deforestation for the plantations generally occurred over the easy access low lands. By contrast, it was obvious that no green pixels extended their distribution up to high elevation (20 to 120m) areas mainly after 2006. This trend suggests recent development of the plantation has been extended to relatively inland and high elevation areas.

MODIS Snow-Cover Products

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Riggs, George A.; Salomonson, Vincent V.; DiGirolamo, Nicole E.; Bayr, Klaus J.; Houser, Paul R. (Technical Monitor)

2002-01-01

On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. MODIS snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to or enhancement of the currently-available operational products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. Also the snow-mapping algorithms are automated which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The MODIS snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at about 5.6-km spatial resolution, with both daily and 8-day composite products. Each pixel of the CMG contains fraction of snow cover from 40 - 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02 - 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented to show some early validation work.

A global dataset of sub-daily rainfall indices

NASA Astrophysics Data System (ADS)

Fowler, H. J.; Lewis, E.; Blenkinsop, S.; Guerreiro, S.; Li, X.; Barbero, R.; Chan, S.; Lenderink, G.; Westra, S.

2017-12-01

It is still uncertain how hydrological extremes will change with global warming as we do not fully understand the processes that cause extreme precipitation under current climate variability. The INTENSE project is using a novel and fully-integrated data-modelling approach to provide a step-change in our understanding of the nature and drivers of global precipitation extremes and change on societally relevant timescales, leading to improved high-resolution climate model representation of extreme rainfall processes. The INTENSE project is in conjunction with the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges Project (GEWEX) Science questions. A new global sub-daily precipitation dataset has been constructed (data collection is ongoing). Metadata for each station has been calculated, detailing record lengths, missing data, station locations. A set of global hydroclimatic indices have been produced based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. This will provide a unique global data resource on sub-daily precipitation whose derived indices will be freely available to the wider scientific community.

Resolution of Persistent Post-Stapedotomy Vertigo With Migraine Prophylactic Medication.

PubMed

Moshtaghi, Omid; Mahboubi, Hossein; Haidar, Yarah M; Sahyouni, Ronald; Lin, Harrison W; Djalilian, Hamid R

2017-12-01

To describe persistent post-stapedotomy vertigo (PSV) and its treatment using migraine prophylaxis. A retrospective review of all patients with persistent PSV spanning 10 years at a tertiary academic hospital was performed. Patients who experienced persistent vertigo for a minimum of 3 months after surgery were included. Those with possible perilymph fistula, long prosthesis, and benign paroxysmal positional vertigo were excluded. All patients received instructions on migraine dietary and lifestyle changes and Vitamin B2 and magnesium. In addition, prophylactic treatment with nortriptyline, verapamil, or a combination thereof was started. Changes in vertigo frequency was the main outcome variable. The secondary outcome variables included the time period and medications necessary to achieve symptomatic resolution. Four women and one man with an average age of 53 years were identified that met criteria for persistent PSV indicating an incidence of 0.9% at our institution. The onset of vertigo symptoms was on average 20 days postoperatively. All five patients had daily vertigo episodes and experienced complete resolution with no vertigo episodes after treatment. Symptomatic resolution was achieved over an average of 9 weeks after initiating treatments. Persistent PSV beyond 3 months is a rare occurrence and its treatment can be challenging when there is no evidence of an underlying pathology. This subset of patients may be suffering from migraine, which was triggered postoperatively. Treatment with migraine prophylaxis in this cohort of patients may result in resolution of vertigo.

Consistency of internal fluxes in a hydrological model running at multiple time steps

NASA Astrophysics Data System (ADS)

Ficchi, Andrea; Perrin, Charles; Andréassian, Vazken

2016-04-01

Improving hydrological models remains a difficult task and many ways can be explored, among which one can find the improvement of spatial representation, the search for more robust parametrization, the better formulation of some processes or the modification of model structures by trial-and-error procedure. Several past works indicate that model parameters and structure can be dependent on the modelling time step, and there is thus some rationale in investigating how a model behaves across various modelling time steps, to find solutions for improvements. Here we analyse the impact of data time step on the consistency of the internal fluxes of a rainfall-runoff model run at various time steps, by using a large data set of 240 catchments. To this end, fine time step hydro-climatic information at sub-hourly resolution is used as input of a parsimonious rainfall-runoff model (GR) that is run at eight different model time steps (from 6 minutes to one day). The initial structure of the tested model (i.e. the baseline) corresponds to the daily model GR4J (Perrin et al., 2003), adapted to be run at variable sub-daily time steps. The modelled fluxes considered are interception, actual evapotranspiration and intercatchment groundwater flows. Observations of these fluxes are not available, but the comparison of modelled fluxes at multiple time steps gives additional information for model identification. The joint analysis of flow simulation performance and consistency of internal fluxes at different time steps provides guidance to the identification of the model components that should be improved. Our analysis indicates that the baseline model structure is to be modified at sub-daily time steps to warrant the consistency and realism of the modelled fluxes. For the baseline model improvement, particular attention is devoted to the interception model component, whose output flux showed the strongest sensitivity to modelling time step. The dependency of the optimal model complexity on time step is also analysed. References: Perrin, C., Michel, C., Andréassian, V., 2003. Improvement of a parsimonious model for streamflow simulation. Journal of Hydrology, 279(1-4): 275-289. DOI:10.1016/S0022-1694(03)00225-7

Comparison of fungal spores concentrations measured with wideband integrated bioaerosol sensor and Hirst methodology

NASA Astrophysics Data System (ADS)

Fernández-Rodríguez, S.; Tormo-Molina, R.; Lemonis, N.; Clot, B.; O'Connor, D. J.; Sodeau, John R.

2018-02-01

The aim of this work was to provide both a comparison of traditional and novel methodologies for airborne spores detection (i.e. the Hirst Burkard trap and WIBS-4) and the first quantitative study of airborne fungal concentrations in Payerne (Western Switzerland) as well as their relation to meteorological parameters. From the traditional method -Hirst trap and microscope analysis-, sixty-three propagule types (spores, sporangia and hyphae) were identified and the average spore concentrations measured over the full period amounted to 4145 ± 263.0 spores/m3. Maximum values were reached on July 19th and on August 6th. Twenty-six spore types reached average levels above 10 spores/m3. Airborne fungal propagules in Payerne showed a clear seasonal pattern, increasing from low values in early spring to maxima in summer. Daily average concentrations above 5000 spores/m3 were almost constant in summer from mid-June onwards. Weather parameters showed a relevant role for determining the observed spore concentrations. Coniferous forest, dominant in the surroundings, may be a relevant source for airborne fungal propagules as their distribution and predominant wind directions are consistent with the origin. The comparison between the two methodologies used in this campaign showed remarkably consistent patterns throughout the campaign. A correlation coefficient of 0.9 (CI 0.76-0.96) was seen between the two over the time period for daily resolutions (Hirst trap and WIBS-4). This apparent co-linearity was seen to fall away once increased resolution was employed. However at higher resolutions upon removal of Cladosporium species from the total fungal concentrations (Hirst trap), an increased correlation coefficient was again noted between the two instruments (R = 0.81 with confidence intervals of 0.74 and 0.86).

Assessing Australian Rainfall Projections in Two Model Resolutions

NASA Astrophysics Data System (ADS)

Taschetto, A.; Haarsma, R. D.; Sen Gupta, A.

2016-02-01

Australian climate is projected to change with increases in greenhouse gases. The IPCC reports an increase in extreme daily rainfall across the country. At the same time, mean rainfall over southeast Australia is projected to reduce during austral winter, but to increase during austral summer, mainly associated with changes in the surrounding oceans. Climate models agree better on the future reduction of average rainfall over the southern regions of Australia compared to the increase in extreme rainfall events. One of the reasons for this disagreement may be related to climate model limitations in simulating the observed mechanisms associated with the mid-latitude weather systems, in particular due to coarse model resolutions. In this study we investigate how changes in sea surface temperature (SST) affect Australian mean and extreme rainfall under global warming, using a suite of numerical experiments at two model resolutions: about 126km (T159) and 25km (T799). The numerical experiments are performed with the earth system model EC-EARTH. Two 6-member ensembles are produced for the present day conditions and a future scenario. The present day ensemble is forced with the observed daily SST from the NOAA National Climatic Data Center from 2002 to 2006. The future scenario simulation is integrated from 2094 to 2098 using the present day SST field added onto the future SST change created from a 17-member ensemble based on the RCP4.5 scenario. Preliminary results show an increase in extreme rainfall events over Tasmania associated with enhanced convection driven by the Tasman Sea warming. We will further discuss how the projected changes in SST will impact the southern mid-latitude weather systems that ultimately affect Australian rainfall.

Examining Mars at Many Levels (Artist Concept)

NASA Image and Video Library

2005-03-23

This artist's concept represents the "Follow the Water" theme of NASA's Mars Reconnaissance Orbiter mission. The orbiter's science instruments monitor the present water cycle in the Mars atmosphere and the associated deposition and sublimation of water ice on the surface, while probing the subsurface to see how deep the water-ice reservoir detected by Mars Odyssey extends. At the same time, Mars Reconnaissance Orbiter will search for surface features and minerals (such as carbonates and sulfates) that record the extended presence of liquid water on the surface earlier in the planet's history. The instruments involved are the Shallow Subsurface Radar, the Compact Reconnaissance Imaging Spectrometer for Mars, the Mars Color Imager, the High Resolution Imaging Science Experiment, the Context Camera and the Mars Climate Sounder. To the far left, the radar antenna beams down and "sees" into the first few hundred feet (up to 1 kilometer) of Mars' crust. Just to the right of that, the next beam highlights the data received from the imaging spectrometer, which identifies minerals on the surface. The next beam represents the high-resolution camera, which can "zoom in" on local targets, providing the highest-resolution orbital images yet of features such as craters and gullies and rocks. The beam that shines almost horizontally is that of the Mars Climate Sounder. This instrument is critical to analyzing the current climate of Mars since it observes the temperature, humidity, and dust content of the martian atmosphere, and their seasonal and year-to-year variations. Meanwhile, the Mars Color Imager observes ice clouds, dust clouds and hazes, and the ozone distribution, producing daily global maps in multiple colors to monitor daily weather and seasonal changes. The electromagnetic spectrum is represented on the top right and individual instruments are placed where their capability lies. http://photojournal.jpl.nasa.gov/catalog/PIA07241

Implementation of a flow-dependent background error correlation length scale formulation in the NEMOVAR OSTIA system

NASA Astrophysics Data System (ADS)

Fiedler, Emma; Mao, Chongyuan; Good, Simon; Waters, Jennifer; Martin, Matthew

2017-04-01

OSTIA is the Met Office's Operational Sea Surface Temperature (SST) and Ice Analysis system, which produces L4 (globally complete, gridded) analyses on a daily basis. Work is currently being undertaken to replace the original OI (Optimal Interpolation) data assimilation scheme with NEMOVAR, a 3D-Var data assimilation method developed for use with the NEMO ocean model. A dual background error correlation length scale formulation is used for SST in OSTIA, as implemented in NEMOVAR. Short and long length scales are combined according to the ratio of the decomposition of the background error variances into short and long spatial correlations. The pre-defined background error variances vary spatially and seasonally, but not on shorter time-scales. If the derived length scales applied to the daily analysis are too long, SST features may be smoothed out. Therefore a flow-dependent component to determining the effective length scale has also been developed. The total horizontal gradient of the background SST field is used to identify regions where the length scale should be shortened. These methods together have led to an improvement in the resolution of SST features compared to the previous OI analysis system, without the introduction of spurious noise. This presentation will show validation results for feature resolution in OSTIA using the OI scheme, the dual length scale NEMOVAR scheme, and the flow-dependent implementation.

Satellite-based Monitoring of global Precipitation using the PERSIANN system: from Weather- to Climate-scales with some application examples

NASA Astrophysics Data System (ADS)

Switzer, A.; Yap, W.; Lauro, F.; Gouramanis, C.; Dominey-Howes, D.; Labbate, M.

2016-12-01

This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.

Satellite-based Monitoring of global Precipitation using the PERSIANN system: from Weather- to Climate-scales with some application examples

NASA Astrophysics Data System (ADS)

Sorooshian, S.; Nguyen, P.; Hsu, K. L.

2017-12-01

This presentation provides an overview of the PERSIANN precipitation products from the near real time high-resolution (4km, 30 min) PERSIANN-CCS to the most recent 34+-year PERSIANN-CDR (25km, daily). It is widely believed that the hydrologic cycle has been intensifying due to global warming and the frequency and the intensity of hydrologic extremes has also been increasing. Using the long-term historical global high resolution (daily, 0.25 degree) PERSIANN-CDR dataset covering over three decades from 1983 to the present day, we assess changes in global precipitation across different spatial scales. Our results show differences in trends, depending on which spatial scale is used, highlighting the importance of spatial scale in trend analysis. In addition, while there is an easily observable increasing global temperature trend, the global precipitation trend results created by the PERSIANN-CDR dataset used in this study are inconclusive. In addition, we use PERSIANN-CDR to assess the performance of the 32 CMIP5 models in terms of extreme precipitation indices in various continent-climate zones. The assessment can provide a guide for both model developers to target regions and processes that are not yet fully captured in certain climate types, and for climate model output users to be able to select the models and/or the study areas that may best fit their applications of interest.

Spatio-temporal trends of rainfall across Indian river basins

NASA Astrophysics Data System (ADS)

Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

2018-04-01

Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

Practical aspects of estimating energy components in rodents

PubMed Central

van Klinken, Jan B.; van den Berg, Sjoerd A. A.; van Dijk, Ko Willems

2013-01-01

Recently there has been an increasing interest in exploiting computational and statistical techniques for the purpose of component analysis of indirect calorimetry data. Using these methods it becomes possible to dissect daily energy expenditure into its components and to assess the dynamic response of the resting metabolic rate (RMR) to nutritional and pharmacological manipulations. To perform robust component analysis, however, is not straightforward and typically requires the tuning of parameters and the preprocessing of data. Moreover the degree of accuracy that can be attained by these methods depends on the configuration of the system, which must be properly taken into account when setting up experimental studies. Here, we review the methods of Kalman filtering, linear, and penalized spline regression, and minimal energy expenditure estimation in the context of component analysis and discuss their results on high resolution datasets from mice and rats. In addition, we investigate the effect of the sample time, the accuracy of the activity sensor, and the washout time of the chamber on the estimation accuracy. We found that on the high resolution data there was a strong correlation between the results of Kalman filtering and penalized spline (P-spline) regression, except for the activity respiratory quotient (RQ). For low resolution data the basal metabolic rate (BMR) and resting RQ could still be estimated accurately with P-spline regression, having a strong correlation with the high resolution estimate (R2 > 0.997; sample time of 9 min). In contrast, the thermic effect of food (TEF) and activity related energy expenditure (AEE) were more sensitive to a reduction in the sample rate (R2 > 0.97). In conclusion, for component analysis on data generated by single channel systems with continuous data acquisition both Kalman filtering and P-spline regression can be used, while for low resolution data from multichannel systems P-spline regression gives more robust results. PMID:23641217

Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data

NASA Technical Reports Server (NTRS)

Veraverbeke, Sander; Sedano, Fernando; Hook, Simon J.; Randerson, James T.; Jin, Yufang; Rogers, Brendan

2013-01-01

High temporal resolution information on burned area is a prerequisite for incorporating bottom-up estimates of wildland fire emissions in regional air transport models and for improving models of fire behavior. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the evolution of nine large wildland fires. For each fire, local input parameters for the kriging model were defined using variogram analysis. The accuracy of the kriging model was assessed using high resolution daily fire perimeter data available from the U.S. Forest Service. We also assessed the temporal reporting accuracy of the MODIS burned area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared to 33% for MCD45A1 and 53% for MCD64A1.

Sequential estimation of surface water mass changes from daily satellite gravimetry data

NASA Astrophysics Data System (ADS)

Ramillien, G. L.; Frappart, F.; Gratton, S.; Vasseur, X.

2015-03-01

We propose a recursive Kalman filtering approach to map regional spatio-temporal variations of terrestrial water mass over large continental areas, such as South America. Instead of correcting hydrology model outputs by the GRACE observations using a Kalman filter estimation strategy, regional 2-by-2 degree water mass solutions are constructed by integration of daily potential differences deduced from GRACE K-band range rate (KBRR) measurements. Recovery of regional water mass anomaly averages obtained by accumulation of information of daily noise-free simulated GRACE data shows that convergence is relatively fast and yields accurate solutions. In the case of cumulating real GRACE KBRR data contaminated by observational noise, the sequential method of step-by-step integration provides estimates of water mass variation for the period 2004-2011 by considering a set of suitable a priori error uncertainty parameters to stabilize the inversion. Spatial and temporal averages of the Kalman filter solutions over river basin surfaces are consistent with the ones computed using global monthly/10-day GRACE solutions from official providers CSR, GFZ and JPL. They are also highly correlated to in situ records of river discharges (70-95 %), especially for the Obidos station where the total outflow of the Amazon River is measured. The sparse daily coverage of the GRACE satellite tracks limits the time resolution of the regional Kalman filter solutions, and thus the detection of short-term hydrological events.

Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

Evaluating MTCLIM for incident daily solar radiation and humidity in diverse meteorological and topographical environments in the main Hawaiian Islands

NASA Astrophysics Data System (ADS)

Giambelluca, T. W.; Needham, H.; Longman, R. J.

2017-12-01

Continuous and high resolution climatologies are important inputs in determining future scenarios for land processes. In Hawaíi, a lack of continuous meteorological data has been a problem for both ecological and hydrological research of land-surface processes at daily time scales. For downward shortwave radiation (SWdown) and relative humidity (RH) climate variables, the number of surface stations which record daily values are limited and tend to be situated at city airports or in convenient locations leaving large sections of the islands underrepresented. The aim of this study is to evaluate the rationale behind using the mountain microclimate simulator MTCLIM to obtain a gridded observation based ensemble of SWdown and RH data at a daily increment for the period of 1990-2014 for the main Hawaiian Islands. Preliminary results, testing model output with observed data, show mean bias errors (%MBE) of 1.15 W/m2 for SWdown and -0.8% for RH. Mean absolute errors (%MAE) of 32.83 W/m2 SWdown and 14.96% RH, with root mean square errors (%RMSE) of 40.17 W/m2 SWdown and 11.75% RH. Further optimization of the model and additional methods to reduce errors are being investigated to improve the model's functionality with Hawaíi's extreme climate gradients.

Detecting climate variations and change: New challenges for observing and data management systems

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

Karl, T.R.; Quayle, R.G.; Groisman, P.Ya.

1993-08-01

Several essential aspects of weather observing and the management of weather data related to improving knowledge of climate variations and change in the surface boundary layer and the consequences for socioeconomic and biogeophysical systems, are discussed. The issues include long-term homogeneous time series of routine weather observations; time- and space-scale resolution of datasets derived from the observations; information about observing systems, data collection systems, and data reduction algorithms; and the enhancement of weather observing systems to serve as climate observing systems. Although much has been learned from existing weather networks and methods of data management, the system is far frommore » perfect. Several vital areas have not received adequate attention. Particular improvements are needed in the interaction between network designers and climatologists; operational analyses that focus on detecting and documenting outliers and time-dependent biases within datasets; developing the means to cope with and minimize potential inhomogeneities in weather observing systems; and authoritative documentation of how various aspects of climate have or have not changed. In this last area, close attention must be given to time and space resolution of the data. In many instances the time and space resolution requirements for understanding why the climate changes are not synonymous with understanding how it has changed or varied. This is particularly true within the surface boundary layer. A standard global daily/monthly climate message should also be introduced to supplement current Global Telecommunication System's CLIMAT data. Overall, a call is made for improvements in routine weather observing, data management, and analysis systems. Routine observations have provided (and will continue to provide) most of the information regarding how the climate has changed during the last 100 years affecting where we live, work, and grow our food. 58 refs., 8 figs., 1 tab.« less

Drivers of Intra-Summer Seasonality and Daily Variability of Coastal Low Cloudiness in California Subregions

NASA Astrophysics Data System (ADS)

Schwartz, R. E.; Iacobellis, S.; Gershunov, A.; Williams, P.; Cayan, D. R.

2014-12-01

Summertime low cloud intrusion into the terrestrial west coast of North America impacts human, ecological, and logistical systems. Over a broad region of the West Coast, summer (May - September) coastal low cloudiness (CLC) varies coherently on interannual to interdecadal timescales and has been found to be organized by North Pacific sea surface temperature. Broad-scale studies of low stratiform cloudiness over ocean basins also find that the season of maximum low stratus corresponds to the season of maximum lower tropospheric stability (LTS) or estimated inversion strength. We utilize a 18-summer record of CLC derived from NASA/NOAA Geostationary Operational Environmental Satellite (GOES) at 4km resolution over California (CA) to make a more nuanced spatial and temporal examination of intra-summer variability in CLC and its drivers. We find that uniform spatial coherency over CA is not apparent for intra-summer variability in CLC. On monthly to daily timescales, at least two distinct subregions of coastal California (CA) can be identified, where relationships between meteorology and stratus variability appear to change throughout summer in each subregion. While north of Point Conception and offshore the timing of maximum CLC is closely coincident with maximum LTS, in the Southern CA Bight and northern Baja region, maximum CLC occurs up to about a month before maximum LTS. It appears that summertime CLC in this southern region is not as strongly related as in the northern region to LTS. In particular, although the relationship is strong in May and June, starting in July the daily relationship between LTS and CLC in the south begins to deteriorate. Preliminary results indicate a moderate association between decreased CLC in the south and increased precipitable water content above 850 hPa on daily time scales beginning in July. Relationships between daily CLC variability and meteorological variables including winds, inland temperatures, relative humidity, and geopotential heights within and above the marine boundary layer are investigated and dissected by month, CA subregion, and cloud height. The rich spatial detail of the satellite derived CLC record is utilized to examine the propagation in time and space of CLC on synoptic scales within and among subregions.

Multi-site time series analysis of acute effects of multiple air pollutants on respiratory mortality: a population-based study in Beijing, China.

PubMed

Yang, Yang; Cao, Yang; Li, Wenjing; Li, Runkui; Wang, Meng; Wu, Zhenglai; Xu, Qun

2015-03-01

In large cities in China, the traffic-related air pollution has become the focus of attention, and its adverse effects on health have raised public concerns. We conducted a study to quantify the association between exposure to three major traffic-related pollutants - particulate matter < 10 μm in aerodynamic diameter (PM10), carbon monoxide (CO) and nitrogen dioxide (NO2) and the risk of respiratory mortality in Beijing, China at a daily spatiotemporal resolution. We used the generalized additive models (GAM) with natural splines and principal component regression method to associate air pollutants with daily respiratory mortality, covariates and confounders. The GAM analysis adjusting for the collinearity among pollutants indicated that PM10, CO and NO2 had significant effects on daily respiratory mortality in Beijing. An interquartile range increase in 2-day moving averages concentrations of day 0 and day 1 of PM10, CO and NO2 corresponded to 0.99 [95% confidence interval (CI): 0.30, 1.67], 0.89 (95% CI: 0.27, 1.51) and 0.95 (95% CI: 0.29, 1.61) percent increase in daily respiratory mortality, respectively. The effects were varied across the districts. The strongest effects were found in two rural districts and one suburban district but significant in only one district. In conclusion, high level of several traffic-related air pollutants is associated with an increased risk of respiratory mortality in Beijing over a short-time period. The high risk found in rural areas suggests a potential susceptible sub-population with undiagnosed respiratory diseases in these areas. Although the rural areas have relatively lower air pollution levels, they deserve more attention to respiratory disease prevention and air pollution reduction. Copyright © 2014 Elsevier B.V. All rights reserved.

Monitoring daily and sub-daily variations in crustal strain with seismic arrays

NASA Astrophysics Data System (ADS)

Mao, S.; Campillo, M.; van der Hilst, R. D.; Brenguier, F.; Hillers, G.

2017-12-01

We demonstrate that we can monitor deformation of the shallow crust (with hourly temporal resolution) directly with seismic waves, by measuring relative seismic wave speed changes (dv/v) due to relatively known periodical forcing (tides and changes in atmospheric temperature) at Piton de la Fournaise Volcano (PdF), La Réunion. We use ambient seismic noise recorded (for one month) at VolcArray, an experiment with three arrays of 49 vertical-component geophones deployed on a 7x7 grid of approximately 80 m spacing. Through noise-based coda wave interferometry we infer for each array the average relative changes in propagation speed of seismic waves (dv/v) as a function of time, which relate to temporal changes in medium properties within 100m depth. The variations in dv/v ( 0.05%) on time-scales longer than a day are best explained by effects of precipitation on pore pressure. In contrast, the (weaker) daily and sub-daily fluctuations of dv/v ( 0.01%) are likely to be caused by tidal and thermal effects. We verify that the inferred variations of dv/v are unrelated to spatiotemporal changes of noise wavefields. We further compare the power spectrum of dv/v with spectra of simulated tide-induced volumetric strain, temperature records, very broadband (VBB) seismograms, and borehole tilt records. In all five types of data, dominant peaks are found at around diurnal, semi-diurnal, and ter-diurnal frequencies. A comparison of phase and spectra of the data suggests that the tidal and thermal effects on dv/v are of similar magnitude but vary with frequency. Theoretical modeling of tide- and temperature-induced strain in different frequency bands agrees with the relative magnitude of the two effects on dv/v from passive monitoring.

Modeling clear-sky solar radiation across a range of elevations in Hawai‘i: Comparing the use of input parameters at different temporal resolutions

NASA Astrophysics Data System (ADS)

Longman, Ryan J.; Giambelluca, Thomas W.; Frazier, Abby G.

2012-01-01

Estimates of clear sky global solar irradiance using the parametric model SPCTRAL2 were tested against clear sky radiation observations at four sites in Hawai`i using daily, mean monthly, and 1 year mean model parameter settings. Atmospheric parameters in SPCTRAL2 and similar models are usually set at site-specific values and are not varied to represent the effects of fluctuating humidity, aerosol amount and type, or ozone concentration, because time-dependent atmospheric parameter estimates are not available at most sites of interest. In this study, we sought to determine the added value of using time dependent as opposed to fixed model input parameter settings. At the AERONET site, Mauna Loa Observatory (MLO) on the island of Hawai`i, where daily measurements of atmospheric optical properties and hourly solar radiation observations are available, use of daily rather than 1 year mean aerosol parameter values reduced mean bias error (MBE) from 18 to 10 W m-2 and root mean square error from 25 to 17 W m-2. At three stations in the HaleNet climate network, located at elevations of 960, 1640, and 2590 m on the island of Maui, where aerosol-related parameter settings were interpolated from observed values for AERONET sites at MLO (3397 m) and Lāna`i (20 m), and precipitable water was estimated using radiosonde-derived humidity profiles from nearby Hilo, the model performed best when using constant 1 year mean parameter values. At HaleNet Station 152, for example, MBE was 18, 10, and 8 W m-2 for daily, monthly, and 1 year mean parameters, respectively.

The osteoporotic vertebral structure is well adapted to the loads of daily life, but not to infrequent "error" loads.

PubMed

Homminga, J; Van-Rietbergen, B; Lochmüller, E M; Weinans, H; Eckstein, F; Huiskes, R

2004-03-01

Osteoporotic vertebral fractures typically have a gradual onset, frequently remain clinically undetected, and do not seem to be related to traumatic events. The osteoporotic vertebrae may therefore be expected to display a less "optimal" bone architecture, leading to an uneven load distribution over the bone material. We evaluated the trabecular load distribution in an osteoporotic and a healthy vertebra under normal daily loading by combining three recent innovations: high resolution computed tomography (microCT) of entire bones, microfinite element analyses (microFEA), and parallel supercomputers. Much to our surprise, the number of highly loaded trabeculae was not higher in the osteoporotic vertebra than in the healthy one under normal daily loads (8% and 9%, respectively). The osteoporotic trabeculae were more oriented in the longitudinal direction, compensating for effects of bone loss and ensuring adequate stiffness for normal daily loading. The increased orientation did, however, make the osteoporotic structure less resistant against collateral "error" loads. In this case, the number of overloaded trabeculae in the osteoporotic vertebra was higher than in the healthy one (13% and 4%, respectively). These results strengthen the paradigm of a strong relationship between bone morphology and external loads applied during normal daily life. They also indicate that vertebral fractures result from actions like forward flexion or lifting, loads that may not be "daily" but are normally not traumatic either. If future clinical imaging techniques would enable such high-resolution images to be obtained in vivo, the combination of microCT and microFEA would produce a powerful tool to diagnose osteoporosis.

Multitemporal MODIS-EVI relationships with precipitation and temperature at the Santa Rita Experimental Range

Treesearch

Jorry Z. U. Kaurivi; Alfredo R. Huete; Kamel Didan

2003-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides temporal enhanced vegetation index (EVI) data at 250, 500, and 1,000 m spatial resolutions that can be compared to daily, weekly, monthly, and annual weather parameters. A study was conducted at the grassland site (less than 10 percent velvet mesquite [Prosopis juliflora, var. velutina]) and the...

Mapping day-of-burning with coarse-resolution satellite fire-detection data

Treesearch

Sean A. Parks

2014-01-01

Evaluating the influence of observed daily weather on observed fire-related effects (e.g. smoke production, carbon emissions and burn severity) often involves knowing exactly what day any given area has burned. As such, several studies have used fire progression maps ­ in which the perimeter of an actively burning fire is mapped at a fairly high temporal resolution -...

A 47-Year Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges -APHRODITE project-

NASA Astrophysics Data System (ADS)

Yatagai, A. I.; Yasutomi, N.; Hamada, A.; Kamiguchi, K.; Arakawa, O.

2009-12-01

A daily gridded precipitation dataset for 1961-2007 is created by collecting rain gauge observation data across Asia through the activities of the Asian Precipitation--Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE) project. We have already released APHRODITE’s daily gridded precipitation (APHRO_V0902) product for 1961-2004 (Yatagai et al., 2009), and our number of valid stations was between 5000 and 12,000, representing 2.3 to 4.5 times the data available through the Global Telecommunication System network, which were used for most daily grid precipitation products. APHRO_V0902 is the only long-term (1961 onward) continental-scale daily product that contains a dense network of daily rain gauge data for Asia including the Himalayas and mountainous areas in the Middle East. The product has already contributed to studies such as the evaluation of Asian water resources, diagnosis of climate change, statistical downscaling, and verification of numerical model simulation and high-resolution precipitation estimates using satellites. We are currently improving quality control (QC) schemes and interpolation algorithms, and make continuous efforts in data collection. In addition, we have undertaken capacity building activities, such as training seminars by inviting researchers/programmers from some Asian meteorological organizations who provided the observation data for us. Furthermore, we feed the errata (QC) information back to the above organizations and/or data centers. The next version of the algorithm will be fixed in December 2009 (APHRO_V0912), and we will update the product up to 2007. Our progress and advantage of the next products will be shown at the AGU fall meeting in 2009.

Near Real-Time Monitoring of Global Evapotranspiration and its Application to Water Resource Management

NASA Astrophysics Data System (ADS)

Halverson, G. H.; Fisher, J.; Jewell, L. A.; Moore, G.; Verma, M.; McDonald, T.; Kim, S.; Muniz, A.

2016-12-01

Water scarcity and its impact on agriculture is a pressing world concern. At the heart of this crisis is the balance of water exchange between the land and the atmosphere. The ability to monitor evapotranspiration provides a solution by enabling sustainable irrigation practices. The Priestley-Taylor Jet Propulsion Laboratory model of evapotranspiration has been implemented to meet this need as a daily MODIS product with 1 to 5 km resolution. An automated data pipeline for this model implementation provides daily data with global coverage and near real-time latency using the Geospatial Data Abstraction Library. An interactive map providing on-demand statistical analysis enables water resource managers to monitor rates of water loss. To demonstrate the application of remotely-sensed evapotranspiration to water resource management, a partnership has been arranged with the New Mexico Office of the State Engineer (NMOSE). The online water research management tool was developed to meet the specifications of NMOSE using the Leaflet, GeoServer, and Django frameworks. NMOSE will utilize this tool to monitor drought and fire risk and manage irrigation. Through this test-case, it is hoped that real-time, user-friendly remote sensing tools will be adopted globally to make resource management decisions informed by the NASA Earth Observation System.

Continuous estimation of evapotranspiration and gross primary productivity from an Unmanned Aerial System

NASA Astrophysics Data System (ADS)

Wang, S.; Bandini, F.; Jakobsen, J.; J Zarco-Tejada, P.; Liu, X.; Haugård Olesen, D.; Ibrom, A.; Bauer-Gottwein, P.; Garcia, M.

2017-12-01

Model prediction of evapotranspiration (ET) and gross primary productivity (GPP) using optical and thermal satellite imagery is biased towards clear-sky conditions. Unmanned Aerial Systems (UAS) can collect optical and thermal signals at unprecedented very high spatial resolution (< 1 meter) under sunny and cloudy weather conditions. However, methods to obtain model outputs between image acquisitions are still needed. This study uses UAS based optical and thermal observations to continuously estimate daily ET and GPP in a Danish willow forest for an entire growing season of 2016. A hexacopter equipped with multispectral and thermal infrared cameras and a real-time kinematic Global Navigation Satellite System was used. The Normalized Differential Vegetation Index (NDVI) and the Temperature Vegetation Dryness Index (TVDI) were used as proxies for leaf area index and soil moisture conditions, respectively. To obtain continuously daily records between UAS acquisitions, UAS surface temperature was assimilated by the ensemble Kalman filter into a prognostic land surface model (Noilhan and Planton, 1989), which relies on the force-restore method, to simulate the continuous land surface temperature. NDVI was interpolated into daily time steps by the cubic spline method. Using these continuous datasets, a joint ET and GPP model, which combines the Priestley-Taylor Jet Propulsion Laboratory ET model (Fisher et al., 2008; Garcia et al., 2013) and the Light Use Efficiency GPP model (Potter et al., 1993), was applied. The simulated ET and GPP were compared with the footprint of eddy covariance observations. The simulated daily ET has a RMSE of 14.41 W•m-2 and a correlation coefficient of 0.83. The simulated daily GPP has a root mean square error (RMSE) of 1.56 g•C•m-2•d-1 and a correlation coefficient of 0.87. This study demonstrates the potential of UAS based multispectral and thermal mapping to continuously estimate ET and GPP for both sunny and cloudy weather conditions.

A multimodel intercomparison of resolution effects on precipitation: simulations and theory

DOE PAGES

Rauscher, Sara A.; O?Brien, Travis A.; Piani, Claudio; ...

2016-02-27

An ensemble of six pairs of RCM experiments performed at 25 and 50 km for the period 1961–2000 over a large European domain is examined in order to evaluate the effects of resolution on the simulation of daily precipitation statistics. Application of the non-parametric two-sample Kolmorgorov–Smirnov test, which tests for differences in the location and shape of the probability distributions of two samples, shows that the distribution of daily precipitation differs between the pairs of simulations over most land areas in both summer and winter, with the strongest signal over southern Europe. Two-dimensional histograms reveal that precipitation intensity increases with resolutionmore » over almost the entire domain in both winter and summer. In addition, the 25 km simulations have more dry days than the 50 km simulations. The increase in dry days with resolution is indicative of an improvement in model performance at higher resolution, while the more intense precipitation exceeds observed values. The systematic increase in precipitation extremes with resolution across all models suggests that this response is fundamental to model formulation. Simple theoretical arguments suggest that fluid continuity, combined with the emergent scaling properties of the horizontal wind field, results in an increase in resolved vertical transport as grid spacing decreases. This increase in resolution-dependent vertical mass flux then drives an intensification of convergence and resolvable-scale precipitation as grid spacing decreases. In conclusion, this theoretical result could help explain the increasingly, and often anomalously, large stratiform contribution to total rainfall observed with increasing resolution in many regional and global models.« less

A downscaling method for the assessment of local climate change

NASA Astrophysics Data System (ADS)

Bruno, E.; Portoghese, I.; Vurro, M.

2009-04-01

The use of complimentary models is necessary to study the impact of climate change scenarios on the hydrological response at different space-time scales. However, the structure of GCMs is such that their space resolution (hundreds of kilometres) is too coarse and not adequate to describe the variability of extreme events at basin scale (Burlando and Rosso, 2002). To bridge the space-time gap between the climate scenarios and the usual scale of the inputs for hydrological prediction models is a fundamental requisite for the evaluation of climate change impacts on water resources. Since models operate a simplification of a complex reality, their results cannot be expected to fit with climate observations. Identifying local climate scenarios for impact analysis implies the definition of more detailed local scenario by downscaling GCMs or RCMs results. Among the output correction methods we consider the statistical approach by Déqué (2007) reported as a ‘Variable correction method' in which the correction of model outputs is obtained by a function build with the observation dataset and operating a quantile-quantile transformation (Q-Q transform). However, in the case of daily precipitation fields the Q-Q transform is not able to correct the temporal property of the model output concerning the dry-wet lacunarity process. An alternative correction method is proposed based on a stochastic description of the arrival-duration-intensity processes in coherence with the Poissonian Rectangular Pulse scheme (PRP) (Eagleson, 1972). In this proposed approach, the Q-Q transform is applied to the PRP variables derived from the daily rainfall datasets. Consequently the corrected PRP parameters are used for the synthetic generation of statistically homogeneous rainfall time series that mimic the persistency of daily observations for the reference period. Then the PRP parameters are forced through the GCM scenarios to generate local scale rainfall records for the 21st century. The statistical parameters characterizing daily storm occurrence, storm intensity and duration needed to apply the PRP scheme are considered among STARDEX collection of extreme indices.

Russian eruption warning systems for aviation

USGS Publications Warehouse

Neal, C.; Girina, O.; Senyukov, S.; Rybin, A.; Osiensky, J.; Izbekov, P.; Ferguson, G.

2009-01-01

More than 65 potentially active volcanoes on the Kamchatka Peninsula and the Kurile Islands pose a substantial threat to aircraft on the Northern Pacific (NOPAC), Russian Trans-East (RTE), and Pacific Organized Track System (PACOTS) air routes. The Kamchatka Volcanic Eruption Response Team (KVERT) monitors and reports on volcanic hazards to aviation for Kamchatka and the north Kuriles. KVERT scientists utilize real-time seismic data, daily satellite views of the region, real-time video, and pilot and field reports of activity to track and alert the aviation industry of hazardous activity. Most Kurile Island volcanoes are monitored by the Sakhalin Volcanic Eruption Response Team (SVERT) based in Yuzhno-Sakhalinsk. SVERT uses daily moderate resolution imaging spectroradiometer (MODIS) satellite images to look for volcanic activity along this 1,250-km chain of islands. Neither operation is staffed 24 h per day. In addition, the vast majority of Russian volcanoes are not monitored seismically in real-time. Other challenges include multiple time-zones and language differences that hamper communication among volcanologists and meteorologists in the US, Japan, and Russia who share the responsibility to issue official warnings. Rapid, consistent verification of explosive eruptions and determination of cloud heights remain significant technical challenges. Despite these difficulties, in more than a decade of frequent eruptive activity in Kamchatka and the northern Kuriles, no damaging encounters with volcanic ash from Russian eruptions have been recorded. ?? Springer Science+Business Media B.V. 2009.

Mapping Daily and Maximum Flood Extents at 90-m Resolution During Hurricanes Harvey and Irma Using Passive Microwave Remote Sensing

NASA Astrophysics Data System (ADS)

Galantowicz, J. F.; Picton, J.; Root, B.

2017-12-01

Passive microwave remote sensing can provided a distinct perspective on flood events by virtue of wide sensor fields of view, frequent observations from multiple satellites, and sensitivity through clouds and vegetation. During Hurricanes Harvey and Irma, we used AMSR2 (Advanced Microwave Scanning Radiometer 2, JAXA) data to map flood extents starting from the first post-storm rain-free sensor passes. Our standard flood mapping algorithm (FloodScan) derives flooded fraction from 22-km microwave data (AMSR2 or NASA's GMI) in near real time and downscales it to 90-m resolution using a database built from topography, hydrology, and Global Surface Water Explorer data and normalized to microwave data footprint shapes. During Harvey and Irma we tested experimental versions of the algorithm designed to map the maximum post-storm flood extent rapidly and made a variety of map products available immediately for use in storm monitoring and response. The maps have several unique features including spanning the entire storm-affected area and providing multiple post-storm updates as flood water shifted and receded. From the daily maps we derived secondary products such as flood duration, maximum flood extent (Figure 1), and flood depth. In this presentation, we describe flood extent evolution, maximum extent, and local details as detected by the FloodScan algorithm in the wake of Harvey and Irma. We compare FloodScan results to other available flood mapping resources, note observed shortcomings, and describe improvements made in response. We also discuss how best-estimate maps could be updated in near real time by merging FloodScan products and data from other remote sensing systems and hydrological models.

Clinical outcomes and cost minimization with an alternative dosing regimen for meropenem in a community hospital.

PubMed

Patel, Gita Wasan; Duquaine, Susan M; McKinnon, Peggy S

2007-12-01

To compare outcomes and cost for the traditional United States Food and Drug Administration-approved dosing regimen for meropenem versus an alternative dosing regimen providing similar pharmacodynamic exposure with a lower total daily dose. Retrospective cohort study with a cost-minimization analysis. A 417-bed, privately owned community hospital. One hundred patients who received meropenem 1 g every 8 or 12 hours (traditional dosing regimen) between January 1 and September 30, 2004 (historical controls), and 192 patients who received meropenem 500 mg every 6 or 8 hours (alternative dosing regimen) between October 1, 2004, and September 30, 2005. Demographic and clinical data were collected for all patients. Cost-minimization analysis was performed by using the drug acquisition cost for meropenem. Demographics, sources of infection, distributions of organisms, and Charlson Comorbidity Index scores were similar between patients in the traditionally and alternatively dosed groups. Concomitant therapy, duration of therapy, success rates, lengths of stay, and in-hospital mortality rates were also similar between groups. Median time to the resolution of symptoms was 3 days for traditional dosing and 1.5 days for alternative dosing (p<0.0001). A logistic regression model including the dosing strategy showed that only polymicrobial infections and sepsis were associated with increased failure rates. The median cost for antibiotics was $439.05/patient for traditional dosing and $234.08/patient for alternative dosing (p<0.0001). An alternative dosing regimen for meropenem with a lower total daily dose yielded patient outcomes, including success rates and duration of therapy, equivalent to those of the traditional dosing regimen. Alternative dosing decreased total drug exposure, costs for antibiotics, and time to the resolution of infections.

A Phase 3, Multicenter, Randomized, Double-Blind, Vehicle-Controlled Study Evaluating the Safety and Efficacy of Metronidazole Vaginal Gel 1.3% in the Treatment of Bacterial Vaginosis.

PubMed

Schwebke, Jane R; Marrazzo, Jeanne; Beelen, Andrew P; Sobel, Jack D

2015-07-01

Bacterial vaginosis (BV), a prevalent infection in women of reproductive age, is associated with increased risk of upper genital tract and sexually transmitted infections, and complications in pregnancy. Currently approved treatments include metronidazole, which requires once or twice daily intravaginal administration for 5 days or twice daily oral administration for 7 days. This phase 3 study determined the safety and efficacy of single-dose metronidazole vaginal gel (MVG) 1.3%. In this double-blind, vehicle-controlled study, 651 women with clinical diagnosis of BV were randomized 1:1 to receive MVG 1.3% or vehicle vaginal gel. Primary efficacy measure was clinical cure (normal discharge, negative "whiff test," and <20% clue cells) at day 21. Secondary measures included therapeutic cure (both clinical and bacteriological; day 21) and bacteriologic cure (Nugent score <4), clinical cure, and time to resolution of symptoms (day 7). A total of 487 participants were included in the primary analysis. Clinical and therapeutic cure rates (day 21) were higher in participants treated with MVG 1.3% compared with vehicle gel (37.2% vs. 26.6% [P = 0.010] and 16.8% vs. 7.2% [P = 0.001], respectively). Clinical and bacteriologic cure rates (day 7) were also higher in the MVG 1.3% group (46.0% vs. 20.0% [P < 0.001] and 32.7% vs. 6.3% [P < 0.001], respectively). The median time to resolution of symptoms was shorter in the MVG 1.3% (day 6) than vehicle group (not reached). No serious adverse events were reported, and incidence was similar across treatment groups. Single-dose MVG 1.3% was safe and superior to vehicle gel in producing cure among women with BV.

Reanalysis Data Evaluation to Study Temperature Extremes in Siberia

NASA Astrophysics Data System (ADS)

Shulgina, T. M.; Gordov, E. P.

2014-12-01

Ongoing global climate changes are strongly pronounced in Siberia by significant warming in the 2nd half of 20th century and recent extreme events such as 2010 heat wave and 2013 flood in Russia's Far East. To improve our understanding of observed climate extremes and to provide to regional decision makers the reliable scientifically based information with high special and temporal resolution on climate state, we need to operate with accurate meteorological data in our study. However, from available 231 stations across Siberia only 130 of them present the homogeneous daily temperature time series. Sparse, station network, especially in high latitudes, force us to use simulated reanalysis data. However those might differ from observations. To obtain reliable information on temperature extreme "hot spots" in Siberia we have compared daily temperatures form ERA-40, ERA Interim, JRA-25, JRA-55, NCEP/DOE, MERRA Reanalysis, HadEX2 and GHCNDEX gridded datasets with observations from RIHMI-WDC/CDIAC dataset for overlap period 1981-2000. Data agreement was estimated at station coordinates to which reanalysis data were interpolated using modified Shepard method. Comparison of averaged over 20 year annual mean temperatures shows general agreement for Siberia excepting Baikal region, where reanalyses significantly underestimate observed temperature behavior. The annual temperatures closest to observed one were obtained from ERA-40 and ERA Interim. Furthermore, t-test results show homogeneity of these datasets, which allows one to combine them for long term time series analysis. In particular, we compared the combined data with observations for percentile-based extreme indices. In Western Siberia reanalysis and gridded data accurately reproduce observed daily max/min temperatures. For East Siberia, Lake Baikal area, ERA Interim data slightly underestimates TN90p and TX90p values. Results obtained allows regional decision-makers to get required high spatial resolution (0,25°×0,25°) climatic information products from the combined ERA data. The authors acknowledge partial financial support for this research from the RFBR (13-05-12034, 14-05-00502), SB RAS Integration projects (131, VIII.80.2.1.) and grant of the President of RF (№ 181).

Downscaling wind and wavefields for 21st century coastal flood hazard projections in a region of complex terrain

USGS Publications Warehouse

O'Neill, Andrea; Erikson, Li; Barnard, Patrick

2017-01-01

While global climate models (GCMs) provide useful projections of near-surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling. Statistically downscaled GCM projections from Multivariate Adaptive Constructed Analogues provide daily averaged near-surface winds at an appropriate spatial resolution for wave modeling within the orographically complex region of San Francisco Bay, but greater resolution in time is needed to capture the peak of storm events. Short-duration high wind speeds, on the order of hours, are usually excluded in statistically downscaled climate models and are of key importance in wave and subsequent coastal flood modeling. Here we present a temporal downscaling approach, similar to constructed analogues, for near-surface winds suitable for use in local wave models and evaluate changes in wind and wave conditions for the 21st century. Reconstructed hindcast winds (1975–2004) recreate important extreme wind values within San Francisco Bay. A computationally efficient method for simulating wave heights over long time periods was used to screen for extreme events. Wave hindcasts show resultant maximum wave heights of 2.2 m possible within the Bay. Changes in extreme over-water wind speeds suggest contrasting trends within the different regions of San Francisco Bay, but 21th century projections show little change in the overall magnitude of extreme winds and locally generated waves.

Recent Developments for Satellite-Based Fire Monitoring in Canada

NASA Astrophysics Data System (ADS)

Abuelgasim, A.; Fraser, R.

2002-05-01

Wildfires in Canadian forests are a major source of natural disturbance. These fires have a tremendous impact on the local environment, humans and wildlife, ecosystem function, weather, and climate. Approximately 9000 fires burn 3 million hectares per year in Canada (based on a 10-year average). While only 2 to 3 percent of these wildfires grow larger than 200 hectares in size, they account for almost 97 percent of the annual area burned. This provides an excellent opportunity to monitor active fires using a combination of low and high resolution sensors for the purpose of determining fire location and burned areas. Given the size of Canada, the use of remote sensing data is a cost-effective way to achieve a synoptic overview of large forest fire activity in near-real time. In 1998 the Canada Centre for Remote Sensing (CCRS) and the Canadian Forest Service (CFS) developed a system for Fire Monitoring, Mapping and Modelling (Fire M3;http://fms.nofc.cfs.nrcan.gc.ca/FireM3/). Fire M3 automatically identifies, monitors, and maps large forest fires on a daily basis using NOAA AVHRR data. These data are processed daily using the GEOCOMP-N satellite image processing system. This presentation will describe recent developments to Fire M3, included the addition of a set of algorithms tailored for NOAA-16 (N-16) data. The two fire detection algorithms are developed for N-16 day and night-time daily data collection. The algorithms exploit both the multi-spectral and thermal information from the AVHRR daily images. The set of N-16 day and night algorithms was used to generate daily active fire maps across North America for the 2001 fire season. Such a combined approach for fire detection leads to an improved detection rate, although day-time detection based on the new 1.6 um channel was much less effective (note - given the low detection rate with day time imagery, I don't think we can make the statement about capturing the diurnal cycle). Selected validation sites in western Canada and the United States showed reasonable correspondence with the location of fires mapped by CFS and those mapped by the USDA Forest Service using conventional means.

Long-Term Quantitative Precipitation Estimates (QPE) at High Spatial and Temporal Resolution over CONUS: Bias-Adjustment of the Radar-Only National Mosaic and Multi-sensor QPE (NMQ/Q2) Precipitation Reanalysis (2001-2012)

NASA Astrophysics Data System (ADS)

Prat, Olivier; Nelson, Brian; Stevens, Scott; Seo, Dong-Jun; Kim, Beomgeun

2015-04-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is completed for the period covering from 2001 to 2012. This important milestone constitutes a unique opportunity to study precipitation processes at a 1-km spatial resolution for a 5-min temporal resolution. However, in order to be suitable for hydrological, meteorological and climatological applications, the radar-only product needs to be bias-adjusted and merged with in-situ rain gauge information. Several in-situ datasets are available to assess the biases of the radar-only product and to adjust for those biases to provide a multi-sensor QPE. The rain gauge networks that are used such as the Global Historical Climatology Network-Daily (GHCN-D), the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), and the Climate Reference Network (CRN), have different spatial density and temporal resolution. The challenges related to incorporating non-homogeneous networks over a vast area and for a long-term record are enormous. Among the challenges we are facing are the difficulties incorporating differing resolution and quality surface measurements to adjust gridded estimates of precipitation. Another challenge is the type of adjustment technique. The objective of this work is threefold. First, we investigate how the different in-situ networks can impact the precipitation estimates as a function of the spatial density, sensor type, and temporal resolution. Second, we assess conditional and un-conditional biases of the radar-only QPE for various time scales (daily, hourly, 5-min) using in-situ precipitation observations. Finally, after assessing the bias and applying reduction or elimination techniques, we are using a unique in-situ dataset merging the different RG networks (CRN, ASOS, HADS, GHCN-D) to adjust the radar-only QPE product via an Inverse Distance Weighting (IDW) approach. In addition, we also investigate alternate adjustment techniques such as the kriging method and its variants (Simple Kriging: SK; Ordinary Kriging: OK; Conditional Bias-Penalized Kriging: CBPK). From this approach, we also hope to generate estimates of uncertainty for the gridded bias-adjusted QPE. Further comparison with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) and satellite products (TMPA, CMORPH, PERSIANN) is also provided in order to give a detailed picture of the improvements and remaining challenges.

NASA SPoRT Initialization Datasets for Local Model Runs in the Environmental Modeling System

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; LaFontaine, Frank J.; Molthan, Andrew L.; Carcione, Brian; Wood, Lance; Maloney, Joseph; Estupinan, Jeral; Medlin, Jeffrey M.; Blottman, Peter; Rozumalski, Robert A.

2011-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed several products for its National Weather Service (NWS) partners that can be used to initialize local model runs within the Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). These real-time datasets consist of surface-based information updated at least once per day, and produced in a composite or gridded product that is easily incorporated into the WRF EMS. The primary goal for making these NASA datasets available to the WRF EMS community is to provide timely and high-quality information at a spatial resolution comparable to that used in the local model configurations (i.e., convection-allowing scales). The current suite of SPoRT products supported in the WRF EMS include a Sea Surface Temperature (SST) composite, a Great Lakes sea-ice extent, a Greenness Vegetation Fraction (GVF) composite, and Land Information System (LIS) gridded output. The SPoRT SST composite is a blend of primarily the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared and Advanced Microwave Scanning Radiometer for Earth Observing System data for non-precipitation coverage over the oceans at 2-km resolution. The composite includes a special lake surface temperature analysis over the Great Lakes using contributions from the Remote Sensing Systems temperature data. The Great Lakes Environmental Research Laboratory Ice Percentage product is used to create a sea-ice mask in the SPoRT SST composite. The sea-ice mask is produced daily (in-season) at 1.8-km resolution and identifies ice percentage from 0 100% in 10% increments, with values above 90% flagged as ice.

Drive for thinness, affect regulation and physical activity in eating disorders: a daily life study.

PubMed

Vansteelandt, Kristof; Rijmen, Frank; Pieters, Guido; Probst, Michel; Vanderlinden, Johan

2007-08-01

Using Ecological Momentary Assessment, the within patient associations between drive for thinness, emotional states, momentary urge to be physically active and physical activity were studied in 32 inpatients with an eating disorder. Participants received an electronic device and had to indicate at nine random times a day during 1 week their momentary drive for thinness, positive and negative emotional states and their urge to be physically active and physical activity. Multilevel analyses indicated that patients with higher mean levels for urge to be physically active were characterized by lower body mass index (BMI) and chronically negative affect whereas patients with higher mean levels for physical activity were characterized by lower BMI and higher dispositions for drive for thinness. In addition, within patient relations between drive for thinness and urge to be physically active were moderated by BMI and chronically negative affect whereas within patient relations between drive for thinness and physical activity were moderated by BMI. Finally, also positive emotional states were significantly associated with physical activity within patients. By using a daily process design, characteristics of physical activity were revealed that have not been identified with assessment methods that have a lower time resolution.

Using High-Resolution Satellite Aerosol Optical Depth To Estimate Daily PM2.5 Geographical Distribution in Mexico City.

PubMed

Just, Allan C; Wright, Robert O; Schwartz, Joel; Coull, Brent A; Baccarelli, Andrea A; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

2015-07-21

Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most U.S. and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004-2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross-validation R(2) of 0.724. Cross-validated root-mean-squared prediction error (RMSPE) of the model was 5.55 μg/m(3). This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City.

Using high-resolution satellite aerosol optical depth to estimate daily PM2.5 geographical distribution in Mexico City

PubMed Central

Just, Allan C.; Wright, Robert O.; Schwartz, Joel; Coull, Brent A.; Baccarelli, Andrea A.; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

2015-01-01

Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most US and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004–2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross validation R2 of 0.724. Cross-validated root mean squared prediction error (RMSPE) of the model was 5.55 μg/m3. This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City. PMID:26061488

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

Thorne, N; Kassaee, A

Purpose: To develop an algorithm which can calculate the Full Width Half Maximum (FWHM) of a Proton Pencil Beam from a 2D dimensional ion chamber array (IBA Matrixx) with limited spatial resolution ( 7.6 mm inter chamber distance). The algorithm would allow beam FWHM measurements to be taken during daily QA without an appreciable time increase. Methods: Combinations of 147 MeV single spot beams were delivered onto an IBA Matrixx and concurrently on EBT3 films for a standard. Data were collected around the Bragg Peak region and evaluated by a custom MATLAB script based on our algorithm using a leastmore » squared analysis. A set of artificial data, modified with random noise, was also processed to test for robustness. Results: The Matlab script processed Matixx data shows acceptable agreement (within 5%) with film measurements with no single measurement differing by more than 1.8 mm. In cases where the spots show some degree of asymmetry, the algorithm is able to resolve the differences. The algorithm was able to process artificial data with noise up to 15% of the maximum value. Time assays of each measurement took less than 3 minutes to perform, indicating that such measurements may be efficiently added to daily QA treatment. Conclusion: The developed algorithm can be implemented in daily QA program for Proton Pencil Beam scanning beams (PBS) with Matrixx to extract spot size and position information. The developed algorithm may be extended to small field sizes in photon clinic.« less

Ocean Color and Earth Science Data Records

NASA Astrophysics Data System (ADS)

Maritorena, S.

2014-12-01

The development of consistent, high quality time series of biogeochemical products from a single ocean color sensor is a difficult task that involves many aspects related to pre- and post-launch instrument calibration and characterization, stability monitoring and the removal of the contribution of the atmosphere which represents most of the signal measured at the sensor. It is even more challenging to build Climate Data Records (CDRs) or Earth Science Data Records (ESDRs) from multiple sensors as design, technology and methodologies (bands, spectral/spatial resolution, Cal/Val, algorithms) differ from sensor to sensor. NASA MEaSUREs, ESA Climate Change Initiative (CCI) and IOCCG Virtual Constellation are some of the underway efforts that investigate or produce ocean color CDRs or ESDRs from the recent and current global missions (SeaWiFS, MODIS, MERIS). These studies look at key aspects of the development of unified data records from multiple sensors, e.g. the concatenation of the "best" individual records vs. the merging of multiple records or band homogenization vs. spectral diversity. The pros and cons of the different approaches are closely dependent upon the overall science purpose of the data record and its temporal resolution. While monthly data are generally adequate for biogeochemical modeling or to assess decadal trends, higher temporal resolution data records are required to look into changes in phenology or the dynamics of phytoplankton blooms. Similarly, short temporal resolution (daily to weekly) time series may benefit more from being built through the merging of data from multiple sensors while a simple concatenation of data from individual sensors might be better suited for longer temporal resolution (e.g. monthly time series). Several Ocean Color ESDRs were developed as part of the NASA MEaSUREs project. Some of these time series are built by merging the reflectance data from SeaWiFS, MODIS-Aqua and Envisat-MERIS in a semi-analytical ocean color model that generates both merged reflectance and merged biogeochemical products. The benefits and limitations of this merging approach to develop ESDRs will be presented and discussed along with those of alternative approaches.

Hydrochemical processes in lowland rivers: insights from in situ, high-resolution monitoring

NASA Astrophysics Data System (ADS)

Wade, A. J.; Palmer-Felgate, E. J.; Halliday, S. J.; Skeffington, R. A.; Loewenthal, M.; Jarvie, H. P.; Bowes, M. J.; Greenway, G. M.; Haswell, S. J.; Bell, I. M.; Joly, E.; Fallatah, A.; Neal, C.; Williams, R. J.; Gozzard, E.; Newman, J. R.

2012-11-01

This paper introduces new insights into the hydrochemical functioning of lowland river systems using field-based spectrophotometric and electrode technologies. The streamwater concentrations of nitrogen species and phosphorus fractions were measured at hourly intervals on a continuous basis at two contrasting sites on tributaries of the River Thames - one draining a rural catchment, the River Enborne, and one draining a more urban system, The Cut. The measurements complement those from an existing network of multi-parameter water quality sondes maintained across the Thames catchment and weekly monitoring based on grab samples. The results of the sub-daily monitoring show that streamwater phosphorus concentrations display highly complex dynamics under storm conditions dependent on the antecedent catchment wetness, and that diurnal phosphorus and nitrogen cycles occur under low flow conditions. The diurnal patterns highlight the dominance of sewage inputs in controlling the streamwater phosphorus and nitrogen concentrations at low flows, even at a distance of 7 km from the nearest sewage treatment works in the rural River Enborne. The time of sample collection is important when judging water quality against ecological thresholds or standards. An exhaustion of the supply of phosphorus from diffuse and multiple septic tank sources during storm events was evident and load estimation was not improved by sub-daily monitoring beyond that achieved by daily sampling because of the eventual reduction in the phosphorus mass entering the stream during events. The results highlight the utility of sub-daily water quality measurements and the discussion considers the practicalities and challenges of in situ, sub-daily monitoring.

33 Years of Near-Global Daily Precipitation from Multisatellite Observations and its Application to Drought Monitoring

NASA Astrophysics Data System (ADS)

Ashouri, H.; Hsu, K.; Sorooshian, S.; Braithwaite, D.; Knapp, K. R.; Cecil, L. D.

2013-12-01

PERSIANN Climate Data Record (PERSIANN-CDR) is a new retrospective satellite-based precipitation data set that is constructed for long-term hydrological and climate studies. The PERSIANN-CDR is a near-global (60°S-60°N) long-term (1980-2012), multi-satellite, high-resolution precipitation product that provides rain rate estimates at 0.25° and daily spatiotemporal resolution. PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high resolution precipitation data set for studying the spatial and temporal variations and changes of precipitation patterns, particularly in a scale relevant to climate extremes at the global scale. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data from the International Satellite Cloud Climatology Project (ISCCP). PERSIANN-CDR is adjusted using the Global Precipitation Climatology Project (GPCP) monthly precipitation to maintain consistency of two data sets at 2.5° monthly scale throughout the entire reconstruction period. PERSIANN-CDR daily precipitation data demonstrates considerable consistency with both GPCP monthly and GPCP 1DD precipitation products. Verification studies over Hurricane Katrina show that PERSIANN-CDR has a good agreement with NCEP Stage IV radar data, noting that PERSIANN-CDR has better spatial coverage. In addition, the Probability Density Function (PDF) of PERSIANN-CDR over the contiguous United States was compared with the PDFs extracted from CPC gauge data and the TMPA precipitation product. The experiment also shows good agreement of the PDF of PERSIANN-CDR with the PDFs of TMPA and CPC gauge data. The application of PERSIANN-CDR in regional and global drought monitoring is investigated. Consisting of more than three decades of high-resolution precipitation data, PERSIANN-CDR makes us capable of long-term assessment of droughts at a higher resolution (0.25°) than previously possible. The results will be presented at the meeting.

Daily Estimation of High Resolution PM2.5 Concentrations over BTH area by Fusing MODIS AOD and Ground Observations

NASA Astrophysics Data System (ADS)

Lyu, Baolei; Hu, Yongtao; Chang, Howard; Russell, Armistead; Bai, Yuqi

2017-04-01

The satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) is often used to predict ground-level fine particulate matter (PM2.5) concentrations. The associated estimation accuracy is always reduced by AOD missing values and by insufficiently accounting for the spatio-temporal PM2.5 variations. This study aims to estimate PM2.5 concentrations at a high resolution with enhanced accuracy by fusing MODIS AOD and ground observations in the polluted and populated Beijing-Tianjin-Hebei (BTH) area of China in 2014 and 2015. A Bayesian-based statistical downscaler was employed to model the spatio-temporally varied AOD-PM2.5 relationships. We resampled a 3 km MODIS AOD product to a 4 km resolution in a Lambert conic conformal projection, to assist comparison and fusion with CMAQ predictions. A two-step method was used to fill the missing AOD values to obtain a full AOD dataset with complete spatial coverage. The downscaler has a relatively good performance in the fitting procedure (R2 = 0.75) and in the cross validation procedure (with two evaluation methods, R2 = 0.58 by random method and R2 = 0.47 by city-specific method). The number of missing AOD values was serious and related to elevated PM2.5 concentrations. The gap-filled AOD values corresponded well with our understanding of PM2.5 pollution conditions in BTH. The prediction accuracy of PM2.5 concentrations were improved in terms of their annual and seasonal mean. As a result of its fine spatio-temporal resolution and complete spatial coverage, the daily PM2.5 estimation dataset could provide extensive and insightful benefits to related studies in the BTH area. This may include understanding the formation processes of regional PM2.5 pollution episodes, evaluating daily human exposure, and establishing pollution controlling measures.

Worldwide impact of aerosol's time scale on the predicted long-term concentrating solar power potential.

PubMed

Ruiz-Arias, Jose A; Gueymard, Christian A; Santos-Alamillos, Francisco J; Pozo-Vázquez, David

2016-08-10

Concentrating solar technologies, which are fuelled by the direct normal component of solar irradiance (DNI), are among the most promising solar technologies. Currently, the state-of the-art methods for DNI evaluation use datasets of aerosol optical depth (AOD) with only coarse (typically monthly) temporal resolution. Using daily AOD data from both site-specific observations at ground stations as well as gridded model estimates, a methodology is developed to evaluate how the calculated long-term DNI resource is affected by using AOD data averaged over periods from 1 to 30 days. It is demonstrated here that the use of monthly representations of AOD leads to systematic underestimations of the predicted long-term DNI up to 10% in some areas with high solar resource, which may result in detrimental consequences for the bankability of concentrating solar power projects. Recommendations for the use of either daily or monthly AOD data are provided on a geographical basis.

The benefits of daily data and scale up issues in hydrologic models-SWAT and CRAFT

NASA Astrophysics Data System (ADS)

Huang, Yumei; Quinn, Paul; Liang, Qiuhua; Adams, Russell

2017-04-01

When modelling the flow pathways for nutrient transport, the lack of good data and limitation of data resolution become the key cause of low quality output in various hydrologic models. The scale of catchment being studied would present the main issues of the sensitivity and uncertainty expected on the hydrologic modelling. Equally, the time step chosen is also important to nutrient dynamics. This study aims to evaluate the benefits of using both monthly and daily data in hydrologic models, and to address the issues of catchment scale when using the two hydrologic models, the Soil and Water Assessment Tool (SWAT), and Catchment Runoff Attenuation Flux Tool (CRAFT), by comparing the difference between SWAT and CRAFT in flow pathways and sediment transport. The models are different in terms of complexity, therefore the poster will discuss the strengths and weakness of the models. Also we can show the problems of calibration and how the models can be used to support catchment modelling.

Worldwide impact of aerosol’s time scale on the predicted long-term concentrating solar power potential

PubMed Central

Ruiz-Arias, Jose A.; Gueymard, Christian A.; Santos-Alamillos, Francisco J.; Pozo-Vázquez, David

2016-01-01

Concentrating solar technologies, which are fuelled by the direct normal component of solar irradiance (DNI), are among the most promising solar technologies. Currently, the state-of the-art methods for DNI evaluation use datasets of aerosol optical depth (AOD) with only coarse (typically monthly) temporal resolution. Using daily AOD data from both site-specific observations at ground stations as well as gridded model estimates, a methodology is developed to evaluate how the calculated long-term DNI resource is affected by using AOD data averaged over periods from 1 to 30 days. It is demonstrated here that the use of monthly representations of AOD leads to systematic underestimations of the predicted long-term DNI up to 10% in some areas with high solar resource, which may result in detrimental consequences for the bankability of concentrating solar power projects. Recommendations for the use of either daily or monthly AOD data are provided on a geographical basis. PMID:27507711

Daily temperature and precipitation extremes in the Baltic Sea region derived from the BaltAn65+ reanalysis

NASA Astrophysics Data System (ADS)

Toll, Velle; Post, Piia

2018-04-01

Daily 2-m temperature and precipitation extremes in the Baltic Sea region for the time period of 1965-2005 is studied based on data from the BaltAn65 + high resolution atmospheric reanalysis. Moreover, the ability of regional reanalysis to capture extremes is analysed by comparing the reanalysis data to gridded observations. The shortcomings in the simulation of the minimum temperatures over the northern part of the region and in the simulation of the extreme precipitation over the Scandinavian mountains in the BaltAn65+ reanalysis data are detected and analysed. Temporal trends in the temperature and precipitation extremes in the Baltic Sea region, with the largest increases in temperature and precipitation in winter, are detected based on both gridded observations and the BaltAn65+ reanalysis data. However, the reanalysis is not able to capture all of the regional trends in the extremes in the observations due to the shortcomings in the simulation of the extremes.

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation.

Treesearch

David P. Turner; William D. Ritts; Warren B. Cohen; Stith T. Gower; Maosheng Zhao; Steve W. Running; Steven C. Wofsy; Shawn Urbanski; Allison L. Dunn; J.W. Munger

2003-01-01

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using...

Development of high-resolution (250 m) historical daily gridded air temperature data using reanalysis and distributed sensor networks for the US northern Rocky Mountains

Treesearch

Zachary A. Holden; Alan Swanson; Anna E. Klene; John T. Abatzoglou; Solomon Z. Dobrowski; Samuel A. Cushman; John Squires; Gretchen G. Moisen; Jared W. Oyler

2016-01-01

Gridded temperature data sets are typically produced at spatial resolutions that cannot fully resolve fine-scale variation in surface air temperature in regions of complex topography. These data limitations have become increasingly important as scientists and managers attempt to understand and plan for potential climate change impacts. Here, we describe the...

Relationship between passive microwave-derived snowmelt and surface-measured discharge, Wheaton River, Yukon Territory, Canada

NASA Astrophysics Data System (ADS)

Ramage, J. M.; McKenney, R. A.; Thorson, B.; Maltais, P.; Kopczynski, S. E.

2006-03-01

Snow volume and melt timing are major factors influencing the water cycle at northern high altitudes and latitudes, yet both are hard to quantify or monitor in remote mountainous regions. Twice-daily special sensor microwave imager (SSM/I) passive microwave observations of seasonal snow melt onset in the Wheaton River basin, Yukon Territory, Canada (60 ° 0805N, 134 ° 5345W), are used to test the idea that melt onset date and duration of snowpack melt-refreeze fluctuations control the timing of the early hydrograph peaks with predictable lags. This work uses the SSM/I satellite data from 1988 to 2002 to evaluate the chronology of melt and runoff patterns in the upper Yukon River basin. The Wheaton River is a small (875 km2) tributary to the Yukon, and is a subarctic, partly glacierized heterogeneous basin with near-continuous hydrographic records dating back to 1966. SSM/I pixels are sensitive to melt onset due to the strong increase in snow emissivity, and have a robust signal, in spite of coarse (>25 × 25 km2) pixel resolution and varied terrain. Results show that Wheaton River peak flows closely follow the end of large daily variations in brightness temperature of pixels covering the Wheaton River, but the magnitude of flow is highly variable, as might be expected from interannual snow mass variability. Spring rise in the hydrograph follows the end of high diurnal brightness temperature (Tb) amplitude variations (DAV) by 0 to 5 days approximately 90% of the time for this basin. Subsequent work will compare these findings for a larger (7250 km2), unglacierized tributary, the Ross River, which is farther northeast (61 ° 5940N, 132 ° 2240W) in the Yukon Territory. These techniques will also be used to try to determine the improvement in melt detection and runoff prediction from the higher resolution (15 × 15 km2) advanced microwave scanning radiometer for EOS (AMSR-E) sensor.

Performance and Quality Assessment of the Forthcoming Copernicus Marine Service Global Ocean Monitoring and Forecasting Real-Time System

NASA Astrophysics Data System (ADS)

Lellouche, J. M.; Le Galloudec, O.; Greiner, E.; Garric, G.; Regnier, C.; Drillet, Y.

2016-02-01

Mercator Ocean currently delivers in real-time daily services (weekly analyses and daily forecast) with a global 1/12° high resolution system. The model component is the NEMO platform driven at the surface by the IFS ECMWF atmospheric analyses and forecasts. Observations are assimilated by means of a reduced-order Kalman filter with a 3D multivariate modal decomposition of the forecast error. It includes an adaptive-error estimate and a localization algorithm. Along track altimeter data, satellite Sea Surface Temperature and in situ temperature and salinity vertical profiles are jointly assimilated to estimate the initial conditions for numerical ocean forecasting. A 3D-Var scheme provides a correction for the slowly-evolving large-scale biases in temperature and salinity.Since May 2015, Mercator Ocean opened the Copernicus Marine Service (CMS) and is in charge of the global ocean analyses and forecast, at eddy resolving resolution. In this context, R&D activities have been conducted at Mercator Ocean these last years in order to improve the real-time 1/12° global system for the next CMS version in 2016. The ocean/sea-ice model and the assimilation scheme benefit among others from the following improvements: large-scale and objective correction of atmospheric quantities with satellite data, new Mean Dynamic Topography taking into account the last version of GOCE geoid, new adaptive tuning of some observational errors, new Quality Control on the assimilated temperature and salinity vertical profiles based on dynamic height criteria, assimilation of satellite sea-ice concentration, new freshwater runoff from ice sheets melting …This presentation doesn't focus on the impact of each update, but rather on the overall behavior of the system integrating all updates. This assessment reports on the products quality improvements, highlighting the level of performance and the reliability of the new system.

Diagnostic and functional structure of a high-resolution thyroid nodule clinic.

PubMed

Fernández-García, José Carlos; Mancha-Doblas, Isabel; Ortega-Jiménez, María Victoria; Ruiz-Escalante, José Francisco; Castells-Fusté, Ignasi; Tofé-Povedano, Santiago; Argüelles-Jiménez, Iñaki; Tinahones, Francisco José

2014-01-01

Appearance of a thyroid nodule has become a daily occurrence in clinical practice. Adequate thyroid nodule assessment requires several diagnostic tests and multiple medical appointments, which results in a substantial delay in diagnosis. Implementation of a high-resolution thyroid nodule clinic largely avoids these drawbacks by condensing in a single appointment all tests required for adequate evaluation of thyroid nodule. This paper reviews the diagnostic and functional structure of a high-resolution thyroid nodule clinic. Copyright © 2013 SEEN. Published by Elsevier Espana. All rights reserved.

A data centred method to estimate and map how the local distribution of daily precipitation is changing

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nick

2014-05-01

Estimates of how our climate is changing are needed locally in order to inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles in distributions of variables such as daily temperature or precipitation. Here we focus on these local changes and on a method to transform daily observations of precipitation into patterns of local climate change. We develop a method[1] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes, to specifically address the challenges presented by daily precipitation data. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the relative amount of precipitation in those days. Our method is a simple mathematical deconstruction of how the difference between two observations from two different time periods can be assigned to the combination of natural statistical variability and/or the consequences of secular climate change. This deconstruction facilitates an assessment of how fast different quantiles of precipitation distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily precipitation from specific locations across Europe over the last 60 years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the pattern of change at a given threshold of precipitation and with geographical location. This is model- independent, thus providing data of direct value in model calibration and assessment. Our results show regionally consistent patterns of systematic increase in precipitation on the wettest days, and of drying across all days which is of potential value in adaptation planning. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, 2013, S. C. Chapman, N. W. Watkins, Mapping climate change in European temperature distributions, Environ. Res. Lett. 8, 034031 [2] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119

The effects of employment status and daily stressors on time spent on daily household chores in middle-aged and older adults.

PubMed

Wong, Jen D; Almeida, David M

2013-02-01

This study examines how employment status (worker vs. retiree) and life course influences (age, gender, and marital status) are associated with time spent on daily household chores. Second, this study assesses whether the associations between daily stressors and time spent on daily household chores differ as a function of employment status and life course influences. Men and women aged 55-74 from the National Study of Daily Experiences (N = 268; 133 workers and 135 retirees), a part of the National Survey of Midlife in the United States (MIDUS), completed telephone interviews regarding their daily experiences across 8 consecutive evenings. Working women spent more than double the amount of time on daily household chores than working men. Unmarried retirees spent the most time on daily household chores in comparison to their counterparts. There was a trend toward significance for the association between home stressors from the previous day and time spent on daily household chores as a function of employment and marital status. These findings highlight the importance of gender and marital status in the associations between employment status and time spent on daily household chores and the role that daily stressors, in particular home stressful events, have on daily household chore participation.

Seasonal and high-resolution variability in hydrochemistry of the Andes-Amazon

NASA Astrophysics Data System (ADS)

Burt, E.; West, A. J.

2017-12-01

Stream hydrochemistry acts as a record of integrated catchment processes such as the amount of time it takes precipitation to flow through the subsurface and become streamflow (water transit times), water-rock interaction and biogeochemical cycling. Although it is understood that sampling interval affects observed patterns in hydrochemistry, most studies collect samples on a weekly, bi-weekly or monthly schedule due to lack of resources or the difficulty of maintaining automated sampling devices. Here, we attempt to combine information from two sampling time scales, comparing a year-long hydrochemical time series to data from a recent sub-daily sampling campaign. Starting in April 2016, river, soil and rain waters have been collected every two weeks at five small catchments spanning the tropical Andes and Amazon - a natural laboratory for its gradients in topography, erosion rates, precipitation, temperature and flora. Between January and March, 2017, we conducted high frequency sampling for approximately one week at each catchment, sampling at least every four hours including overnight. We will constrain young water fractions (Kirchner, 2016) and storm water fluxes for the experimental catchments using stable isotopes of water as conservative tracers. Major element data will provide the opportunity to make initial constraints on geochemical and hydrologic coupling. Preliminary results suggest that in the Amazon, hydrochemistry patterns are dependent on sampling frequency: the seasonal cycle in stable isotopes of water is highly damped, while the high resolution sampling displays large variability. This suggests that a two-week sampling interval is not frequent enough to capture rapid transport of water, perhaps through preferential flow networks. In the Andes, stable isotopes of water are highly damped in both the seasonal and high resolution cycle, suggesting that the catchment behaves as a "well-mixed" system.

Environmental Factors Affecting Asthma and Allergies: Predicting and Simulating Downwind Exposure to Airborne Pollen

NASA Technical Reports Server (NTRS)

Luvall, Jeffrey; Estes, Sue; Sprigg, William A.; Nickovic, Slobodan; Huete, Alfredo; Solano, Ramon; Ratana, Piyachat; Jiang, Zhangyan; Flowers, Len; Zelicoff, Alan

2009-01-01

This slide presentation reviews the environmental factors that affect asthma and allergies and work to predict and simulate the downwind exposure to airborne pollen. Using a modification of Dust REgional Atmosphere Model (DREAM) that incorporates phenology (i.e. PREAM) the aim was to predict concentrations of pollen in time and space. The strategy for using the model to simulate downwind pollen dispersal, and evaluate the results. Using MODerate-resolution Imaging Spectroradiometer (MODIS), to get seasonal sampling of Juniper, the pollen chosen for the study, land cover on a near daily basis. The results of the model are reviewed.

The Ozone Monitoring Instrument: overview of 14 years in space

NASA Astrophysics Data System (ADS)

Levelt, Pieternel F.; Joiner, Joanna; Tamminen, Johanna; Pepijn Veefkind, J.; Bhartia, Pawan K.; Stein Zweers, Deborah C.; Duncan, Bryan N.; Streets, David G.; Eskes, Henk; van der A, Ronald; McLinden, Chris; Fioletov, Vitali; Carn, Simon; de Laat, Jos; DeLand, Matthew; Marchenko, Sergey; McPeters, Richard; Ziemke, Jerald; Fu, Dejian; Liu, Xiong; Pickering, Kenneth; Apituley, Arnoud; González Abad, Gonzalo; Arola, Antti; Boersma, Folkert; Miller, Christopher Chan; Chance, Kelly; de Graaf, Martin; Hakkarainen, Janne; Hassinen, Seppo; Ialongo, Iolanda; Kleipool, Quintus; Krotkov, Nickolay; Li, Can; Lamsal, Lok; Newman, Paul; Nowlan, Caroline; Suleiman, Raid; Gijsbert Tilstra, Lieuwe; Torres, Omar; Wang, Huiqun; Wargan, Krzysztof

2018-04-01

This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain.

The Ozone Monitoring Instrument: overview of 14 years in space

NASA Technical Reports Server (NTRS)

Tamminen, Johanna; Veefkind, J. Pepijn; van der A, Ronald; Miller, Christopher Chan; Ialongo, Iolanda; Kleipool, Quintus; Lamsal, Lok N.; Wang, Huiqun; Bhartia, Pawan K.; Zweers, Deborah C. Stein;

Estimation of daily maximum and minimum air temperatures in urban landscapes using MODIS time series satellite data

NASA Astrophysics Data System (ADS)

Yoo, Cheolhee; Im, Jungho; Park, Seonyoung; Quackenbush, Lindi J.

2018-03-01

Urban air temperature is considered a significant variable for a variety of urban issues, and analyzing the spatial patterns of air temperature is important for urban planning and management. However, insufficient weather stations limit accurate spatial representation of temperature within a heterogeneous city. This study used a random forest machine learning approach to estimate daily maximum and minimum air temperatures (Tmax and Tmin) for two megacities with different climate characteristics: Los Angeles, USA, and Seoul, South Korea. This study used eight time-series land surface temperature (LST) data from Moderate Resolution Imaging Spectroradiometer (MODIS), with seven auxiliary variables: elevation, solar radiation, normalized difference vegetation index, latitude, longitude, aspect, and the percentage of impervious area. We found different relationships between the eight time-series LSTs with Tmax/Tmin for the two cities, and designed eight schemes with different input LST variables. The schemes were evaluated using the coefficient of determination (R2) and Root Mean Square Error (RMSE) from 10-fold cross-validation. The best schemes produced R2 of 0.850 and 0.777 and RMSE of 1.7 °C and 1.2 °C for Tmax and Tmin in Los Angeles, and R2 of 0.728 and 0.767 and RMSE of 1.1 °C and 1.2 °C for Tmax and Tmin in Seoul, respectively. LSTs obtained the day before were crucial for estimating daily urban air temperature. Estimated air temperature patterns showed that Tmax was highly dependent on the geographic factors (e.g., sea breeze, mountains) of the two cities, while Tmin showed marginally distinct temperature differences between built-up and vegetated areas in the two cities.

Time Series Analysis of Subsidence and Water-Level Data for Aquifer System Characterization

NASA Astrophysics Data System (ADS)

Burbey, T. J.

2012-12-01

The accessibility of high resolution surface displacement data in the form of InSAR, PS-InSAR, GPS, and extensometer data in heavily pumped basins provides diagnostic information that can be used in powerful ways to characterize the hydraulic properties of both confining units and aquifers that water-level data alone cannot accomplish. Land surface deformation signals reflect the elastic and inelastic properties of the heterogeneous aquifer system. These deformation signals can be quite complex and coupled with water level data often exhibit temporal signals at daily, seasonal, and decadal scales resulting from accompanying cyclical pumping patterns. In Las Vegas Valley, for example, cyclical seasonal and daily water-level fluctuations are superimposed on long-term water-level declines. The resulting changes in effective stress have resulted in decades of inelastic land surface lowering with superimposed seasonal elastic deformation signals. In this investigation signal processing of both water level and deformation data was done to filter separate signals at daily, seasonal, and decadal time scales that can be individually evaluated to more accurately estimate the hydraulic properties of the principle aquifer system in the valley that consists of multiple aquifers and confining units. Both elastic and inelastic skeletal specific storage, the horizontal hydraulic conductivity of the aquifers, and the vertical hydraulic conductivity of the confining units can be readily evaluated in this manner. The results compare favorably with the parameters calculated from a complex one-dimensional numerical compaction model. The advantage of the time series approach is that a more thorough description of the system can be made and the analytical approach is far simpler than constructing and calibrating a numerical model.

Network Diversity and Affect Dynamics: The Role of Personality Traits

PubMed Central

Alshamsi, Aamena; Pianesi, Fabio; Lepri, Bruno; Pentland, Alex; Rahwan, Iyad

2016-01-01

People divide their time unequally among their social contacts due to time constraints and varying strength of relationships. It was found that high diversity of social communication, dividing time more evenly among social contacts, is correlated with economic well-being both at macro and micro levels. Besides economic well-being, it is not clear how the diversity of social communication is also associated with the two components of individuals’ subjective well-being, positive and negative affect. Specifically, positive affect and negative affect are two independent dimensions representing the experience (feeling) of emotions. In this paper, we investigate the relationship between the daily diversity of social communication and dynamic affect states that people experience in their daily lives. We collected two high-resolution datasets that capture affect scores via daily experience sampling surveys and social interaction through wearable sensing technologies: sociometric badges for face-to-face interaction and smart phones for mobile phone calls. We found that communication diversity correlates with desirable affect states–e.g. an increase in the positive affect state or a decrease in the negative affect state–for some personality types, but correlates with undesirable affect states for others. For example, diversity in phone calls is experienced as good by introverts, but bad by extroverts; diversity in face-to-face interaction is experienced as good by people who tend to be positive by nature (trait) but bad for people who tend to be not positive by nature. More broadly, the moderating effect of personality type on the relationship between diversity and affect was detected without any knowledge of the type of social tie or the content of communication. This provides further support for the power of unobtrusive sensing in understanding social dynamics, and in measuring the effect of potential interventions designed to improve well-being. PMID:27035904

Network Diversity and Affect Dynamics: The Role of Personality Traits.

PubMed

Alshamsi, Aamena; Pianesi, Fabio; Lepri, Bruno; Pentland, Alex; Rahwan, Iyad

2016-01-01

People divide their time unequally among their social contacts due to time constraints and varying strength of relationships. It was found that high diversity of social communication, dividing time more evenly among social contacts, is correlated with economic well-being both at macro and micro levels. Besides economic well-being, it is not clear how the diversity of social communication is also associated with the two components of individuals' subjective well-being, positive and negative affect. Specifically, positive affect and negative affect are two independent dimensions representing the experience (feeling) of emotions. In this paper, we investigate the relationship between the daily diversity of social communication and dynamic affect states that people experience in their daily lives. We collected two high-resolution datasets that capture affect scores via daily experience sampling surveys and social interaction through wearable sensing technologies: sociometric badges for face-to-face interaction and smart phones for mobile phone calls. We found that communication diversity correlates with desirable affect states--e.g. an increase in the positive affect state or a decrease in the negative affect state--for some personality types, but correlates with undesirable affect states for others. For example, diversity in phone calls is experienced as good by introverts, but bad by extroverts; diversity in face-to-face interaction is experienced as good by people who tend to be positive by nature (trait) but bad for people who tend to be not positive by nature. More broadly, the moderating effect of personality type on the relationship between diversity and affect was detected without any knowledge of the type of social tie or the content of communication. This provides further support for the power of unobtrusive sensing in understanding social dynamics, and in measuring the effect of potential interventions designed to improve well-being.

Global surface density of water mass variations by using a two-step inversion by cumulating daily satellite gravity information

NASA Astrophysics Data System (ADS)

Ramillien, Guillaume; Frappart, Frédéric; Seoane, Lucia

2016-04-01

We propose a new method to produce time series of global maps of surface mass variations by progressive integration of daily geopotential variations measured by orbiting satellites. In the case of the GRACE mission, these geopotential variations can be determined from very accurate inter-satellite K-Band Range Rate (KBRR) measurements of 5-second daily orbits. In particular, the along-track gravity contribution of hydrological mass changes is extracted by removing de-aliasing models for static field, atmosphere, oceans mass variations (including periodical tides), as well as polar movements. Our determination of surface mass sources is composed of two successive dependent Kalman filter stages. The first one consists of reducing the satellite-based potential anomalies by adjusting the longest spatial wavelengths (i.e., low-degree spherical harmonics lower than 2). In the second stage, the residual potential anomalies from the previous stage are used to recover surface mass density changes - in terms of Equivalent-Water Height (EWH) - over a global network of juxtaposed triangular elements. These surface tiles of ~100,000 km x km (or equivalently 330 km by 330 km) are defined to be of equal areas over the terrestrial sphere. However they can be adapted to the local geometry of the surface mass. Our global approach was tested by inverting geopotential data, and successfully applied to estimate time-varying surface mass densities from real GRACE-based residuals. This strategy of combined Kalman filter-type inversions can also be useful for exploring the possibility of improving time and space resolutions for ocean and land studies that would be hopefully brought by future low altitude geodetic missions.

Anthropogenic heat flux: advisable spatial resolutions when input data are scarce

NASA Astrophysics Data System (ADS)

Gabey, A. M.; Grimmond, C. S. B.; Capel-Timms, I.

2018-02-01

Anthropogenic heat flux (QF) may be significant in cities, especially under low solar irradiance and at night. It is of interest to many practitioners including meteorologists, city planners and climatologists. QF estimates at fine temporal and spatial resolution can be derived from models that use varying amounts of empirical data. This study compares simple and detailed models in a European megacity (London) at 500 m spatial resolution. The simple model (LQF) uses spatially resolved population data and national energy statistics. The detailed model (GQF) additionally uses local energy, road network and workday population data. The Fractions Skill Score (FSS) and bias are used to rate the skill with which the simple model reproduces the spatial patterns and magnitudes of QF, and its sub-components, from the detailed model. LQF skill was consistently good across 90% of the city, away from the centre and major roads. The remaining 10% contained elevated emissions and "hot spots" representing 30-40% of the total city-wide energy. This structure was lost because it requires workday population, spatially resolved building energy consumption and/or road network data. Daily total building and traffic energy consumption estimates from national data were within ± 40% of local values. Progressively coarser spatial resolutions to 5 km improved skill for total QF, but important features (hot spots, transport network) were lost at all resolutions when residential population controlled spatial variations. The results demonstrate that simple QF models should be applied with conservative spatial resolution in cities that, like London, exhibit time-varying energy use patterns.

Testing Snow Melt Algorithms in High Relief Topography Using Calibrated Enhanced-Resolution Brightness Temperatures, Hunza River Basin, Pakistan

NASA Astrophysics Data System (ADS)

Ramage, J. M.; Brodzik, M. J.; Hardman, M.; Troy, T. J.

2017-12-01

Snow is a vital part of the terrestrial hydrological cycle, a crucial resource for people and ecosystems. In mountainous regions snow is extensive, variable, and challenging to document. Snow melt timing and duration are important factors affecting the transfer of snow mass to soil moisture and runoff. Passive microwave brightness temperature (Tb) changes at 36 and 18 GHz are a sensitive way to detect snow melt onset due to their sensitivity to the abrupt change in emissivity. They are widely used on large icefields and high latitude watersheds. The coarse resolution ( 25 km) of historically available data has precluded effective use in high relief, heterogeneous regions, and gaps between swaths also create temporal data gaps at lower latitudes. New enhanced resolution data products generated from a scatterometer image reconstruction for radiometer (rSIR) technique are available at the original frequencies. We use these Calibrated Enhanced-resolution Brightness (CETB) Temperatures Earth System Data Records (ESDR) to evaluate existing snow melt detection algorithms that have been used in other environments, including the cross polarized gradient ratio (XPGR) and the diurnal amplitude variations (DAV) approaches. We use the 36/37 GHz (3.125 km resolution) and 18/19 GHz (6.25 km resolution) vertically and horizontally polarized datasets from the Special Sensor Microwave Imager (SSM/I) and Advanced Microwave Radiometer for EOS (AMSR-E) and evaluate them for use in this high relief environment. The new data are used to assess glacier and snow melt records in the Hunza River Basin [area 13,000 sq. km, located at 36N, 74E], a tributary to the Upper Indus Basin, Pakistan. We compare the melt timing results visually and quantitatively to the corresponding EASE-Grid 2.0 25-km dataset, SRTM topography, and surface temperatures from station and reanalysis data. The new dataset is coarser than the topography, but is able to differentiate signals of melt/refreeze timing for different altitudes and land cover in this remote area with significant hazards from snow melt and glacier discharge. The improved spatial resolution, enhanced to 3-6 km, and retaining twice daily observations is a key improvement to fully analyze snowpack melt characteristics in remote mountainous regions.

More than the sum of its parts? A merged satellite product from MODIS and AMSR2 sea ice concentration

NASA Astrophysics Data System (ADS)

Ludwig, V. S.; Istomina, L.; Spreen, G.

2017-12-01

Arctic sea ice concentration (SIC), the fraction of a grid cell that is covered by sea ice, is relevant for a multitude of branches: physics (heat/momentum exchange), chemistry (gas exchange), biology (photosynthesis), navigation (location of pack ice) and others. It has been observed from passive microwave (PMW) radiometers on satellites continuously since 1979, providing an almost 40-year time series. However, the resolution is limited to typically 25 km which is good enough for climate studies but too coarse to properly resolve the ice edge or to show leads. The highest resolution from PMW sensors today is 5 km of the AMSR2 89 GHz channels. Thermal infrared (TIR) and visible (VIS) measurements provide much higher resolutions between 1 km (TIR) and 30 m (VIS, regional daily coverage). The higher resolutions come at the cost of depending on cloud-free fields of view (TIR and VIS) and daylight (VIS). We present a merged product of ASI-AMSR2 SIC (PMW) and MODIS SIC (TIR) at a nominal resolution of 1 km. This product benefits from both the independence of PMW towards cloud coverage and the high resolution of TIR data. An independent validation data set has been produced from manually selected, cloud-free Landsat VIS data at 30 m resolution. This dataset is used to evaluate the performance of the merged SIC dataset. Our results show that the merged product resolves features which are smeared out by the PMW data while benefitting from the PMW data in cloudy cases and is thus indeed more than the sum of its parts.

Spatial Downscaling of TRMM Precipitation using MODIS product in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Cho, H.; Choi, M.

2013-12-01

Precipitation is a major driving force in the water cycle. But, it is difficult to provide spatially distributed precipitation data from isolated individual in situ. The Tropical Rainfall Monitoring Mission (TRMM) satellite can provide precipitation data with relatively coarse spatial resolution (0.25° scale) at daily basis. In order to overcome the coarse spatial resolution of TRMM precipitation products, we conducted a downscaling technique using a scaling parameter from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor. In this study, statistical relations between precipitation estimates derived from the TRMM satellite and the normalized difference vegetation index (NDVI) which is obtained from the MODIS sensor in TERRA satellite are found for different spatial scales on the Korean peninsula in northeast Asia. We obtain the downscaled precipitation mapping by regression equation between yearly TRMM precipitations values and annual average NDVI aggregating 1km to 25 degree. The downscaled precipitation is validated using time series of the ground measurements precipitation dataset provided by Korea Meteorological Organization (KMO) from 2002 to 2005. To improve the spatial downscaling of precipitation, we will conduct a study about correlation between precipitation and land surface temperature, perceptible water and other hydrological parameters.

Bifocal computational near eye light field displays and Structure parameters determination scheme for bifocal computational display.

PubMed

Liu, Mali; Lu, Chihao; Li, Haifeng; Liu, Xu

2018-02-19

We propose a bifocal computational near eye light field display (bifocal computational display) and structure parameters determination scheme (SPDS) for bifocal computational display that achieves greater depth of field (DOF), high resolution, accommodation and compact form factor. Using a liquid varifocal lens, two single-focal computational light fields are superimposed to reconstruct a virtual object's light field by time multiplex and avoid the limitation on high refresh rate. By minimizing the deviation between reconstructed light field and original light field, we propose a determination framework to determine the structure parameters of bifocal computational light field display. When applied to different objective to SPDS, it can achieve high average resolution or uniform resolution display over scene depth range. To analyze the advantages and limitation of our proposed method, we have conducted simulations and constructed a simple prototype which comprises a liquid varifocal lens, dual-layer LCDs and a uniform backlight. The results of simulation and experiments with our method show that the proposed system can achieve expected performance well. Owing to the excellent performance of our system, we motivate bifocal computational display and SPDS to contribute to a daily-use and commercial virtual reality display.

High-Resolution in Situ Measurement of Nitrate in Runoff from the Greenland Ice Sheet.

PubMed

Beaton, Alexander D; Wadham, Jemma L; Hawkings, Jon; Bagshaw, Elizabeth A; Lamarche-Gagnon, Guillaume; Mowlem, Matthew C; Tranter, Martyn

2017-11-07

We report the first in situ high-resolution nitrate time series from two proglacial meltwater rivers draining the Greenland Ice Sheet, using a recently developed submersible analyzer based on lab-on-chip (LOC) technology. The low sample volume (320 μL) required by the LOC analyzer meant that low concentration (few micromolar to submicromolar), highly turbid subglacial meltwater could be filtered and colorimetrically analyzed in situ. Nitrate concentrations in rivers draining Leverett Glacier in southwest Greenland and Kiattuut Sermiat in southern Greenland exhibited a clear diurnal signal and a gradual decline at the commencement of the melt season, displaying trends that would not be discernible using traditional daily manual sampling. Nitrate concentrations varied by 4.4 μM (±0.2 μM) over a 10 day period at Kiattuut Sermiat and 3.0 μM (±0.2 μM) over a 14 day period at Leverett Glacier. Marked changes in nitrate concentrations were observed when discharge began to increase. High-resolution in situ measurements such as these have the potential to significantly advance the understanding of nutrient cycling in remote systems, where the dynamics of nutrient release are complex but are important for downstream biogeochemical cycles.

The Impact of Estimating High-Resolution Tropospheric Gradients on Multi-GNSS Precise Positioning

PubMed Central

Zhou, Feng; Li, Xingxing; Li, Weiwei; Chen, Wen; Dong, Danan; Wickert, Jens; Schuh, Harald

2017-01-01

Benefits from the modernized US Global Positioning System (GPS), the revitalized Russian GLObal NAvigation Satellite System (GLONASS), and the newly-developed Chinese BeiDou Navigation Satellite System (BDS) and European Galileo, multi-constellation Global Navigation Satellite System (GNSS) has emerged as a powerful tool not only in positioning, navigation, and timing (PNT), but also in remote sensing of the atmosphere and ionosphere. Both precise positioning and the derivation of atmospheric parameters can benefit from multi-GNSS observations. In this contribution, extensive evaluations are conducted with multi-GNSS datasets collected from 134 globally-distributed ground stations of the International GNSS Service (IGS) Multi-GNSS Experiment (MGEX) network in July 2016. The datasets are processed in six different constellation combinations, i.e., GPS-, GLONASS-, BDS-only, GPS + GLONASS, GPS + BDS, and GPS + GLONASS + BDS + Galileo precise point positioning (PPP). Tropospheric gradients are estimated with eight different temporal resolutions, from 1 h to 24 h, to investigate the impact of estimating high-resolution gradients on position estimates. The standard deviation (STD) is used as an indicator of positioning repeatability. The results show that estimating tropospheric gradients with high temporal resolution can achieve better positioning performance than the traditional strategy in which tropospheric gradients are estimated on a daily basis. Moreover, the impact of estimating tropospheric gradients with different temporal resolutions at various elevation cutoff angles (from 3° to 20°) is investigated. It can be observed that with increasing elevation cutoff angles, the improvement in positioning repeatability is decreased. PMID:28368346

The 1 km resolution global data set: needs of the International Geosphere Biosphere Programme

USGS Publications Warehouse

Townshend, J.R.G.; Justice, C.O.; Skole, D.; Malingreau, J.-P.; Cihlar, J.; Teillet, P.; Sadowski, F.; Ruttenberg, S.

1994-01-01

Examination of the scientific priorities for the International Geosphere Biosphere Programme (IGBP) reveals a requirement for global land data sets in several of its Core Projects. These data sets need to be at several space and time scales. Requirements are demonstrated for the regular acquisition of data at spatial resolutions of 1 km and finer and at high temporal frequencies. Global daily data at a resolution of approximately 1 km are sensed by the Advanced Very High Resolution Radiometer (AVHRR), but they have not been available in a single archive. It is proposed, that a global data set of the land surface is created from remotely sensed data from the AVHRR to support a number of IGBP's projects. This data set should have a spatial resolution of 1 km and should be generated at least once every 10 days for the entire globe. The minimum length of record should be a year, and ideally a system should be put in place which leads to the continuous acquisition of 1 km data to provide a base line data set prior to the Earth Observing System (EOS) towards the end of the decade. Because of the high cloud cover in many parts of the world, it is necessary to plan for the collection of data from every orbit. Substantial effort will be required in the preprocessing of the data set involving radiometric calibration, atmospheric correction, geometric correction and temporal compositing, to make it suitable for the extraction of information.

The Impact of Estimating High-Resolution Tropospheric Gradients on Multi-GNSS Precise Positioning.

PubMed

Zhou, Feng; Li, Xingxing; Li, Weiwei; Chen, Wen; Dong, Danan; Wickert, Jens; Schuh, Harald

2017-04-03

Benefits from the modernized US Global Positioning System (GPS), the revitalized Russian GLObal NAvigation Satellite System (GLONASS), and the newly-developed Chinese BeiDou Navigation Satellite System (BDS) and European Galileo, multi-constellation Global Navigation Satellite System (GNSS) has emerged as a powerful tool not only in positioning, navigation, and timing (PNT), but also in remote sensing of the atmosphere and ionosphere. Both precise positioning and the derivation of atmospheric parameters can benefit from multi-GNSS observations. In this contribution, extensive evaluations are conducted with multi-GNSS datasets collected from 134 globally-distributed ground stations of the International GNSS Service (IGS) Multi-GNSS Experiment (MGEX) network in July 2016. The datasets are processed in six different constellation combinations, i.e., GPS-, GLONASS-, BDS-only, GPS + GLONASS, GPS + BDS, and GPS + GLONASS + BDS + Galileo precise point positioning (PPP). Tropospheric gradients are estimated with eight different temporal resolutions, from 1 h to 24 h, to investigate the impact of estimating high-resolution gradients on position estimates. The standard deviation (STD) is used as an indicator of positioning repeatability. The results show that estimating tropospheric gradients with high temporal resolution can achieve better positioning performance than the traditional strategy in which tropospheric gradients are estimated on a daily basis. Moreover, the impact of estimating tropospheric gradients with different temporal resolutions at various elevation cutoff angles (from 3° to 20°) is investigated. It can be observed that with increasing elevation cutoff angles, the improvement in positioning repeatability is decreased.

Enhancement of the MODIS Daily Snow Albedo Product

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Schaaf, Crystal B.; Wang, Zhuosen; Riggs, George A.

2009-01-01

The MODIS daily snow albedo product is a data layer in the MOD10A1 snow-cover product that includes snow-covered area and fractional snow cover as well as quality information and other metadata. It was developed to augment the MODIS BRDF/Albedo algorithm (MCD43) that provides 16-day maps of albedo globally at 500-m resolution. But many modelers require daily snow albedo, especially during the snowmelt season when the snow albedo is changing rapidly. Many models have an unrealistic snow albedo feedback in both estimated albedo and change in albedo over the seasonal cycle context, Rapid changes in snow cover extent or brightness challenge the MCD43 algorithm; over a 16-day period, MCD43 determines whether the majority of clear observations was snow-covered or snow-free then only calculates albedo for the majority condition. Thus changes in snow albedo and snow cover are not portrayed accurately during times of rapid change, therefore the current MCD43 product is not ideal for snow work. The MODIS daily snow albedo from the MOD10 product provides more frequent, though less robust maps for pixels defined as "snow" by the MODIS snow-cover algorithm. Though useful, the daily snow albedo product can be improved using a daily version of the MCD43 product as described in this paper. There are important limitations to the MOD10A1 daily snow albedo product, some of which can be mitigated. Utilizing the appropriate per-pixel Bidirectional Reflectance Distribution Functions (BRDFs) can be problematic, and correction for anisotropic scattering must be included. The BRDF describes how the reflectance varies with view and illumination geometry. Also, narrow-to-broadband conversion specific for snow on different surfaces must be calculated and this can be difficult. In consideration of these limitations of MOD10A1, we are planning to improve the daily snow albedo algorithm by coupling the periodic per-pixel snow albedo from MCD43, with daily surface ref|outanoom, In this paper, we compare a daily version of MCD43B3 with the daily albedo from MOD10A1. and MCD43B3 with a 16-day average of MOD10A1, over Greenland. We also discuss some near-future planned enhancements to MOD10A1.

The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning

Treesearch

C. Wiedinmyer; S. K. Akagi; R. J. Yokelson; L. K. Emmons; J. A. Al-Saadi; J. J. Orlando; A. J. Soja

2010-01-01

The Fire INventory from NCAR version 1.0 (FINNv1) provides daily, 1 km resolution, global estimates of the trace gas and particle emissions from open burning of biomass, which includes wildfire, agricultural fires, and prescribed burning and does not include 5 biofuel use and trash burning. Emission factors used in the calculations have been updated with recent data,...

Technical note: 3-hourly temporal downscaling of monthly global terrestrial biosphere model net ecosystem exchange

DOE PAGES

Fisher, Joshua B.; Sikka, Munish; Huntzinger, Deborah N.; ...

2016-07-29

Here, the land surface provides a boundary condition to atmospheric forward and flux inversion models. These models require prior estimates of CO 2 fluxes at relatively high temporal resolutions (e.g., 3-hourly) because of the high frequency of atmospheric mixing and wind heterogeneity. However, land surface model CO 2 fluxes are often provided at monthly time steps, typically because the land surface modeling community focuses more on time steps associated with plant phenology (e.g., seasonal) than on sub-daily phenomena. Here, we describe a new dataset created from 15 global land surface models and 4 ensemble products in the Multi-scale Synthesis andmore » Terrestrial Model Intercomparison Project (MsTMIP), temporally downscaled from monthly to 3-hourly output. We provide 3-hourly output for each individual model over 7 years (2004–2010), as well as an ensemble mean, a weighted ensemble mean, and the multi-model standard deviation. Output is provided in three different spatial resolutions for user preferences: 0.5° × 0.5°, 2.0° × 2.5°, and 4.0° × 5.0° (latitude × longitude).« less

Mapping of heavy metal pollution in river water at daily time-scale using spatio-temporal fusion of MODIS-aqua and Landsat satellite imageries.

PubMed

Swain, Ratnakar; Sahoo, Bhabagrahi

2017-05-01

For river water quality monitoring at 30m × 1-day spatio-temporal scales, a spatial and temporal adaptive reflectance fusion model (STARFM) is developed for estimating turbidity (T u ), total suspended solid (TSS), and six heavy metals (HV) of iron, zinc, copper, chromium, lead and cadmium, by blending the Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat (L s ) spectral bands. A combination of regression analysis and genetic algorithm (GA) techniques are applied to develop spectral relationships between T u -L s , TSS-T u , and each HV-TSS. The STARFM algorithm and all the developed relationship models are evaluated satisfactorily by various performance evaluation measures to develop heavy metal pollution index-based vulnerability maps at 1-km resolution in the Brahmani River in eastern India. The Monte-Carlo simulation based analysis of the developed formulations reveals that the uncertainty in estimating Zn and Cd is the minimum (1.04%) and the maximum (5.05%), respectively. Hence, the remote sensing based approach developed herein can effectively be used in many world rivers for real-time monitoring of heavy metal pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of Ultra High Resolution Sea Surface Temperature Level 4 Datasets

NASA Technical Reports Server (NTRS)

Wagner, Grant

2011-01-01

Sea surface temperature (SST) studies are often focused on improving accuracy, or understanding and quantifying uncertainties in the measurement, as SST is a leading indicator of climate change and represents the longest time series of any ocean variable observed from space. Over the past several decades SST has been studied with the use of satellite data. This allows a larger area to be studied with much more frequent measurements being taken than direct measurements collected aboard ship or buoys. The Group for High Resolution Sea Surface Temperature (GHRSST) is an international project that distributes satellite derived sea surface temperatures (SST) data from multiple platforms and sensors. The goal of the project is to distribute these SSTs for operational uses such as ocean model assimilation and decision support applications, as well as support fundamental SST research and climate studies. Examples of near real time applications include hurricane and fisheries studies and numerical weather forecasting. The JPL group has produced a new 1 km daily global Level 4 SST product, the Multiscale Ultrahigh Resolution (MUR), that blends SST data from 3 distinct NASA radiometers: the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Very High Resolution Radiometer (AVHRR), and the Advanced Microwave Scanning Radiometer ? Earth Observing System(AMSRE). This new product requires further validation and accuracy assessment, especially in coastal regions.We examined the accuracy of the new MUR SST product by comparing the high resolution version and a lower resolution version that has been smoothed to 19 km (but still gridded to 1 km). Both versions were compared to the same data set of in situ buoy temperature measurements with a focus on study regions of the oceans surrounding North and Central America as well as two smaller regions around the Gulf Stream and California coast. Ocean fronts exhibit high temperature gradients (Roden, 1976), and thus satellite data of SST can be used in the detection of these fronts. In this case, accuracy is less of a concern because the primary focus is on the spatial derivative of SST. We calculated the gradients for both versions of the MUR data set and did statistical comparisons focusing on the same regions.

Stochastic Modeling of Empirical Storm Loss in Germany

NASA Astrophysics Data System (ADS)

Prahl, B. F.; Rybski, D.; Kropp, J. P.; Burghoff, O.; Held, H.

2012-04-01

Based on German insurance loss data for residential property we derive storm damage functions that relate daily loss with maximum gust wind speed. Over a wide range of loss, steep power law relationships are found with spatially varying exponents ranging between approximately 8 and 12. Global correlations between parameters and socio-demographic data are employed to reduce the number of local parameters to 3. We apply a Monte Carlo approach to calculate German loss estimates including confidence bounds in daily and annual resolution. Our model reproduces the annual progression of winter storm losses and enables to estimate daily losses over a wide range of magnitude.

genRE: A Method to Extend Gridded Precipitation Climatology Data Sets in Near Real-Time for Hydrological Forecasting Purposes

NASA Astrophysics Data System (ADS)

van Osnabrugge, B.; Weerts, A. H.; Uijlenhoet, R.

2017-11-01

To enable operational flood forecasting and drought monitoring, reliable and consistent methods for precipitation interpolation are needed. Such methods need to deal with the deficiencies of sparse operational real-time data compared to quality-controlled offline data sources used in historical analyses. In particular, often only a fraction of the measurement network reports in near real-time. For this purpose, we present an interpolation method, generalized REGNIE (genRE), which makes use of climatological monthly background grids derived from existing gridded precipitation climatology data sets. We show how genRE can be used to mimic and extend climatological precipitation data sets in near real-time using (sparse) real-time measurement networks in the Rhine basin upstream of the Netherlands (approximately 160,000 km2). In the process, we create a 1.2 × 1.2 km transnational gridded hourly precipitation data set for the Rhine basin. Precipitation gauge data are collected, spatially interpolated for the period 1996-2015 with genRE and inverse-distance squared weighting (IDW), and then evaluated on the yearly and daily time scale against the HYRAS and EOBS climatological data sets. Hourly fields are compared qualitatively with RADOLAN radar-based precipitation estimates. Two sources of uncertainty are evaluated: station density and the impact of different background grids (HYRAS versus EOBS). The results show that the genRE method successfully mimics climatological precipitation data sets (HYRAS/EOBS) over daily, monthly, and yearly time frames. We conclude that genRE is a good interpolation method of choice for real-time operational use. genRE has the largest added value over IDW for cases with a low real-time station density and a high-resolution background grid.

Applications systems verification and transfer project. Volume 2: Operational applications of satellite snow-cover observations and data-collection systems in the Arizona test site

NASA Technical Reports Server (NTRS)

Schumann, H. H.

1981-01-01

Ground surveys and aerial observations were used to monitor rapidly changing moisture conditions in the Salt-Verde watershed. Repetitive satellite snow cover observations greatly reduce the necessity for routine aerial snow reconnaissance flights over the mountains. High resolution, multispectral imagery provided by LANDSAT satellite series enabled rapid and accurate mapping of snow-cover distributions for small- to medium-sized subwatersheds; however, the imagery provided only one observation every 9 days of about a third of the watershed. Low resolution imagery acquired by the ITOSa dn SMS/GOES meteorological satellite series provides the daily synoptic observation necessary to monitor the rapid changes in snow-covered area in the entire watershed. Short term runoff volumes can be predicted from daily sequential snow cover observations.

Spatial variations in fault friction related to lithology from rupture and afterslip of the 2014 South Napa, California, earthquake

USGS Publications Warehouse

Michael Floyd,; Richard Walters,; John Elliot,; Funning, Gareth J.; Svarc, Jerry L.; Murray, Jessica R.; Andy Hooper,; Yngvar Larsen,; Petar Marinkovic,; Bürgmann, Roland; Johanson, Ingrid; Tim Wright,

2016-01-01

Following earthquakes, faults are often observed to continue slipping aseismically. It has been proposed that this afterslip occurs on parts of the fault with rate-strengthening friction that are stressed by the mainshock, but our understanding has been limited by a lack of immediate, high-resolution observations. Here we show that the behavior of afterslip following the 2014 South Napa earthquake varied over distances of only a few kilometers. This variability cannot be explained by coseismic stress changes alone. We present daily positions from continuous and survey GPS sites that we re-measured within 12 hours of the mainshock, and surface displacements from the new Sentinel-1 radar mission. This unique geodetic data set constrains the distribution and evolution of coseismic and postseismic fault slip with exceptional resolution in space and time. We suggest that the observed heterogeneity in behavior is caused by lithological controls on the frictional properties of the fault plane.

OCTOCAM: A Workhorse Instrument for the Gemini Telescopes During the Era of LSST

NASA Astrophysics Data System (ADS)

Roming, Peter; van der Horst, Alexander; OCTOCAM Team

2018-01-01

The decade of the 2020s are planned to be an era of large surveys and giant telescopes. A trademark of this era will be the large number of interesting objects observed daily by high-cadence surveys, such as the LSST. Because of the sheer numbers, only a very small fraction of these interesting objects will be observed with extremely large telescopes. The follow up workhorses during this era will be the 8-meter class telescopes and corresponding instruments that are prepared to pursue these interesting objects. One such workhorse instrument is OCTOCAM, a highly efficient instrument designed to probe the time domain window with simulatenous broad-wavelength coverage. OCTOCAM optimizes the use of Gemini for broadband imaging and spectroscopic single-target observations. The instrument is designed for high temporal resolution, broad spectral coverage, and moderate spectral resolution. OCTOCAM was selected as part of the Gemini instrumentation program in early 2017. Here we provide a description of the science cases to be addressed, overall instrument design, and current status.

The effect of spatial resolution on water scarcity estimates in Australia

NASA Astrophysics Data System (ADS)

Gevaert, Anouk; Veldkamp, Ted; van Dijk, Albert; Ward, Philip

2017-04-01

Water scarcity is an important global issue with severe socio-economic consequences, and its occurrence is likely to increase in many regions due to population growth, economic development and climate change. This has prompted a number of global and regional studies to identify areas that are vulnerable to water scarcity and to determine how this vulnerability will change in the future. A drawback of these studies, however, is that they typically have coarse spatial resolutions. Here, we studied the effect of increasing the spatial resolution of water scarcity estimates in Australia, and the Murray-Darling Basin in particular. This was achieved by calculating the water stress index (WSI), an indicator showing the ratio of water use to water availability, at 0.5 and 0.05 degree resolution for the period 1990-2010. Monthly water availability data were based on outputs of the Australian Water Resources Assessment Landscape model (AWRA-L), which was run at both spatial resolutions and at a daily time scale. Water use information was obtained from a monthly 0.5 degree global dataset that distinguishes between water consumption for irrigation, livestock, industrial and domestic uses. The data were downscaled to 0.05 degree by dividing the sectoral water uses over the areas covered by relevant land use types using a high resolution ( 0.5km) land use dataset. The monthly WSIs at high and low resolution were then used to evaluate differences in the patterns of water scarcity frequency and intensity. In this way, we assess to what extent increasing the spatial resolution can improve the identification of vulnerable areas and thereby assist in the development of strategies to lower this vulnerability. The results of this study provide insight into the scalability of water scarcity estimates and the added value of high resolution water scarcity information in water resources management.

Production and Distribution of NASA MODIS Remote Sensing Products

NASA Technical Reports Server (NTRS)

Wolfe, Robert

2007-01-01

The two Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on-board NASA's Earth Observing System (EOS) Terra and Aqua satellites make key measurements for understanding the Earth's terrestrial ecosystems. Global time-series of terrestrial geophysical parameters have been produced from MODIS/Terra for over 7 years and for MODIS/Aqua for more than 4 1/2 years. These well calibrated instruments, a team of scientists and a large data production, archive and distribution systems have allowed for the development of a new suite of high quality product variables at spatial resolutions as fine as 250m in support of global change research and natural resource applications. This talk describes the MODIS Science team's products, with a focus on the terrestrial (land) products, the data processing approach and the process for monitoring and improving the product quality. The original MODIS science team was formed in 1989. The team's primary role is the development and implementation of the geophysical algorithms. In addition, the team provided feedback on the design and pre-launch testing of the instrument and helped guide the development of the data processing system. The key challenges the science team dealt with before launch were the development of algorithms for a new instrument and provide guidance of the large and complex multi-discipline processing system. Land, Ocean and Atmosphere discipline teams drove the processing system requirements, particularly in the area of the processing loads and volumes needed to daily produce geophysical maps of the Earth at resolutions as fine as 250 m. The processing system had to handle a large number of data products, large data volumes and processing loads, and complex processing requirements. Prior to MODIS, daily global maps from heritage instruments, such as Advanced Very High Resolution Radiometer (AVHRR), were not produced at resolutions finer than 5 km. The processing solution evolved into a combination of processing the lower level (Level 1) products and the higher level discipline specific Land and Atmosphere products in the MODIS Science Investigator Lead Processing System (SIPS), the MODIS Adaptive Processing System (MODAPS), and archive and distribution of the Land products to the user community by two of NASA s EOS Distributed Active Archive Centers (DAACs). Recently, a part of MODAPS, the Level 1 and Atmosphere Archive and Distribution System (LAADS), took over the role of archiving and distributing the Level 1 and Atmosphere products to the user community.

Probabilistic global maps of the CO2 column at daily and monthly scales from sparse satellite measurements

NASA Astrophysics Data System (ADS)

Chevallier, Frédéric; Broquet, Grégoire; Pierangelo, Clémence; Crisp, David

2017-07-01

The column-average dry air-mole fraction of carbon dioxide in the atmosphere (XCO2) is measured by scattered satellite measurements like those from the Orbiting Carbon Observatory (OCO-2). We show that global continuous maps of XCO2 (corresponding to level 3 of the satellite data) at daily or coarser temporal resolution can be inferred from these data with a Kalman filter built on a model of persistence. Our application of this approach on 2 years of OCO-2 retrievals indicates that the filter provides better information than a climatology of XCO2 at both daily and monthly scales. Provided that the assigned observation uncertainty statistics are tuned in each grid cell of the XCO2 maps from an objective method (based on consistency diagnostics), the errors predicted by the filter at daily and monthly scales represent the true error statistics reasonably well, except for a bias in the high latitudes of the winter hemisphere and a lack of resolution (i.e., a too small discrimination skill) of the predicted error standard deviations. Due to the sparse satellite sampling, the broad-scale patterns of XCO2 described by the filter seem to lag behind the real signals by a few weeks. Finally, the filter offers interesting insights into the quality of the retrievals, both in terms of random and systematic errors.

Regionalizing nonparametric models of precipitation amounts on different temporal scales

NASA Astrophysics Data System (ADS)

Mosthaf, Tobias; Bárdossy, András

2017-05-01

Parametric distribution functions are commonly used to model precipitation amounts corresponding to different durations. The precipitation amounts themselves are crucial for stochastic rainfall generators and weather generators. Nonparametric kernel density estimates (KDEs) offer a more flexible way to model precipitation amounts. As already stated in their name, these models do not exhibit parameters that can be easily regionalized to run rainfall generators at ungauged locations as well as at gauged locations. To overcome this deficiency, we present a new interpolation scheme for nonparametric models and evaluate it for different temporal resolutions ranging from hourly to monthly. During the evaluation, the nonparametric methods are compared to commonly used parametric models like the two-parameter gamma and the mixed-exponential distribution. As water volume is considered to be an essential parameter for applications like flood modeling, a Lorenz-curve-based criterion is also introduced. To add value to the estimation of data at sub-daily resolutions, we incorporated the plentiful daily measurements in the interpolation scheme, and this idea was evaluated. The study region is the federal state of Baden-Württemberg in the southwest of Germany with more than 500 rain gauges. The validation results show that the newly proposed nonparametric interpolation scheme provides reasonable results and that the incorporation of daily values in the regionalization of sub-daily models is very beneficial.

Modeling Future Fire danger over North America in a Changing Climate

NASA Astrophysics Data System (ADS)

Jain, P.; Paimazumder, D.; Done, J.; Flannigan, M.

2016-12-01

Fire danger ratings are used to determine wildfire potential due to weather and climate factors. The Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System (CFFDRS), incorporates temperature, relative humidity, windspeed and precipitation to give a daily fire danger rating that is used by wildfire management agencies in an operational context. Studies using GCM output have shown that future wildfire danger will increase in a warming climate. However, these studies are somewhat limited by the coarse spatial resolution (typically 100-400km) and temporal resolution (typically 6-hourly to monthly) of the model output. Future wildfire potential over North America based on FWI is calculated using output from the Weather, Research and Forecasting (WRF) model, which is used to downscale future climate scenarios from the bias-corrected Community Climate System Model (CCSM) under RCP8.5 scenarios at a spatial resolution of 36km. We consider five eleven year time slices: 1990-2000, 2020-2030, 2030-2040, 2050-2060 and 2080-2090. The dynamically downscaled simulation improves determination of future extreme weather by improving both spatial and temporal resolution over most GCM models. To characterize extreme fire weather we calculate annual numbers of spread days (days for which FWI > 19) and annual 99th percentile of FWI. Additionally, an extreme value analysis based on the peaks-over-threshold method allows us to calculate the return values for extreme FWI values.

Improving the Energy Saving Process with High-Resolution Data: A Case Study in a University Building.

PubMed

Han, Jeongyun; Lee, Eunjung; Cho, Hyunghun; Yoon, Yoonjin; Lee, Hyoseop; Rhee, Wonjong

2018-05-17

In this paper, we provide findings from an energy saving experiment in a university building, where an IoT platform with 1 Hz sampling sensors was deployed to collect electric power consumption data. The experiment was a reward setup with daily feedback delivered by an energy delegate for one week, and energy saving of 25.4% was achieved during the experiment. Post-experiment sustainability, defined as 10% or more of energy saving, was also accomplished for 44 days without any further intervention efforts. The saving was possible mainly because of the data-driven intervention designs with high-resolution data in terms of sampling frequency and number of sensors, and the high-resolution data turned out to be pivotal for an effective waste behavior investigation. While the quantitative result was encouraging, we also noticed many uncontrollable factors, such as exams, papers due, office allocation shuffling, graduation, and new-comers, that affected the result in the campus environment. To confirm that the quantitative result was due to behavior changes, rather than uncontrollable factors, we developed several data-driven behavior detection measures. With these measures, it was possible to analyze behavioral changes, as opposed to simply analyzing quantitative fluctuations. Overall, we conclude that the space-time resolution of data can be crucial for energy saving, and potentially for many other data-driven energy applications.

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

SMAP Soil Moisture Disaggregation using Land Surface Temperature and Vegetation Data

NASA Astrophysics Data System (ADS)

Fang, B.; Lakshmi, V.

2016-12-01

Soil moisture (SM) is a key parameter in agriculture, hydrology and ecology studies. The global SM retrievals have been providing by microwave remote sensing technology since late 1970s and many SM retrieval algorithms have been developed, calibrated and applied on satellite sensors such as AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System), AMSR-2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). Particularly, SMAP (Soil Moisture Active/Passive) satellite, which was developed by NASA, was launched in January 2015. SMAP provides soil moisture products of 9 km and 36 km spatial resolutions which are not capable for research and applications of finer scale. Toward this issue, this study applied a SM disaggregation algorithm to disaggregate SMAP passive microwave soil moisture 36 km product. This algorithm was developed based on the thermal inertial relationship between daily surface temperature variation and daily average soil moisture which is modulated by vegetation condition, by using remote sensing retrievals from AVHRR (Advanced Very High Resolution Radiometer, MODIS (Moderate Resolution Imaging Spectroradiometer), SPOT (Satellite Pour l'Observation de la Terre), as well as Land Surface Model (LSM) output from NLDAS (North American Land Data Assimilation System). The disaggregation model was built at 1/8o spatial resolution on monthly basis and was implemented to calculate and disaggregate SMAP 36 km SM retrievals to 1 km resolution in Oklahoma. The SM disaggregation results were also validated using MESONET (Mesoscale Network) and MICRONET (Microscale Network) ground SM measurements.

Merging Radar Quantitative Precipitation Estimates (QPEs) from the High-resolution NEXRAD Reanalysis over CONUS with Rain-gauge Observations

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Nickl, E.; Seo, D. J.; Kim, B.; Zhang, J.; Qi, Y.

2015-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over the Continental United States (CONUS) is completed for the period covering from 2002 to 2011. While this constitutes a unique opportunity to study precipitation processes at higher resolution than conventionally possible (1-km, 5-min), the long-term radar-only product needs to be merged with in-situ information in order to be suitable for hydrological, meteorological and climatological applications. The radar-gauge merging is performed by using rain gauge information at daily (Global Historical Climatology Network-Daily: GHCN-D), hourly (Hydrometeorological Automated Data System: HADS), and 5-min (Automated Surface Observing Systems: ASOS; Climate Reference Network: CRN) resolution. The challenges related to incorporating differing resolution and quality networks to generate long-term large-scale gridded estimates of precipitation are enormous. In that perspective, we are implementing techniques for merging the rain gauge datasets and the radar-only estimates such as Inverse Distance Weighting (IDW), Simple Kriging (SK), Ordinary Kriging (OK), and Conditional Bias-Penalized Kriging (CBPK). An evaluation of the different radar-gauge merging techniques is presented and we provide an estimate of uncertainty for the gridded estimates. In addition, comparisons with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) are provided in order to give a detailed picture of the improvements and remaining challenges.

A Framework for Mapping Global Evapotranspiration using 375-m VIIRS LST

NASA Astrophysics Data System (ADS)

Hain, C.; Anderson, M. C.; Schull, M. A.; Neale, C. M. U.

2017-12-01

As the world's water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use are becoming increasingly important, especially in areas of food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in morning land surface temperature to estimate the partitioning of sensible/latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring. Until recently, ALEXI has been limited to areas with high resolution temporal sampling of geostationary sensors. The use of geostationary sensors makes global mapping a complicated process, especially for real-time applications, as data from as many as five different sensors are required to be ingested and harmonized to create a global mosaic. However, our research team has developed a new and novel method of using twice-daily observations from polar-orbiting sensors such as MODIS and VIIRS to estimate the mid-morning rise in LST that is used to drive the energy balance estimations within ALEXI. This allows the method to be applied globally using a single sensor rather than a global compositing of all available geostationary data. Other advantages of this new method include the higher spatial resolution provided by MODIS and VIIRS and the increased sampling at high latitudes where oblique view angles limit the utility of geostationary sensors. Improvements to the spatial resolution of the thermal infrared wavelengths on the VIIRS instrument, as compared to MODIS (375-m VIIRS vs. 1-km MODIS), allows for a much higher resolution ALEXI product than has been previously available. Therefore, recent developments have been to generate 375-m ALEXI ET products over several pilot regions (e.g. western US and the MENA region). The monitoring of consumptive water use over regions where significant groundwater pumping for irrigation is employed is important to accurately quantify the efficiency of water use in the region.

Euro-Atlantic winter storminess and precipitation extremes under 1.5 °C vs. 2 °C warming scenarios

NASA Astrophysics Data System (ADS)

Barcikowska, Monika J.; Weaver, Scott J.; Feser, Frauke; Russo, Simone; Schenk, Frederik; Stone, Dáithí A.; Wehner, Michael F.; Zahn, Matthias

2018-06-01

Severe winter storms in combination with precipitation extremes pose a serious threat to Europe. Located at the southeastern exit of the North Atlantic's storm track, European coastlines are directly exposed to impacts by high wind speeds, storm floods and coastal erosion. In this study we analyze potential changes in simulated winter storminess and extreme precipitation, which may occur under 1.5 or 2 °C warming scenarios. Here we focus on a first simulation suite of the atmospheric model CAM5 performed within the HAPPI project and evaluate how changes of the horizontal model resolution impact the results regarding atmospheric pressure, storm tracks, wind speed and precipitation extremes. The comparison of CAM5 simulations with different resolutions indicates that an increased horizontal resolution to 0.25° not only refines regional-scale information but also improves large-scale atmospheric circulation features over the Euro-Atlantic region. The zonal bias in monthly pressure at mean sea level and wind fields, which is typically found in low-resolution models, is considerably reduced. This allows us to analyze potential changes in regional- to local-scale extreme wind speeds and precipitation in a more realistic way. Our analysis of the future response for the 2 °C warming scenario generally confirms previous model simulations suggesting a poleward shift and intensification of the meridional circulation in the Euro-Atlantic region. Additional analysis suggests that this shift occurs mainly after exceeding the 1.5 °C global warming level, when the midlatitude jet stream manifests a strengthening northeastward. At the same time, this northeastern shift of the storm tracks allows an intensification and northeastern expansion of the Azores high, leading to a tendency of less precipitation across the Bay of Biscay and North Sea. Regions impacted by the strengthening of the midlatitude jet, such as the northwestern coasts of the British Isles, Scandinavia and the Norwegian Sea, and over the North Atlantic east of Newfoundland, experience an increase in the mean as well as daily and sub-daily precipitation, wind extremes and storminess, suggesting an important influence of increasing storm activity in these regions in response to global warming.

The creation of future daily gridded datasets of precipitation and temperature with a spatial weather generator, Cyprus 2020-2050

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Pashiardis, Stelios; Lange, Manfred

2014-05-01

High-resolution gridded daily datasets are essential for natural resource management and the analysis of climate changes and their effects. This study aimed to create gridded datasets of daily precipitation and daily minimum and maximum temperature, for the future (2020-2050). The horizontal resolution of the developed datasets is 1 x 1 km2, covering the area under control of the Republic of Cyprus (5.760 km2). The study is divided into two parts. The first consists of the evaluation of the performance of different interpolation techniques for daily rainfall and temperature data (1980-2010) for the creation of the gridded datasets. Rainfall data recorded at 145 stations and temperature data from 34 stations were used. For precipitation, inverse distance weighting (IDW) performs best for local events, while a combination of step-wise geographically weighted regression and IDW proves to be the best method for large scale events. For minimum and maximum temperature, a combination of step-wise linear multiple regression and thin plate splines is recognized as the best method. Six Regional Climate Models (RCMs) for the A1B SRES emission scenario from the EU ENSEMBLE project database were selected as sources for future climate projections. The RCMs were evaluated for their capacity to simulate Cyprus climatology for the period 1980-2010. Data for the period 2020-2050 from the three best performing RCMs were downscaled, using the change factors approach, at the location of observational stations. Daily time series were created with a stochastic rainfall and temperature generator. The RainSim V3 software (Burton et al., 2008) was used to generate spatial-temporal coherent rainfall fields. The temperature generator was developed in R and modeled temperature as a weakly stationary process with the daily mean and standard deviation conditioned on the wet and dry state of the day (Richardson, 1981). Finally gridded datasets depicting projected future climate conditions were created with the identified best interpolation methods. The difference between the input and simulated mean daily rainfall, averaged over all the stations, was 0.03 mm (2.2%), while the error related to the number of dry days was 2 (0.6%). For mean daily minimum temperature the error was 0.005 ºC (0.04%), while for maximum temperature it was 0.01 ºC (0.04%). Overall, the weather generators were found to be reliable instruments for the downscaling of precipitation and temperature. The resulting datasets indicate a decrease of the mean annual rainfall over the study area between 5 and 70 mm (1-15%) for 2020-2050, relative to 1980-2010. Average annual minimum and maximum temperature over the Republic of Cyprus are projected to increase between 1.2 and 1.5 ºC. The dataset is currently used to compute agricultural production and water use indicators, as part of the AGWATER project (AEIFORIA/GEORGO/0311(BIE)/06), co-financed by the European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation. Burton, A., Kilsby, C.G., Fowler, H.J., Cowpertwait, P.S.P., and O'Connell, P.E.: RainSim: A spatial-temporal stochastic rainfall modelling system. Environ. Model. Software 23, 1356-1369, 2008 Richardson, C.W.: Stochastic simulation of daily precipitation, temperature, and solar radiation. Water Resour. Res. 17, 182-190, 1981.

File Specification for the 7-km GEOS-5 Nature Run, Ganymed Release Non-Hydrostatic 7-km Global Mesoscale Simulation

NASA Technical Reports Server (NTRS)

da Silva, Arlindo M.; Putman, William; Nattala, J.

2014-01-01

This document describes the gridded output files produced by a two-year global, non-hydrostatic mesoscale simulation for the period 2005-2006 produced with the non-hydrostatic version of GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), O3, CO and CO2. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic sources. A description of the GEOS-5 model configuration used for this simulation can be found in Putman et al. (2014). The simulation is performed at a horizontal resolution of 7 km using a cubed-sphere horizontal grid with 72 vertical levels, extending up to to 0.01 hPa (approximately 80 km). For user convenience, all data products are generated on two logically rectangular longitude-latitude grids: a full-resolution 0.0625 deg grid that approximately matches the native cubed-sphere resolution, and another 0.5 deg reduced-resolution grid. The majority of the full-resolution data products are instantaneous with some fields being time-averaged. The reduced-resolution datasets are mostly time-averaged, with some fields being instantaneous. Hourly data intervals are used for the reduced-resolution datasets, while 30-minute intervals are used for the full-resolution products. All full-resolution output is on the model's native 72-layer hybrid sigma-pressure vertical grid, while the reduced-resolution output is given on native vertical levels and on 48 pressure surfaces extending up to 0.02 hPa. Section 4 presents additional details on horizontal and vertical grids. Information of the model surface representation can be found in Appendix B. The GEOS-5 product is organized into file collections that are described in detail in Appendix C. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GEOS-5 Nature Run portal: http://gmao.gsfc.nasa.gov/projects/G5NR. Information on the scientific quality of this simulation will appear in a forthcoming NASA Technical Report Series on Global Modeling and Data Assimilation to be available from http://gmao.gsfc.nasa.gov/pubs/tm/.

Greenland outlet glacier dynamics from Extreme Ice Survey (EIS) photogrammetry

NASA Astrophysics Data System (ADS)

Hawbecker, P.; Box, J. E.; Balog, J. D.; Ahn, Y.; Benson, R. J.

2010-12-01

Time Lapse cameras fill gaps in our observational capabilities: 1. By providing much higher temporal resolution than offered by conventional airborne or satellite remote sensing. 2. While GPS or auto-theodolite observations can provide higher time resolution data than from photogrammetry, survival of these instruments on the hazardous glacier surface is limited, plus, the maintenance of such systems can be more expensive than the maintenance of a terrestrial photogrammetry installation. 3. Imagery provide a high spatial density of observations across the glacier surface, higher than is realistically available from GPS or other in-situ observations. 4. time lapse cameras provide observational capabilities in Eulerian and Lagrangian frames while GPS or theodolite targets, going along for a ride on the glacier, provide only Lagrangian data. Photogrammetry techniques are applied to a year-plus of images from multiple west Greenland glaciers to determine the glacier front horizontal velocity variations at hourly to seasonal time scales. The presentation includes comparisons between glacier front velocities and: 1. surface melt rates inferred from surface air temperature and solar radiation observations; 2. major calving events identified from camera images; 3. surface and near-surface ocean temperature; 4. land-fast sea ice breakup; 5. tidal variations; 6. supra-glacial melt lake drainage events observed in daily optical satellite imagery; and 7.) GPS data. Extreme Ice Survey (EIS) time lapse camera overlooking the Petermann glacier, installed to image glacier dynamics and to capture the predicted ice "island" detachment.

A Real-time 1/16° Global Ocean Nowcast/Forecast System

NASA Astrophysics Data System (ADS)

Shriver, J. F.; Rhodes, R. C.; Hurlburt, H. E.; Wallcraft, A. J.; Metzger, E. J.; Smedstad, O. M.; Kara, A. B.

2001-05-01

A 1/16° eddy-resolving global ocean prediction system that uses the NRL Layered Ocean Model (NLOM) has been transitioned to the Naval Oceanographic Office (NAVO), Stennis Space Center, MS. The system gives a real time view of the ocean down to the 50-100 mile scale of ocean eddies and the meandering of ocean currents and fronts, a view with unprecedented resolution and clarity, and demonstrated forecast skill for a month or more for many ocean features. It has been running in real time at NAVO since 19 Oct 2000 with assimilation of real-time altimeter sea surface height (SSH) data (currently ERS-2, GFO and TOPEX/POSEIDON) and sea surface temperature (SST). The model is updated daily and 4-day forecasts are made daily. 30-day forecasts are made once a week. Nowcasts and forecasts using this model are viewable on the web, including SSH, SST and 30-day forecast verification statistics for many zoom regions. The NRL web address is http://www7320.nrlssc.navy.mil/global_nlom/index.html. The NAVO web address is: http://www.navo.navy.mil. Click on "Operational Products", then "Product Search Form", then "Product Type View", then select "Model Navy Layered Ocean Model" and a region and click on "Submit Query". This system is used at NAVO for ocean front and eddy analyses and predictions and to provide accurate sea surface height for use in computing synthetic temperature and salinity profiles, among other applications.

Measurement error in time-series analysis: a simulation study comparing modelled and monitored data.

PubMed

Butland, Barbara K; Armstrong, Ben; Atkinson, Richard W; Wilkinson, Paul; Heal, Mathew R; Doherty, Ruth M; Vieno, Massimo

2013-11-13

Assessing health effects from background exposure to air pollution is often hampered by the sparseness of pollution monitoring networks. However, regional atmospheric chemistry-transport models (CTMs) can provide pollution data with national coverage at fine geographical and temporal resolution. We used statistical simulation to compare the impact on epidemiological time-series analysis of additive measurement error in sparse monitor data as opposed to geographically and temporally complete model data. Statistical simulations were based on a theoretical area of 4 regions each consisting of twenty-five 5 km × 5 km grid-squares. In the context of a 3-year Poisson regression time-series analysis of the association between mortality and a single pollutant, we compared the error impact of using daily grid-specific model data as opposed to daily regional average monitor data. We investigated how this comparison was affected if we changed the number of grids per region containing a monitor. To inform simulations, estimates (e.g. of pollutant means) were obtained from observed monitor data for 2003-2006 for national network sites across the UK and corresponding model data that were generated by the EMEP-WRF CTM. Average within-site correlations between observed monitor and model data were 0.73 and 0.76 for rural and urban daily maximum 8-hour ozone respectively, and 0.67 and 0.61 for rural and urban loge(daily 1-hour maximum NO2). When regional averages were based on 5 or 10 monitors per region, health effect estimates exhibited little bias. However, with only 1 monitor per region, the regression coefficient in our time-series analysis was attenuated by an estimated 6% for urban background ozone, 13% for rural ozone, 29% for urban background loge(NO2) and 38% for rural loge(NO2). For grid-specific model data the corresponding figures were 19%, 22%, 54% and 44% respectively, i.e. similar for rural loge(NO2) but more marked for urban loge(NO2). Even if correlations between model and monitor data appear reasonably strong, additive classical measurement error in model data may lead to appreciable bias in health effect estimates. As process-based air pollution models become more widely used in epidemiological time-series analysis, assessments of error impact that include statistical simulation may be useful.

A Multi-Season Study of the Effects of MODIS Sea-Surface Temperatures on Operational WRF Forecasts at NWS Miami, FL

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Santos, Pablo; Lazarus, Steven M.; Splitt, Michael E.; Haines, Stephanie L.; Dembek, Scott R.; Lapenta, William M.

2008-01-01

Studies at the Short-term Prediction Research and Transition (SPORT) Center have suggested that the use of Moderate Resolution Imaging Spectroradiometer (MODIS) sea-surface temperature (SST) composites in regional weather forecast models can have a significant positive impact on short-term numerical weather prediction in coastal regions. Recent work by LaCasse et al (2007, Monthly Weather Review) highlights lower atmospheric differences in regional numerical simulations over the Florida offshore waters using 2-km SST composites derived from the MODIS instrument aboard the polar-orbiting Aqua and Terra Earth Observing System satellites. To help quantify the value of this impact on NWS Weather Forecast Offices (WFOs), the SPORT Center and the NWS WFO at Miami, FL (MIA) are collaborating on a project to investigate the impact of using the high-resolution MODIS SST fields within the Weather Research and Forecasting (WRF) prediction system. The project's goal is to determine whether more accurate specification of the lower-boundary forcing within WRF will result in improved land/sea fluxes and hence, more accurate evolution of coastal mesoscale circulations and the associated sensible weather elements. The NWS MIA is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run dally initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. Each model run is initialized using the Local Analysis and Prediction System (LAPS) analyses available in AWIPS. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution (approx.9 km); however, the RTG product does not exhibit fine-scale details consistent with its grid resolution. SPORT is conducting parallel WRF EMS runs identical to the operational runs at NWS MIA except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water, The MODIS SST composites for initializing the SPORT WRF runs are generated on a 2-km grid four times daily at 0400, 0700, 1600, and 1900 UTC, based on the times of the overhead passes of the Aqua and Terra satellites. The incorporation of the MODIS SST data into the SPORT WRF runs is staggered such that SSTs are updated with a new composite every six hours in each of the WRF runs. From mid-February to July 2007, over 500 parallel WRF simulations have been collected for analysis and verification. This paper will present verification results comparing the NWS MIA operational WRF runs to the SPORT experimental runs, and highlight any substantial differences noted in the predicted mesoscale phenomena for specific cases.

Comparison of different synthetic 5-min rainfall time series regarding their suitability for urban drainage modelling

NASA Astrophysics Data System (ADS)

van der Heijden, Sven; Callau Poduje, Ana; Müller, Hannes; Shehu, Bora; Haberlandt, Uwe; Lorenz, Manuel; Wagner, Sven; Kunstmann, Harald; Müller, Thomas; Mosthaf, Tobias; Bárdossy, András

2015-04-01

For the design and operation of urban drainage systems with numerical simulation models, long, continuous precipitation time series with high temporal resolution are necessary. Suitable observed time series are rare. As a result, intelligent design concepts often use uncertain or unsuitable precipitation data, which renders them uneconomic or unsustainable. An expedient alternative to observed data is the use of long, synthetic rainfall time series as input for the simulation models. Within the project SYNOPSE, several different methods to generate synthetic precipitation data for urban drainage modelling are advanced, tested, and compared. The presented study compares four different approaches of precipitation models regarding their ability to reproduce rainfall and runoff characteristics. These include one parametric stochastic model (alternating renewal approach), one non-parametric stochastic model (resampling approach), one downscaling approach from a regional climate model, and one disaggregation approach based on daily precipitation measurements. All four models produce long precipitation time series with a temporal resolution of five minutes. The synthetic time series are first compared to observed rainfall reference time series. Comparison criteria include event based statistics like mean dry spell and wet spell duration, wet spell amount and intensity, long term means of precipitation sum and number of events, and extreme value distributions for different durations. Then they are compared regarding simulated discharge characteristics using an urban hydrological model on a fictitious sewage network. First results show a principal suitability of all rainfall models but with different strengths and weaknesses regarding the different rainfall and runoff characteristics considered.

Comparison of Diurnal Characteristics of GPM-IMERG Precipitation Products with Hourly Rain Gauge Observations and TRMM-TMPA Products over Mainland China

NASA Astrophysics Data System (ADS)

Li, R.; Wang, K.; QI, D.

2017-12-01

The next generation global high resolutions precipitation products, the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) provide new insights into the global hydrometeorology studies. Although there are some previous works to evaluate it on daily scale or above, its performance on sub-daily scale is still limited. This study evaluates the diurnal characteristics of the half-hourly IMERG product with the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) data and the hourly rain gauge data from approximately 50000 automatic weather station (AWS) in China during 2014-2016. The results show that IMERG can roughly capture the diurnal cycle of precipitation amount with serial correlation for eight sub-regions ranging from 0.63 to 0.97, but less agreed in frequency (from 0.21 to 0.90) and intensity (from -0.22 to 0.83). IMERG can generally capture the nocturnal and early morning peak of amount, frequency and intensity, which it's a known issue unsolved by TMPA, partly due to the better detection of light rain in the morning. However as for the afternoon precipitation, overestimation of amount and frequency and underestimation of intensity still exist in IMERG product, which probably result from the overestimation of light and moderate rain. IMERG shows large bias in late morning (0900-1100 Beijing Time) and mid evening (2000-2200 Beijing Time). All these results highlight the cautions when using the IMERG sub-daily product and indicate the necessity of improved retrieval algorithm in the future.

A statistical analysis of the daily streamflow hydrograph

NASA Astrophysics Data System (ADS)

Kavvas, M. L.; Delleur, J. W.

1984-03-01

In this study a periodic statistical analysis of daily streamflow data in Indiana, U.S.A., was performed to gain some new insight into the stochastic structure which describes the daily streamflow process. This analysis was performed by the periodic mean and covariance functions of the daily streamflows, by the time and peak discharge -dependent recession limb of the daily streamflow hydrograph, by the time and discharge exceedance level (DEL) -dependent probability distribution of the hydrograph peak interarrival time, and by the time-dependent probability distribution of the time to peak discharge. Some new statistical estimators were developed and used in this study. In general features, this study has shown that: (a) the persistence properties of daily flows depend on the storage state of the basin at the specified time origin of the flow process; (b) the daily streamflow process is time irreversible; (c) the probability distribution of the daily hydrograph peak interarrival time depends both on the occurrence time of the peak from which the inter-arrival time originates and on the discharge exceedance level; and (d) if the daily streamflow process is modeled as the release from a linear watershed storage, this release should depend on the state of the storage and on the time of the release as the persistence properties and the recession limb decay rates were observed to change with the state of the watershed storage and time. Therefore, a time-varying reservoir system needs to be considered if the daily streamflow process is to be modeled as the release from a linear watershed storage.

Effects of climate change on phenology in two French LTER (Alps and Brittany) for the period 1998-2009

NASA Astrophysics Data System (ADS)

Perrimond, B.; Bigot, S.; Quénol, H.; Spielgelberger, T.; Baudry, J.

2012-04-01

Climate and vegetation are linked all over the world. In this study, we work on a seasonal weather classification based on air temperature and precipitation to deduce a link with different phenological stage (greening up, senescence, ...) over a 12 year period (1998-2009) for two different domains in France (Alps and Brittany). In temperate land, the main climatic variable with a potential effect on vegetation is the mean temperature followed by the rainfall deficit. A better understanding in season and their climatic characteristic is need to establish link between climate and phenology; so a weather classification is proposed based on empirical orthogonal functions and ascending hierarchical classification on atmospheric variables. This classification allows us to exhibit the inter-annual and intra-seasonal climatic spatiotemporal variability for both experimental site. Relationships between climate and phenology consist in a comparison between advance and delay in phenological stage and weather type issue from the classification. Experiment field are two french Long Term Ecological Research (LTER). The first one (LTER 'Alps' ) have mountain characteristics about 1000 to 4780 m ASL, ~65% of forest occupation ; the second one (LTER Armorique) is an Atlantic coastal landscape, 0-360 m ASL, ~70% of agricultural field. Climatic data are SAFRAN-France reanalysis which are developed to run SVAT model and come from the French meteorological service 'Météo-France'. All atmospheric variable needed to run a hydrological model are available (air temperature, rainfall/snowfall, wind speed, relative humidity, incoming/outcoming radiation) at a 8-8 km2 space resolution and with a daily time resolution. The phenological data are extracted from SPOT-VGT product 1-1 km2 space resolution and 10 days time resolution) by time series analysis process. Such of study is particularly important to understand relationships between environmental and ecological variables and it will allow to better predict ecological reaction under climate change constraint.

Development of an Objective High Spatial Resolution Soil Moisture Index

NASA Astrophysics Data System (ADS)

Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

2015-12-01

Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective analyses, and application examples.

Aspects of quality insurance in digitizing historical climate data in Germany

NASA Astrophysics Data System (ADS)

Mächel, H.; Behrends, J.; Kapala, A.

2010-09-01

This contribution presents some of the problems and offers solutions regarding the digitization of historical meteorological data, and explains the need for verification and quality control. For the assessment of changes in climate extremes, long-term and complete observational records with a high temporal resolution are needed. However, in most countries, including Germany, such climate data are rare. Therefore, in 2005, the German Weather Service launched a project to inventory and digitize historical daily climatic records in cooperation with the Meteorological Institute of the University of Bonn. Experience with Optical Character Recognition (OCR) show that it is only of very limited use, as even printed tables (e.g. yearbooks) are not sufficiently recognized (10-20% error). In hand-written records, the recognition rate is about 50%. By comparing daily and monthly values, it is possible to auto-detect errors, but they can not be automatically corrected, since there is often more than one error per month. These erroneous data must then be controlled manually on an individual basis, which is significantly more error-prone than direct manual input. Therefore, both precipitation and climate station data are digitized manually. The time required to digitize one year of precipitation data (including the recording of daily precipitation amount and type, snow amount and type, and weather events such as thunder storms, fog, etc.) is equivalent to about five hours for one year of data. This involves manually typing, reformatting and quality control of the digitized data, as well as creating a digital photograph. For climate stations with three observations per day, the working time is 30-50 hours for one year of data, depending on the number of parameters and the condition of the documents. Several other problems occur when creating the digital records from historical observational data, some of which are listed below. Older records often used varying units and different conventions. For example, a value of 100 was added to the observed temperatures to avoid negative values. Furthermore, because standardization of the observations was very low when measurements began up to 200 years ago, the data often reflect a greater part of non-climatic influences. Varying daily observation times make it difficult to calculate a representative daily value. Even unconventional completed tables cost labor and requires experienced and trained staff. Data homogenization as well as both manual and automatic quality control may address some of these problems.

Are satellite products good proxies for gauge precipitation over Singapore?

NASA Astrophysics Data System (ADS)

Hur, Jina; Raghavan, Srivatsan V.; Nguyen, Ngoc Son; Liong, Shie-Yui

2018-05-01

The uncertainties in two high-resolution satellite precipitation products (TRMM 3B42 v7.0 and GSMaP v5.222) were investigated by comparing them against rain gauge observations over Singapore on sub-daily scales. The satellite-borne precipitation products are assessed in terms of seasonal, monthly and daily variations, the diurnal cycle, and extreme precipitation over a 10-year period (2000-2010). Results indicate that the uncertainties in extreme precipitation is higher in GSMaP than in TRMM, possibly due to the issues such as satellite merging algorithm, the finer spatio-temporal scale of high intensity precipitation, and the swath time of satellite. Such discrepancies between satellite-borne and gauge-based precipitations at sub-daily scale can possibly lead to distorting analysis of precipitation characteristics and/or application model results. Overall, both satellite products are unable to capture the observed extremes and provide a good agreement with observations only at coarse time scales. Also, the satellite products agree well on the late afternoon maximum and heavier rainfall of gauge-based data in winter season when the Intertropical Convergence Zone (ITCZ) is located over Singapore. However, they do not reproduce the gauge-observed diurnal cycle in summer. The disagreement in summer could be attributed to the dominant satellite overpass time (about 14:00 SGT) later than the diurnal peak time (about 09:00 SGT) of gauge precipitation. From the analyses of extreme precipitation indices, it is inferred that both satellite datasets tend to overestimate the light rain and frequency but underestimate high intensity precipitation and the length of dry spells. This study on quantification of their uncertainty is useful in many aspects especially that these satellite products stand scrutiny over places where there are no good ground data to be compared against. This has serious implications on climate studies as in model evaluations and in particular, climate model simulated future projections, when information on precipitation extremes need to be reliable as they are highly crucial for adaptation and mitigation.

Rainfall erosivity in Europe.

PubMed

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Klik, Andreas; Rousseva, Svetla; Tadić, Melita Perčec; Michaelides, Silas; Hrabalíková, Michaela; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Beguería, Santiago; Alewell, Christine

2015-04-01

Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha(-1) h(-1) yr(-1), with the highest values (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

VISTA - A Constellation for Real Time Regional Imaging

NASA Astrophysics Data System (ADS)

Meerman, Max; Boland, Lee; da Silva Curiel, Alex; Sweeting, Martin, , Sir

2002-01-01

The role of satellites in medium and high-resolution reconnaissance of the Earth's surface has been well demonstrated in recent years through missions such as Landsat, SPOT, IKONOS, ImageSat and Quickbird. The market for such data products is well served and likely to become more competitive with further very-high-resolution missions. Whereas commercial markets have concentrated on enhancing resolution, the small satellite sector has concentrated on reducing the cost of data products, and the development of systems providing niche services. One such EO requirement that can be well met by smaller satellites is the need for higher temporal resolution, as this typically requires a large number of satellites to operate as a constellation - thus far financially impractical using conventional EO satellites. Surrey is currently engaged in building its first constellation that will provide daily global coverage at moderate resolution (32-metre GSD and 600km swath) in three spectral bands. Targeted at providing timely quick-look data products for disaster mitigation and monitoring, the constellation comprises 7 satellites in a single orbital plane. Each satellite has a wide swath so that successive satellites progressively cover the entire globe in a single day. The Vista constellation takes this concept a step further, and is proposed for applications requiring near-continuous surveillance of regional activity. By introducing a multiple plane constellation of small Earth observation satellites, it is possible to monitor continuously selected regions anywhere on the globe. The paper describes the system trades and outlines the scope of the performance that could be obtained from such a system. A cost model illustrates that the balance between launch and space segment costs must be reached by considering suitable replacement strategies, and that the system is highly sensitive to requirement creep. Finally, it is shown that the use of cost effective, small satellites leads to solutions previously thought to be financially beyond sensible reach.

New method for estimating daily global solar radiation over sloped topography in China

NASA Astrophysics Data System (ADS)

Shi, Guoping; Qiu, Xinfa; Zeng, Yan

2018-03-01

A new scheme for the estimation of daily global solar radiation over sloped topography in China is developed based on the Iqbal model C and MODIS cloud fraction. The effects of topography are determined using a digital elevation model. The scheme is tested using observations of solar radiation at 98 stations in China, and the results show that the mean absolute bias error is 1.51 MJ m-2 d-1 and the mean relative absolute bias error is 10.57%. Based on calculations using this scheme, the distribution of daily global solar radiation over slopes in China on four days in the middle of each season (15 January, 15 April, 15 July and 15 October 2003) at a spatial resolution of 1 km × 1 km are analyzed. To investigate the effects of topography on global solar radiation, the results determined in four mountains areas (Tianshan, Kunlun Mountains, Qinling, and Nanling) are discussed, and the typical characteristics of solar radiation over sloped surfaces revealed. In general, the new scheme can produce reasonable characteristics of solar radiation distribution at a high spatial resolution in mountain areas, which will be useful in analyses of mountain climate and planning for agricultural production.

Validation of satellite based precipitation over diverse topography of Pakistan

NASA Astrophysics Data System (ADS)

Iqbal, Muhammad Farooq; Athar, H.

2018-03-01

This study evaluates the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product data with 0.25° × 0.25° spatial and post-real-time 3 h temporal resolution using point-based Surface Precipitation Gauge (SPG) data from 40 stations, for the period 1998-2013, and using gridded Asian Precipitation ˗ Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) data abbreviated as APH data with 0.25° × 0.25° spatial and daily temporal resolution for the period 1998-2007, over vulnerable and data sparse regions of Pakistan (24-37° N and 62-75° E). To evaluate the performance of TMPA relative to SPG and APH, four commonly used statistical indicator metrics including Mean Error (ME), Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Correlation Coefficient (CC) are employed on daily, monthly, seasonal as well as on annual timescales. The TMPA slightly overestimated both SPG and APH at daily, monthly, and annual timescales, however close results were obtained between TMPA and SPG as compared to those between TMPA and APH, on the same timescale. The TMPA overestimated both SPG and APH during the Pre-Monsoon and Monsoon seasons, whereas it underestimated during the Post-Monsoon and Winter seasons, with different magnitudes. Agreement between TMPA and SPG was good in plain and medium elevation regions, whereas TMPA overestimated APH in 31 stations. The magnitudes of MAE and RMSE were high at daily timescale as compared to monthly and annual timescales. Relatively large MAE was observed in stations located over high elevation regions, whereas minor MAE was recorded in plain area stations at daily, monthly, and annual timescales. A strong positive linear relationship between TMPA and SPG was established at monthly (0.98), seasonal (0.93 to 0.98) and annual (0.97) timescales. Precipitation increased with the increase of elevation, and not only elevation but latitude also affected the intensity and amount of precipitation in Pakistan. It is evident that TMPA overestimates SPG in some regions and seasons and underestimates in other regions and seasons. It is thus determined from the current study that TMPA gives better results on annual, seasonal, and monthly timescales as compared to daily timescale. The TMPA might be used in all the four seasons including Winter, Pre-Monsoon, Monsoon, and Post-Monsoon. The TMPA mostly underestimates both SPG and APH in high elevation regions, whereas in plain and medium elevation regions it gives better results. This study concludes that TMPA can be a good substitute of SPG for water resource management in plain and medium elevation regions in central and northern parts of Pakistan, during all four seasons.

An empirical method that separates irreversible stem radial growth from bark water content changes in trees: theory and case studies

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

Mencuccini, Maurizio; Salmon, Yann; Mitchell, Patrick

Substantial uncertainty surrounds our knowledge of tree stem growth, with some of the most basic questions, such as when stem radial growth occurs through the daily cycle, still unanswered. Here, we employed high-resolution point dendrometers, sap flow sensors, and developed theory and statistical approaches, to devise a novel method separating irreversible radial growth from elastic tension-driven and elastic osmotically driven changes in bark water content. We tested this method using data from five case study species. Experimental manipulations, namely a field irrigation experiment on Scots pine and a stem girdling experiment on red forest gum trees, were used to validatemore » the theory. Time courses of stem radial growth following irrigation and stem girdling were consistent with a-priori predictions. Patterns of stem radial growth varied across case studies, with growth occurring during the day and/or night, consistent with the available literature. Importantly, our approach provides a valuable alternative to existing methods, as it can be approximated by a simple empirical interpolation routine that derives irreversible radial growth using standard regression techniques. In conclusion, our novel method provides an improved understanding of the relative source–sink carbon dynamics of tree stems at a sub-daily time scale.« less

An empirical method that separates irreversible stem radial growth from bark water content changes in trees: theory and case studies.

PubMed

Mencuccini, Maurizio; Salmon, Yann; Mitchell, Patrick; Hölttä, Teemu; Choat, Brendan; Meir, Patrick; O'Grady, Anthony; Tissue, David; Zweifel, Roman; Sevanto, Sanna; Pfautsch, Sebastian

2017-02-01

Substantial uncertainty surrounds our knowledge of tree stem growth, with some of the most basic questions, such as when stem radial growth occurs through the daily cycle, still unanswered. We employed high-resolution point dendrometers, sap flow sensors, and developed theory and statistical approaches, to devise a novel method separating irreversible radial growth from elastic tension-driven and elastic osmotically driven changes in bark water content. We tested this method using data from five case study species. Experimental manipulations, namely a field irrigation experiment on Scots pine and a stem girdling experiment on red forest gum trees, were used to validate the theory. Time courses of stem radial growth following irrigation and stem girdling were consistent with a-priori predictions. Patterns of stem radial growth varied across case studies, with growth occurring during the day and/or night, consistent with the available literature. Importantly, our approach provides a valuable alternative to existing methods, as it can be approximated by a simple empirical interpolation routine that derives irreversible radial growth using standard regression techniques. Our novel method provides an improved understanding of the relative source-sink carbon dynamics of tree stems at a sub-daily time scale. © 2016 The Authors Plant, Cell & Environment Published by John Wiley & Sons Ltd.

Post-wildfire summer greening depends on winter snowpack

NASA Astrophysics Data System (ADS)

Wilson, A.; Nolin, A. W.

2017-12-01

Forested, mountain landscapes in the Pacific Northwest (PNW) are changing at an unprecedented rate, largely due to shifts in the regional climate regime. Documented climatic trends include increasing wildfire frequency and intensity and an increasingly ephemeral snowpack, especially at moderate elevations. One relationship that has yet to be studied thoroughly is the dependence of post-wildfire forest recovery on winter snowpack. This study will correlate winter snowpack with summer greenness in the context of 15 recent severe wildfires across the PNW. Winter snow water equivalent will be estimated using a new Snow Cover Frequency (SCF) metric derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover product. Summer forest greenness will be assessed using the Enhanced Vegetation Index (EVI), also derived from daily MODIS reflectance data. Regression tree analysis will be employed to characterize the relative importance of snowpack, elevation, slope, aspect, soil texture, and summer precipitation to summer greenness. Using findings from the regression tree analysis, the most critical physiographic factors will frame a multivariate time series spanning the 5 years pre-wildfire and 5 years post-wildfire in an effort to illustrate how the snowpack-revegetation relationship persists over time. As northwestern mountainous forests become more vulnerable to wildfire activity, it will be vital to continue deepening our understanding of how snowpack matters to post-wildfire forest recovery.

An empirical method that separates irreversible stem radial growth from bark water content changes in trees: theory and case studies

DOE PAGES

Mencuccini, Maurizio; Salmon, Yann; Mitchell, Patrick; ...

2017-11-12

Substantial uncertainty surrounds our knowledge of tree stem growth, with some of the most basic questions, such as when stem radial growth occurs through the daily cycle, still unanswered. Here, we employed high-resolution point dendrometers, sap flow sensors, and developed theory and statistical approaches, to devise a novel method separating irreversible radial growth from elastic tension-driven and elastic osmotically driven changes in bark water content. We tested this method using data from five case study species. Experimental manipulations, namely a field irrigation experiment on Scots pine and a stem girdling experiment on red forest gum trees, were used to validatemore » the theory. Time courses of stem radial growth following irrigation and stem girdling were consistent with a-priori predictions. Patterns of stem radial growth varied across case studies, with growth occurring during the day and/or night, consistent with the available literature. Importantly, our approach provides a valuable alternative to existing methods, as it can be approximated by a simple empirical interpolation routine that derives irreversible radial growth using standard regression techniques. In conclusion, our novel method provides an improved understanding of the relative source–sink carbon dynamics of tree stems at a sub-daily time scale.« less

Austrian Daily Climate Data Rescue and Quality Control

NASA Astrophysics Data System (ADS)

Jurkovic, A.; Lipa, W.; Adler, S.; Albenberger, J.; Lechner, W.; Swietli, R.; Vossberg, I.; Zehetner, S.

2010-09-01

Checked climate datasets are a "conditio sine qua non" for all projects that are relevant for environment and climate. In the framework of climate change studies and analysis it is essential to work with quality controlled and trustful data. Furthermore these datasets are used as input for various simulation models. In regard to investigations of extreme events, like strong precipitation periods, drought periods and similar ones we need climate data in high temporal resolution (at least in daily resolution). Because of the historical background - during Second World War the majority of our climate sheets were sent to Berlin, where the historical sheets were destroyed by a bomb attack and so important information got lost - only several climate sheets, mostly duplicates, before 1939 are available and stored in our climate data archive. In 1970 the Central Institute for Meteorology and Geodynamics in Vienna started a first attempt to digitize climate data by means of punch cards. With the introduction of a routinely climate data quality control in 1984 we can speak of high-class-checked daily data (finally checked data, quality flag 6). Our group is working on the processing of digitization and quality control of the historical data for the period 1872 to 1983 for 18 years. Since 2007 it was possible to intensify the work (processes) in the framework of an internal project, namely Austrian Climate Data Rescue and Quality Control. The aim of this initiative was - and still is - to supply daily data in an outstanding good and uniform quality. So this project is a kind of pre-project for all scientific projects which are working with daily data. In addition to routine quality checks (that are running since 1984) using the commercial Bull Software we are testing our data with additional open source software, namely ProClim.db. By the use of this spatial and statistical test procedure, the elements air temperature and precipitation - for several sites in Carinthia - could already be checked, flagged and corrected. Checking the output (so called- error list) of ProClim is very time consuming and needs trained staff; however, in last instance it is necessary. Due to the guideline "Your archive is your business card for quality" the sub-project NEW ARCHIVE was initialized and started at the end of 2009. Our paper archive contains historical, up to 150 year-old, climate sheets that are valuable cultural assets. Unfortunately the storage of these historical and actual data treasures turned out to be more than suboptimal (insufficient protection against dust, dirt, humidity and light incidence). Because of this fact a concept for a new storage system and archive database was generated and already partly realized. In a nutshell this presentation shows on the one hand the importance of recovering historical climate sheets for climate change research - even if it is exhausting and time consuming - and gives on the other hand a general overview of used quality control procedures at our institute.

Estimation of Actual Crop ET of Paddy Using the Energy Balance Model SMARET and Validation with Field Water Balance Measurements and a Crop Growth Model (ORYZA)

NASA Astrophysics Data System (ADS)

Nallasamy, N. D.; Muraleedharan, B. V.; Kathirvel, K.; Narasimhan, B.

2014-12-01

Sustainable management of water resources requires reliable estimates of actual evapotranspiration (ET) at fine spatial and temporal resolution. This is significant in the case of rice based irrigation systems, one of the major consumers of surface water resources and where ET forms a major component of water consumption. However huge tradeoff in the spatial and temporal resolution of satellite images coupled with lack of adequate number of cloud free images within a growing season act as major constraints in deriving ET at fine spatial and temporal resolution using remote sensing based energy balance models. The scale at which ET is determined is decided by the spatial and temporal scale of Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), which form inputs to energy balance models. In this context, the current study employed disaggregation algorithms (NL-DisTrad and DisNDVI) to generate time series of LST and NDVI images at fine resolution. The disaggregation algorithms aimed at generating LST and NDVI at finer scale by integrating temporal information from concurrent coarse resolution data and spatial information from a single fine resolution image. The temporal frequency of the disaggregated images is further improved by employing composite images of NDVI and LST in the spatio-temporal disaggregation method. The study further employed half-hourly incoming surface insolation and outgoing long wave radiation obtained from the Indian geostationary satellite (Kalpana-1) to convert the instantaneous ET into daily ET and subsequently to the seasonal ET, thereby improving the accuracy of ET estimates. The estimates of ET were validated with field based water balance measurements carried out in Gadana, a subbasin predominated by rice paddy fields, located in Tamil Nadu, India.

Intercomparison of PERSIANN-CDR and TRMM-3B42V7 precipitation estimates at monthly and daily time scales

NASA Astrophysics Data System (ADS)

Katiraie-Boroujerdy, Pari-Sima; Akbari Asanjan, Ata; Hsu, Kuo-lin; Sorooshian, Soroosh

2017-09-01

In the first part of this paper, monthly precipitation data from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Tropical Rainfall Measuring Mission 3B42 algorithm Version 7 (TRMM-3B42V7) are evaluated over Iran using the Generalized Three-Cornered Hat (GTCH) method which is self-sufficient of reference data as input. Climate Data Unit (CRU) is added to the GTCH evaluations as an independent gauge-based dataset thus, the minimum requirement of three datasets for the model is satisfied. To ensure consistency of all datasets, the two satellite products were aggregated to 0.5° spatial resolution, which is the minimum resolution of CRU. The results show that the PERSIANN-CDR has higher Signal to Noise Ratio (SNR) than TRMM-3B42V7 for the monthly rainfall estimation, especially in the northern half of the country. All datasets showed low SNR in the mountainous area of southwestern Iran, as well as the arid parts in the southeast region of the country. Additionally, in order to evaluate the efficacy of PERSIANN-CDR and TRMM-3B42V7 in capturing extreme daily-precipitation amounts, an in-situ rain-gauge dataset collected by the Islamic Republic of the Iran Meteorological Organization (IRIMO) was employed. Given the sparsity of the rain gauges, only 0.25° pixels containing three or more gauges were used for this evaluation. There were 228 such pixels where daily and extreme rainfall from PERSIANN-CDR and TRMM-3B42V7 could be compared. However, TRMM-3B42V7 overestimates most of the intensity indices (correlation coefficients; R between 0.7648-0.8311, Root Mean Square Error; RMSE between 3.29mm/day-21.2mm/5day); PERSIANN-CDR underestimates these extremes (R between 0.6349-0.7791 and RMSE between 3.59mm/day-30.56mm/5day). Both satellite products show higher correlation coefficients and lower RMSEs for the annual mean of consecutive dry spells than wet spells. The results show that TRMM-3B42V7 can capture the annual mean of the absolute indices (the number of wet days in which daily precipitation > 10 mm, 20 mm) better than PERSIANN-CDR. The results of daily evaluations show that the similarity of Empirical Cumulative Density Function (ECDF) of satellite products and IRIMO gauges daily precipitation, as well as dry spells with different thresholds in some selected pixels (include at least five gauges), are significant. The results also indicate that ECDFs become more significant when threshold increases. In terms of regional analyses, the higher SNR of the products on monthly (based on the GTCH method) and daily evaluations (significant ECDFs) is mostly consistent.

The nitrate response of a lowland catchment and groundwater travel times

NASA Astrophysics Data System (ADS)

van der Velde, Ype; Rozemeijer, Joachim; de Rooij, Gerrit; van Geer, Frans

2010-05-01

Intensive agriculture in lowland catchments causes eutrophication of downstream waters. To determine effective measures to reduce the nutrient loads from upstream lowland catchments, we need to understand the origin of long-term and daily variations in surface water nutrient concentrations. Surface water concentrations are often linked to travel time distributions of water passing through the saturated and unsaturated soil of the contributing catchment. This distribution represents the contact time over which sorption, desorption and degradation takes place. However, travel time distributions are strongly influenced by processes like tube drain flow, overland flow and the dynamics of draining ditches and streams and therefore exhibit strong daily and seasonal variations. The study we will present is situated in the 6.6 km2 Hupsel brook catchment in The Netherlands. In this catchment nitrate and chloride concentrations have been intensively monitored for the past 26 years under steadily decreasing agricultural inputs. We described the complicated dynamics of subsurface water fluxes as streams, ditches and tube drains locally switch between active or passive depending on the ambient groundwater level by a groundwater model with high spatial and temporal resolutions. A transient particle tracking approach is used to derive a unique catchment-scale travel time distribution for each day during the 26 year model period. These transient travel time distributions are not smooth distributions, but distributions that are strongly spiked reflecting the contribution of past rainfall events to the current discharge. We will show that a catchment-scale mass response function approach that only describes catchment-scale mixing and degradation suffices to accurately reproduce observed chloride and nitrate surface water concentrations as long as the mass response functions include the dynamics of travel time distributions caused by the highly variable connectivity of the surface water network.

Effect of spatial averaging on multifractal properties of meteorological time series

NASA Astrophysics Data System (ADS)

Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika

2016-04-01

Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.

Predictive performance of rainfall thresholds for shallow landslide triggering in Switzerland from daily gridded precipitation data

NASA Astrophysics Data System (ADS)

Leonarduzzi, E.; Molnar, P.; McArdell, B. W.

2017-12-01

In Switzerland floods are responsible for most of the damage caused by rainfall-triggered natural hazards (89%), followed by landslides (6%, almost 600 M USD) as reported in Hilker et al. (2009) for the period 1972-2007. A high-resolution gridded daily precipitation dataset is combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds that lead to landsliding in Switzerland. First triggering rainfall and landslides are co-located obtaining the distributions of triggering and non-triggering rainfall event properties at the scale of the precipitation data (2*2 km2) and considering 1 day as the interarrival time to separate events. Then rainfall thresholds are obtained by maximizing true positives (accurate predictions) while minimizing false negatives (false alarms), using the True Skill Statistic. The best predictive performance is obtained by the intensity-duration ID threshold curve, followed by peak daily intensity (Imax) and mean event intensity (Imean). Event duration by itself has very low predictive power. In addition to country-wide thresholds, local ones are also defined by regionalization based on surface erodibility and local long-term climate (mean daily precipitation). Different Imax thresholds are determined for each of the regions separately. It is found that wetter local climate and lower erodibility lead to significantly higher rainfall thresholds required to trigger landslides. However, the improvement in model performance due to regionalization is marginal and much lower than what can be achieved by having a high quality landslide database. In order to validate the performance of the Imax rainfall threshold model, reference cases will be presented in which the landslide locations and timing are randomized and the landslide sample size is reduced. Jack-knife and cross-validation experiments demonstrate that the model is robust. The results highlight the potential of using rainfall I-D threshold curves and Imax threshold values for predicting the occurrence of landslides on a country or regional scale even with daily precipitation data, with possible applications in landslide warning systems.

Influence of Observed Diurnal Cycles of Aerosol Optical Depth on Aerosol Direct Radiative Effect

NASA Technical Reports Server (NTRS)

Arola, A.; Eck, T. F.; Huttunen, J.; Lehtinen, K. E. J.; Lindfors, A. V.; Myhre, G.; Smirinov, A.; Tripathi, S. N.; Yu, H.

2013-01-01

The diurnal variability of aerosol optical depth (AOD) can be significant, depending on location and dominant aerosol type. However, these diurnal cycles have rarely been taken into account in measurement-based estimates of aerosol direct radiative forcing (ADRF) or aerosol direct radiative effect (ADRE). The objective of our study was to estimate the influence of diurnal aerosol variability at the top of the atmosphere ADRE estimates. By including all the possible AERONET sites, we wanted to assess the influence on global ADRE estimates. While focusing also in more detail on some selected sites of strongest impact, our goal was to also see the possible impact regionally.We calculated ADRE with different assumptions about the daily AOD variability: taking the observed daily AOD cycle into account and assuming diurnally constant AOD. Moreover, we estimated the corresponding differences in ADREs, if the single AOD value for the daily mean was taken from the the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra or Aqua overpass times, instead of accounting for the true observed daily variability. The mean impact of diurnal AOD variability on 24 h ADRE estimates, averaged over all AERONET sites, was rather small and it was relatively small even for the cases when AOD was chosen to correspond to the Terra or Aqua overpass time. This was true on average over all AERONET sites, while clearly there can be much stronger impact in individual sites. Examples of some selected sites demonstrated that the strongest observed AOD variability (the strongest morning afternoon contrast) does not typically result in a significant impact on 24 h ADRE. In those cases, the morning and afternoon AOD patterns are opposite and thus the impact on 24 h ADRE, when integrated over all solar zenith angles, is reduced. The most significant effect on daily ADRE was induced by AOD cycles with either maximum or minimum AOD close to local noon. In these cases, the impact on 24 h ADRE was typically around 0.1-0.2W/sq m (both positive and negative) in absolute values, 5-10% in relative ones.

Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2.

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

Thornton, Peter E; Thornton, Michele M; Mayer, Benjamin W

More information: http://daymet.ornl.gov Presenter: Ranjeet Devarakonda Environmental Sciences Division Oak Ridge National Laboratory (ORNL) Daymet: Daily Surface Weather Data and Climatological Summaries provides gridded estimates of daily weather parameters for North America, including daily continuous surfaces of minimum and maximum temperature, precipitation occurrence and amount, humidity, shortwave radiation, snow water equivalent, and day length. The current data product (Version 2) covers the period January 1, 1980 to December 31, 2013 [1]. The prior product (Version 1) only covered from 1980-2008. Data are available on a daily time step at a 1-km x 1-km spatial resolution in Lambert Conformal Conic projectionmore » with a spatial extent that covers the conterminous United States, Mexico, and Southern Canada as meteorological station density allows. Daymet data can be downloaded from 1) the ORNL Distributed Active Archive Center (DAAC) search and order tools (http://daac.ornl.gov/cgi-bin/cart/add2cart.pl?add=1219) or directly from the DAAC FTP site (http://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1219) and 2) the Single Pixel Tool [2] and THREDDS (Thematic Real-time Environmental Data Services) Data Server [3]. The Single Pixel Data Extraction Tool allows users to enter a single geographic point by latitude and longitude in decimal degrees. A routine is executed that translates the (lon, lat) coordinates into projected Daymet (x,y) coordinates. These coordinates are used to access the Daymet database of daily-interpolated surface weather variables. Daily data from the nearest 1 km x 1 km Daymet grid cell are extracted from the database and formatted as a table with one column for each Daymet variable and one row for each day. All daily data for selected years are returned as a single (long) table, formatted for display in the browser window. At the top of this table is a link to the same data in a simple comma-separated text format, suitable for import into a spreadsheet or other data analysis software. The Single Pixel Data Extraction Tool also provides the option to download multiple coordinates programmatically. A multiple extractor script is freely available to download at http://daymet.ornl.gov/files/daymet.zip. The ORNL DAAC s THREDDS data server (TDS) provides customized visualization and access to Daymet time series of North American mosaics. Users can subset and download Daymet data via a variety of community standards, including OPeNDAP, NetCDF Subset service, and Open Geospatial Consortium (OGC) Web Map/Coverage Service. The ORNL DAAC TDS also exposes Daymet metadata through its ncISO service to facilitate harvesting Daymet metadata records into 3rd party catalogs. References: [1] Thornton, P.E., M.M. Thornton, B.W. Mayer, N. Wilhelmi, Y. Wei, R. Devarakonda, and R.B. Cook. 2014. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 2. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA. [2] Devarakonda R., et al. 2012. Daymet: Single Pixel Data Extraction Tool. Available on-line [http://daymet.ornl.go/singlepixel.html]. [3] Wei Y., et al. 2014. Daymet: Thematic Real-time Environmental Data Services. Available on-line [http://daymet.ornl.gov/thredds_tiles.html].« less

Measurement of time processing ability and daily time management in children with disabilities.

PubMed

Janeslätt, Gunnel; Granlund, Mats; Kottorp, Anders

2009-01-01

Improvement is needed in methods for planning and evaluating interventions designed to facilitate daily time management for children with intellectual disability, Asperger syndrome, or other developmental disorders. The aim of this study was to empirically investigate the hypothesized relation between children's time processing ability (TPA), daily time management, and self-rated autonomy. Such a relationship between daily time management and TPA may support the idea that TPA is important for daily time management and that children with difficulties in TPA might benefit from intervention aimed at improving daily time management. Participants were children aged 6 to 11 years with dysfunctions such as attention-deficit/hyperactivity disorder, autism, or physical or intellectual disabilities (N = 118). TPA was measured with the instrument KaTid. All data were transformed to interval measures using applications of Rasch models and then further analysed with correlation and regression analysis. The results demonstrate a moderate significant relation between the parents' ratings of daily time management and TPA of the children, and between the self-rating of autonomy and TPA. There was also a significant relation between self-ratings of autonomy and the parents' rating of the children's daily time management. Parents' ratings of their children's daily time management explain 25% of the variation in TPA, age of the children explains 22%, while the child's self-rating of autonomy can explain 9% of the variation in TPA. The three variables together explain 38% of the variation in TPA. The results indicate the viability of the instrument for assessing TPA also in children with disabilities and that the ability measured by KaTid is relevant for daily time management. TPA seems to be a factor for children's daily time management that needs to be taken into consideration when planning and evaluating interventions designed to facilitate everyday functioning for children with cognitive impairments. The findings add to the increasing knowledge base about children with time processing difficulties and contribute to better methods aimed at improving these children's daily time management. Further research is needed to examine if there are differences in TPA related to specific diagnosis or other child characteristics.

The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote-sensing-based evapotranspiration algorithms

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

Michel, D.; Jimenez, C.; Miralles, D. G.

The WAter Cycle Multi-mission Observation Strategy – EvapoTranspiration (WACMOS-ET) project has compiled a forcing data set covering the period 2005–2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run four established ET algorithms: the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman–Monteith algorithm from the MODerate resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in situ meteorological data from 24 FLUXNET towers were used to force the models, with results from both forcing sets compared tomore » tower-based flux observations. Model performance was assessed on several timescales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement with the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements ( R 2 = 0.67), the agreement of the satellite-based ET estimates is only marginally lower ( R 2 = 0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. In conclusion, an extension of the evaluation to a larger selection of 85 towers (model inputs resampled to a common grid to facilitate global estimates) confirmed the original findings.« less

The WACMOS-ET project – Part 1: Tower-scale evaluation of four remote-sensing-based evapotranspiration algorithms

DOE PAGES

Michel, D.; Jimenez, C.; Miralles, D. G.; ...

2016-02-23

The WAter Cycle Multi-mission Observation Strategy – EvapoTranspiration (WACMOS-ET) project has compiled a forcing data set covering the period 2005–2007 that aims to maximize the exploitation of European Earth Observations data sets for evapotranspiration (ET) estimation. The data set was used to run four established ET algorithms: the Priestley–Taylor Jet Propulsion Laboratory model (PT-JPL), the Penman–Monteith algorithm from the MODerate resolution Imaging Spectroradiometer (MODIS) evaporation product (PM-MOD), the Surface Energy Balance System (SEBS) and the Global Land Evaporation Amsterdam Model (GLEAM). In addition, in situ meteorological data from 24 FLUXNET towers were used to force the models, with results from both forcing sets compared tomore » tower-based flux observations. Model performance was assessed on several timescales using both sub-daily and daily forcings. The PT-JPL model and GLEAM provide the best performance for both satellite- and tower-based forcing as well as for the considered temporal resolutions. Simulations using the PM-MOD were mostly underestimated, while the SEBS performance was characterized by a systematic overestimation. In general, all four algorithms produce the best results in wet and moderately wet climate regimes. In dry regimes, the correlation and the absolute agreement with the reference tower ET observations were consistently lower. While ET derived with in situ forcing data agrees best with the tower measurements ( R 2 = 0.67), the agreement of the satellite-based ET estimates is only marginally lower ( R 2 = 0.58). Results also show similar model performance at daily and sub-daily (3-hourly) resolutions. Overall, our validation experiments against in situ measurements indicate that there is no single best-performing algorithm across all biome and forcing types. In conclusion, an extension of the evaluation to a larger selection of 85 towers (model inputs resampled to a common grid to facilitate global estimates) confirmed the original findings.« less

The 1990 conterminous U. S. AVHRR data set

USGS Publications Warehouse

Eidenshink, Jeffery C.

1992-01-01

The U.S. Geological Survey, using NOAA-ll Advanced Very High Resolution Radiometer (AVHRR) 1-km data, has produced a time series of 19 biweekly maximum normalized difference vegetation index (NDV!) composites of the conterminous United States for the 1990 growing season. Each biweekly composite included data from approximately 20 calibrated and georegistered daily overpasses. The output is a data set which includes all five calibrated AVHRR channels, NOV! values, three satellite/solar viewing angles, and date of observation pointer for each biweekly composite. The data set is intended for assessing seasonal variations in vegetation condition and provides a foundation for studying long-term changes in vegetation resulting from human interactions or global climate alterations.

Current Status and Challenges of Atmospheric Data Assimilation

NASA Astrophysics Data System (ADS)

Atlas, R. M.; Gelaro, R.

2016-12-01

The issues of modern atmospheric data assimilation are fairly simple to comprehend but difficult to address, involving the combination of literally billions of model variables and tens of millions of observations daily. In addition to traditional meteorological variables such as wind, temperature pressure and humidity, model state vectors are being expanded to include explicit representation of precipitation, clouds, aerosols and atmospheric trace gases. At the same time, model resolutions are approaching single-kilometer scales globally and new observation types have error characteristics that are increasingly non-Gaussian. This talk describes the current status and challenges of atmospheric data assimilation, including an overview of current methodologies, the difficulty of estimating error statistics, and progress toward coupled earth system analyses.

Atmospheric Methane at Cape Meares\\, Oregon\\, U.S.A.: A High-Resolution Data Base for the Period 1979-1992

DOE Data Explorer

Khalil, M. A.K. [Oregon Graduate Institute of Science and Technology; Rasmussen, R. A. [Oregon Graduate Institute of Science and Technology

1994-01-01

This data base presents continuous automated atmospheric methane (CH4) measurements taken at the atmospheric monitoring facility in Cape Meares, Oregon, by the Oregon Graduate Institute of Science and Technology. The Cape Meares data represent some 119,000 individual atmospheric methane measurements carried out during 1979-1992. Analysis of ambient air (collected 12 to 72 times daily) was carried out by means of an automated sampling and measurement system, using the method of gas chromatography and flame ionization detection. Despite the long course of the record and the large number of individual measurements, these data may all be linked to a single absolute calibration standard.

Use of regional climate model output for hydrologic simulations

USGS Publications Warehouse

Hay, L.E.; Clark, M.P.; Wilby, R.L.; Gutowski, W.J.; Leavesley, G.H.; Pan, Z.; Arritt, R.W.; Takle, E.S.

2002-01-01

Daily precipitation and maximum and minimum temperature time series from a regional climate model (RegCM2) configured using the continental United States as a domain and run on a 52-km (approximately) spatial resolution were used as input to a distributed hydrologic model for one rainfall-dominated basin (Alapaha River at Statenville, Georgia) and three snowmelt-dominated basins (Animas River at Durango. Colorado; east fork of the Carson River near Gardnerville, Nevada: and Cle Elum River near Roslyn, Washington). For comparison purposes, spatially averaged daily datasets of precipitation and maximum and minimum temperature were developed from measured data for each basin. These datasets included precipitation and temperature data for all stations (hereafter, All-Sta) located within the area of the RegCM2 output used for each basin, but excluded station data used to calibrate the hydrologic model. Both the RegCM2 output and All-Sta data capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all four basins, the RegCM2- and All-Sta-based simulations of runoff show little skill on a daily basis [Nash-Sutcliffe (NS) values range from 0.05 to 0.37 for RegCM2 and -0.08 to 0.65 for All-Sta]. When the precipitation and temperature biases are corrected in the RegCM2 output and All-Sta data (Bias-RegCM2 and Bias-All, respectively) the accuracy of the daily runoff simulations improve dramatically for the snowmelt-dominated basins (NS values range from 0.41 to 0.66 for RegCM2 and 0.60 to 0.76 for All-Sta). In the rainfall-dominated basin, runoff simulations based on the Bias-RegCM2 output show no skill (NS value of 0.09) whereas Bias-All simulated runoff improves (NS value improved from - 0.08 to 0.72). These results indicate that measured data at the coarse resolution of the RegCM2 output can be made appropriate for basin-scale modeling through bias correction (essentially a magnitude correction). However, RegCM2 output, even when bias corrected, does not contain the day-to-day variability present in the All-Sta dataset that is necessary for basin-scale modeling. Future work is warranted to identify the causes for systematic biases in RegCM2 simulations, develop methods to remove the biases, and improve RegCM2 simulations of daily variability in local climate.

Transition of the GOES Evapotranspiration and Drought Product System (GET-D) into Operations at NOAA/NESDIS

NASA Astrophysics Data System (ADS)

Hain, C.; Anderson, M. C.; Fang, L.; Zhan, X.; Otkin, J.

2016-12-01

Abnormally dry conditions can adversely affect the health of agricultural crops if the dryness persists for an extended period of time or if it occurs at a sensitive stage of crop development. Depending on its severity and timing, drought can result in significant yield loss, with impacts on both local and global markets as signified by reduced economic output and higher grain and food prices. Due to changing climate conditions, we are moving into a regime where processes controlling drought evolution are becoming more variable and are shifting in intensity, frequency and duration. The unusually rapid increase in water stress during some of these drought events are not well predicted by standard drought indicators. Different remote sensing indicators sample moisture and vegetation conditions occurring on different time scales during the typical evolution of agricultural drought. It has been shown that the thermal-based Evaporative Stress Index (ESI), based on land surface temperature, has an early warning component where vegetation stress manifested through decreased root-zone soil moisture leads to detectable vegetation stress in the LST signal before degradation in vegetation health is observed in VIS/NIR drought indices (e.g., NDVI). To provide this data to a larger user community and address the needs of our project stakeholders, the GOES Evapotranspiration and Drought Product System (GET-D) has been developed to operationally generate daily ET and ESI maps over the North America. The core model in GET-D is the Atmosphere-Land Exchange Inverse model (ALEXI), which is built on the two-source energy (TSEB) approach and partitions the GOES land surface temperature into characteristic soil and canopy temperatures, based on the fraction of vegetation cover. The primary operational data products of the GET-D system include the daily clear-sky ET and daily 2, 4, 8 and 12 week composites of the Evaporative Stress Index (ESI) computed from the ET daily estimates over North America at a spatial resolution of 8 km. This talk will focus on the evaluation of the operational data products, lessons learned from the transition into operations and the planned global expansion of the GET-D system at NOAA.

Mining nitrate concentration patterns from high-frequency in situ monitoring: a step towards more detailed understanding of hydrological processes?

NASA Astrophysics Data System (ADS)

Aubert, Alice; Houska, Tobias; Plesca, Ina; Kraft, Philipp; Breuer, Lutz

2015-04-01

Recently developed sensing technics allow collecting a considerable amount of high-frequency data; not only for hydrologic parameters (water levels, rainfall, etc.) but also for water chemistry. With devices such as in situ spectrophotometer, nitrate concentration can be monitored down to sub-hourly intervals. Thus, opening the way to new questions: what about daily or sub-daily instream nitrate concentration variations? What do these newly observed variations tell us about hydrological processes? In the Vollnkirchener Bach catchment, a headwater creek flows through a human impacted landscape dominated by agricultural and forest use and including a small settlement. Since March 2013, a Pro-PS device has been installed at the gauging station (monitored since 2011). Nitrate concentration is measured every 15 minutes, discharge and water temperature every 5 minutes. Data mining, more precisely motif discovery, is performed on these time series to identify high-resolution patterns. Spectral analysis highlighted that, in data measured at sub-hourly sampling frequency, variations up to a few hours are more likely to be dominated by measurement noise rather than real-world fluctuations. Therefore, we focus on daily motifs and flood patterns (given the fact that hydrological conditions are changing during flood events, we assume that nitrate concentration changes are depicting real processes). Various flood motifs were extracted: (1) nitrate can either be diluted or (2) concentrated, or (3) both (dilution followed by a bumpy recession curve indicating nitrate enrichment at the end of the flood). In addition to these classical nutrient-discharge behaviors, a variety of other interesting motifs were highlighted. (4) A daily nitrate cycle is clearly observed, but only during a specific year period. (5) Lag to peak time between parameters differentiate flood patterns: sometimes nitrate peaks first, sometimes discharge peaks first. (6) Furthermore, we are able to pinpoint the contributions of a combined sewer overflow, as it creates a different motif from diffuse nitrate inflows from adjacent agricultural fields. We look into the other hydrological parameters to explain this variety of patterns and their occurrence time.

Improving the Long-Term Stability of Atmospheric Surface Deformation Predictions by Mitigating the Effects of Orography Updates in Operational Weather Forecast Models

NASA Astrophysics Data System (ADS)

Dill, Robert; Bergmann-Wolf, Inga; Thomas, Maik; Dobslaw, Henryk

2016-04-01

The global numerical weather prediction model routinely operated at the European Centre for Medium-Range Weather Forecasts (ECMWF) is typically updated about two times a year to incorporate the most recent improvements in the numerical scheme, the physical model or the data assimilation procedures into the system for steadily improving daily weather forecasting quality. Even though such changes frequently affect the long-term stability of meteorological quantities, data from the ECMWF deterministic model is often preferred over alternatively available atmospheric re-analyses due to both the availability of the data in near real-time and the substantially higher spatial resolution. However, global surface pressure time-series, which are crucial for the interpretation of geodetic observables, such as Earth rotation, surface deformation, and the Earth's gravity field, are in particular affected by changes in the surface orography of the model associated with every major change in horizontal resolution happened, e.g., in February 2006, January 2010, and May 2015 in case of the ECMWF operational model. In this contribution, we present an algorithm to harmonize surface pressure time-series from the operational ECMWF model by projecting them onto a time-invariant reference topography under consideration of the time-variable atmospheric density structure. The effectiveness of the method will be assessed globally in terms of pressure anomalies. In addition, we will discuss the impact of the method on predictions of crustal deformations based on ECMWF input, which have been recently made available by GFZ Potsdam.

Simulating the formation of carbonaceous aerosol in a European Megacity (Paris) during the MEGAPOLI summer and winter campaigns

NASA Astrophysics Data System (ADS)

Fountoukis, Christos; Megaritis, Athanasios G.; Skyllakou, Ksakousti; Charalampidis, Panagiotis E.; Denier van der Gon, Hugo A. C.; Crippa, Monica; Prévôt, André S. H.; Fachinger, Friederike; Wiedensohler, Alfred; Pilinis, Christodoulos; Pandis, Spyros N.

2016-03-01

We use a three-dimensional regional chemical transport model (PMCAMx) with high grid resolution and high-resolution emissions (4 × 4 km2) over the Paris greater area to simulate the formation of carbonaceous aerosol during a summer (July 2009) and a winter (January/February 2010) period as part of the MEGAPOLI (megacities: emissions, urban, regional, and global atmospheric pollution and climate effects, and Integrated tools for assessment and mitigation) campaigns. Model predictions of carbonaceous aerosol are compared against Aerodyne aerosol mass spectrometer and black carbon (BC) high time resolution measurements from three ground sites. PMCAMx predicts BC concentrations reasonably well reproducing the majority (70 %) of the hourly data within a factor of two during both periods. The agreement for the summertime secondary organic aerosol (OA) concentrations is also encouraging (mean bias = 0.1 µg m-3) during a photochemically intense period. The model tends to underpredict the summertime primary OA concentrations in the Paris greater area (by approximately 0.8 µg m-3) mainly due to missing primary OA emissions from cooking activities. The total cooking emissions are estimated to be approximately 80 mg d-1 per capita and have a distinct diurnal profile in which 50 % of the daily cooking OA is emitted during lunch time (12:00-14:00 LT) and 20 % during dinner time (20:00-22:00 LT). Results also show a large underestimation of secondary OA in the Paris greater area during wintertime (mean bias = -2.3 µg m-3) pointing towards a secondary OA formation process during low photochemical activity periods that is not simulated in the model.

Simulating the formation of carbonaceous aerosol in a European Megacity (Paris) during the MEGAPOLI summer and winter campaigns

NASA Astrophysics Data System (ADS)

Fountoukis, C.; Megaritis, A. G.; Skyllakou, K.; Charalampidis, P. E.; Denier van der Gon, H. A. C.; Crippa, M.; Prévôt, A. S. H.; Freutel, F.; Wiedensohler, A.; Pilinis, C.; Pandis, S. N.

2015-09-01

We use a three dimensional regional chemical transport model (PMCAMx) with high grid resolution and high resolution emissions (4 km × 4 km) over the Paris greater area to simulate the formation of carbonaceous aerosol during a summer (July 2009) and a winter (January/February 2010) period as part of the MEGAPOLI (Megacities: Emissions, urban, regional, and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) campaigns. Model predictions of carbonaceous aerosol are compared against Aerodyne aerosol mass spectrometer and black carbon (BC) high time resolution measurements from three ground sites. PMCAMx predicts BC concentrations reasonably well reproducing the majority (70 %) of the hourly data within a factor of two during both periods. The agreement for the summertime secondary organic aerosol (OA) concentrations is also encouraging (mean bias = 0.1 μg m-3) during a photochemically intense period. The model tends to underpredict the summertime primary OA concentrations in the Paris greater area (by approximately 0.8 μg m-3) mainly due to missing primary OA emissions from cooking activities. The total cooking emissions are estimated to be approximately 80 mg d-1 per capita and have a distinct diurnal profile in which 50 % of the daily cooking OA is emitted during lunch time (12:00-14:00 LT) and 20 % during dinner time (20:00-22:00 LT). Results also show a large underestimation of secondary OA in the Paris greater area during wintertime (mean bias = -2.3 μg m-3) pointing towards a secondary OA formation process during low photochemical activity periods that is not simulated in the model.

Moderate Resolution Imaging Spectroradiometer (MODIS) Overview

USGS Publications Warehouse

,

2008-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) is an instrument that collects remotely sensed data used by scientists for monitoring, modeling, and assessing the effects of natural processes and human actions on the Earth's surface. The continual calibration of the MODIS instruments, the refinement of algorithms used to create higher-level products, and the ongoing product validation make MODIS images a valuable time series (2000-present) of geophysical and biophysical land-surface measurements. Carried on two National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) satellites, MODIS acquires morning (EOS-Terra) and afternoon (EOS-Aqua) views almost daily. Terra data acquisitions began in February 2000 and Aqua data acquisitions began in July 2002. Land data are generated only as higher-level products, removing the burden of common types of data processing from the user community. MODIS-based products describing ecological dynamics, radiation budget, and land cover are projected onto a sinusoidal mapping grid and distributed as 10- by 10-degree tiles at 250-, 500-, or 1,000-meter spatial resolution. Some products are also created on a 0.05-degree geographic grid to support climate modeling studies. All MODIS products are distributed in the Hierarchical Data Format-Earth Observing System (HDF-EOS) file format and are available through file transfer protocol (FTP) or on digital video disc (DVD) media. Versions 4 and 5 of MODIS land data products are currently available and represent 'validated' collections defined in stages of accuracy that are based on the number of field sites and time periods for which the products have been validated. Version 5 collections incorporate the longest time series of both Terra and Aqua MODIS data products.

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Comiso, Josefino C.; DiGirolamo, Nicolo E.; Shuman, Christopher A.; Key, Jeffrey R.; Koenig, Lora S.

2011-01-01

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly Terra MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid within +/-3 hours of 17:00Z or 2:00 PM Local Solar Time. Preliminary validation of the ISTs at Summit Camp, Greenland, during the 2008-09 winter, shows that there is a cold bias using the MODIS IST which underestimates the measured surface temperature by approximately 3 C when temperatures range from approximately -50 C to approximately -35 C. The ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present. Differences in the APP and MODIS cloud masks have so far precluded the current IST records from spanning both the APP and MODIS IST time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The Greenland IST climate-quality data record is suitable for continuation using future Visible Infrared Imager Radiometer Suite (VIIRS) data and will be elevated in status to a CDR when at least 9 more years of climate-quality data become available either from MODIS Terra or Aqua, or from the VIIRS. The complete MODIS IST data record will be available online in the summer of 2011.

Greenland Ice Sheet Surface Temperature, Melt, and Mass Loss: 2000-2006

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Williams, Richard S., Jr.; Luthcke, Scott B.; DiGirolamo, Nocolo

2007-01-01

Extensive melt on the Greenland Ice Sheet has been documented by a variety of ground and satellite measurements in recent years. If the well-documented warming continues in the Arctic, melting of the Greenland Ice Sheet will likely accelerate, contributing to sea-level rise. Modeling studies indicate that an annual or summer temperature rise of 1 C on the ice sheet will increase melt by 20-50% therefore, surface temperature is one of the most important ice-sheet parameters to study for analysis of changes in the mass balance of the ice-sheet. The Greenland Ice Sheet contains enough water to produce a rise in eustatic sea level of up to 7.0 m if the ice were to melt completely. However, even small changes (centimeters) in sea level would cause important economic and societal consequences in the world's major coastal cities thus it is extremely important to monitor changes in the ice-sheet surface temperature and to ultimately quantify these changes in terms of amount of sea-level rise. We have compiled a high-resolution, daily time series of surface temperature of the Greenland Ice Sheet, using the I-km resolution, clear-sky land-surface temperature (LST) standard product from the Moderate-Resolution Imaging Spectroradiometer (MODIS), from 2000 - 2006. We also use Gravity Recovery and Climate Experiment (GRACE) data, averaged over 10-day periods, to measure change in mass of the ice sheet as it melt and snow accumulates. Surface temperature can be used to determine frequency of surface melt, timing of the start and the end of the melt season, and duration of melt. In conjunction with GRACE data, it can also be used to analyze timing of ice-sheet mass loss and gain.

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: Magnetohydrodynamics Simulation Module for the Global Solar Corona.

PubMed

Hayashi, K; Hoeksema, J T; Liu, Y; Bobra, M G; Sun, X D; Norton, A A

Time-dependent three-dimensional magnetohydrodynamics (MHD) simulation modules are implemented at the Joint Science Operation Center (JSOC) of the Solar Dynamics Observatory (SDO). The modules regularly produce three-dimensional data of the time-relaxed minimum-energy state of the solar corona using global solar-surface magnetic-field maps created from Helioseismic and Magnetic Imager (HMI) full-disk magnetogram data. With the assumption of a polytropic gas with specific-heat ratio of 1.05, three types of simulation products are currently generated: i) simulation data with medium spatial resolution using the definitive calibrated synoptic map of the magnetic field with a cadence of one Carrington rotation, ii) data with low spatial resolution using the definitive version of the synchronic frame format of the magnetic field, with a cadence of one day, and iii) low-resolution data using near-real-time (NRT) synchronic format of the magnetic field on a daily basis. The MHD data available in the JSOC database are three-dimensional, covering heliocentric distances from 1.025 to 4.975 solar radii, and contain all eight MHD variables: the plasma density, temperature, and three components of motion velocity, and three components of the magnetic field. This article describes details of the MHD simulations as well as the production of the input magnetic-field maps, and details of the products available at the JSOC database interface. To assess the merits and limits of the model, we show the simulated data in early 2011 and compare with the actual coronal features observed by the Atmospheric Imaging Assembly (AIA) and the near-Earth in-situ data.

Combining HJ CCD, GF-1 WFV and MODIS Data to Generate Daily High Spatial Resolution Synthetic Data for Environmental Process Monitoring.

PubMed

Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-08-20

The limitations of satellite data acquisition mean that there is a lack of satellite data with high spatial and temporal resolutions for environmental process monitoring. In this study, we address this problem by applying the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) and the Spatial and Temporal Data Fusion Approach (STDFA) to combine Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field of view camera (GF-1 WFV) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate daily high spatial resolution synthetic data for land surface process monitoring. Actual HJ CCD and GF-1 WFV data were used to evaluate the precision of the synthetic images using the correlation analysis method. Our method was tested and validated for two study areas in Xinjiang Province, China. The results show that both the ESTARFM and STDFA can be applied to combine HJ CCD and MODIS reflectance data, and GF-1 WFV and MODIS reflectance data, to generate synthetic HJ CCD data and synthetic GF-1 WFV data that closely match actual data with correlation coefficients (r) greater than 0.8989 and 0.8643, respectively. Synthetic red- and near infrared (NIR)-band data generated by ESTARFM are more suitable for the calculation of Normalized Different Vegetation Index (NDVI) than the data generated by STDFA.

Combining HJ CCD, GF-1 WFV and MODIS Data to Generate Daily High Spatial Resolution Synthetic Data for Environmental Process Monitoring

PubMed Central

Wu, Mingquan; Huang, Wenjiang; Niu, Zheng; Wang, Changyao

2015-01-01

The limitations of satellite data acquisition mean that there is a lack of satellite data with high spatial and temporal resolutions for environmental process monitoring. In this study, we address this problem by applying the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) and the Spatial and Temporal Data Fusion Approach (STDFA) to combine Huanjing satellite charge coupled device (HJ CCD), Gaofen satellite no. 1 wide field of view camera (GF-1 WFV) and Moderate Resolution Imaging Spectroradiometer (MODIS) data to generate daily high spatial resolution synthetic data for land surface process monitoring. Actual HJ CCD and GF-1 WFV data were used to evaluate the precision of the synthetic images using the correlation analysis method. Our method was tested and validated for two study areas in Xinjiang Province, China. The results show that both the ESTARFM and STDFA can be applied to combine HJ CCD and MODIS reflectance data, and GF-1 WFV and MODIS reflectance data, to generate synthetic HJ CCD data and synthetic GF-1 WFV data that closely match actual data with correlation coefficients (r) greater than 0.8989 and 0.8643, respectively. Synthetic red- and near infrared (NIR)-band data generated by ESTARFM are more suitable for the calculation of Normalized Different Vegetation Index (NDVI) than the data generated by STDFA. PMID:26308017

Satellite Remote Sensing for Developing Time and Space Resolved Estimates of Ambient Particulate in Cleveland, OH.

PubMed

Kumar, Naresh; Chu, Allen D; Foster, Andrew D; Peters, Thomas; Willis, Robert

2011-09-01

This article empirically demonstrates the use of fine resolution satellite-based aerosol optical depth (AOD) to develop time and space resolved estimates of ambient particulate matter (PM) ≤2.5 µm and ≤10 µm in aerodynamic diameters (PM(2.5) and PM(10), respectively). AOD was computed at three different spatial resolutions, i.e., 2 km (means 2 km × 2 km area at nadir), 5 km, and 10 km, by using the data from MODerate Resolution Imaging Spectroradiometer (MODIS), aboard the Terra and Aqua satellites. Multiresolution AOD from MODIS (AOD(MODIS)) was compared with the in situ measurements of AOD by NASA's AErosol RObotic NETwork (AERONET) sunphotometer (AOD(AERONET)) at Bondville, IL, to demonstrate the advantages of the fine resolution AOD(MODIS) over the 10-km AOD(MODIS), especially for air quality prediction. An instrumental regression that corrects AOD(MODIS) for meteorological conditions was used for developing a PM predictive model.The 2-km AOD(MODIS) aggregated within 0.025° and 15-min intervals shows the best association with the in situ measurements of AOD(AERONET). The 2-km AOD(MODIS) seems more promising to estimate time and space resolved estimates of ambient PM than the 10-km AOD(MODIS), because of better location precision and a significantly greater number of data points across geographic space and time. Utilizing the collocated AOD(MODIS) and PM data in Cleveland, OH, a regression model was developed for predicting PM for all AOD(MODIS) data points. Our analysis suggests that the slope of the 2-km AOD(MODIS) (instrumented on meteorological conditions) is close to unity with the PM monitored on the ground. These results should be interpreted with caution, because the slope of AOD(MODIS) ranges from 0.52 to 1.72 in the site-specific models. In the cross validation of the overall model, the root mean square error (RMSE) of PM(10) was smaller (2.04 µg/m(3) in overall model) than that of PM(2.5) (2.5 µg/m(3)). The predicted PM in the AOD(MODIS) data (∼2.34 million data points) was utilized to develop a systematic grid of daily PM at 5-km spatial resolution with the aid of spatiotemporal Kriging.

Satellite Remote Sensing for Developing Time and Space Resolved Estimates of Ambient Particulate in Cleveland, OH

PubMed Central

Kumar, Naresh; Chu, Allen D.; Foster, Andrew D.; Peters, Thomas; Willis, Robert

2011-01-01

This article empirically demonstrates the use of fine resolution satellite-based aerosol optical depth (AOD) to develop time and space resolved estimates of ambient particulate matter (PM) ≤2.5 µm and ≤10 µm in aerodynamic diameters (PM2.5 and PM10, respectively). AOD was computed at three different spatial resolutions, i.e., 2 km (means 2 km × 2 km area at nadir), 5 km, and 10 km, by using the data from MODerate Resolution Imaging Spectroradiometer (MODIS), aboard the Terra and Aqua satellites. Multiresolution AOD from MODIS (AODMODIS) was compared with the in situ measurements of AOD by NASA’s AErosol RObotic NETwork (AERONET) sunphotometer (AODAERONET) at Bondville, IL, to demonstrate the advantages of the fine resolution AODMODIS over the 10-km AODMODIS, especially for air quality prediction. An instrumental regression that corrects AODMODIS for meteorological conditions was used for developing a PM predictive model. The 2-km AODMODIS aggregated within 0.025° and 15-min intervals shows the best association with the in situ measurements of AODAERONET. The 2-km AODMODIS seems more promising to estimate time and space resolved estimates of ambient PM than the 10-km AODMODIS, because of better location precision and a significantly greater number of data points across geographic space and time. Utilizing the collocated AODMODIS and PM data in Cleveland, OH, a regression model was developed for predicting PM for all AODMODIS data points. Our analysis suggests that the slope of the 2-km AODMODIS (instrumented on meteorological conditions) is close to unity with the PM monitored on the ground. These results should be interpreted with caution, because the slope of AODMODIS ranges from 0.52 to 1.72 in the site-specific models. In the cross validation of the overall model, the root mean square error (RMSE) of PM10 was smaller (2.04 µg/m3 in overall model) than that of PM2.5 (2.5 µg/m3). The predicted PM in the AODMODIS data (∼2.34 million data points) was utilized to develop a systematic grid of daily PM at 5-km spatial resolution with the aid of spatiotemporal Kriging. PMID:22238503

Estimation of daily PM10 concentrations in Italy (2006-2012) using finely resolved satellite data, land use variables and meteorology.

PubMed

Stafoggia, Massimo; Schwartz, Joel; Badaloni, Chiara; Bellander, Tom; Alessandrini, Ester; Cattani, Giorgio; De' Donato, Francesca; Gaeta, Alessandra; Leone, Gianluca; Lyapustin, Alexei; Sorek-Hamer, Meytar; de Hoogh, Kees; Di, Qian; Forastiere, Francesco; Kloog, Itai

2017-02-01

Health effects of air pollution, especially particulate matter (PM), have been widely investigated. However, most of the studies rely on few monitors located in urban areas for short-term assessments, or land use/dispersion modelling for long-term evaluations, again mostly in cities. Recently, the availability of finely resolved satellite data provides an opportunity to estimate daily concentrations of air pollutants over wide spatio-temporal domains. Italy lacks a robust and validated high resolution spatio-temporally resolved model of particulate matter. The complex topography and the air mixture from both natural and anthropogenic sources are great challenges difficult to be addressed. We combined finely resolved data on Aerosol Optical Depth (AOD) from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, ground-level PM 10 measurements, land-use variables and meteorological parameters into a four-stage mixed model framework to derive estimates of daily PM 10 concentrations at 1-km2 grid over Italy, for the years 2006-2012. We checked performance of our models by applying 10-fold cross-validation (CV) for each year. Our models displayed good fitting, with mean CV-R2=0.65 and little bias (average slope of predicted VS observed PM 10 =0.99). Out-of-sample predictions were more accurate in Northern Italy (Po valley) and large conurbations (e.g. Rome), for background monitoring stations, and in the winter season. Resulting concentration maps showed highest average PM 10 levels in specific areas (Po river valley, main industrial and metropolitan areas) with decreasing trends over time. Our daily predictions of PM 10 concentrations across the whole Italy will allow, for the first time, estimation of long-term and short-term effects of air pollution nationwide, even in areas lacking monitoring data. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Gaballa, H; O’Brien, M; Riegel, A

Purpose: To develop a daily quality assurance (QA) device that can test the 6DoF (degrees of freedom) couch repositioning accuracy, prior to SBRT treatment deliveries, with an accuracy of ±0.3 degrees and ±0.3 mm. Methods: A daily QA phantom is designed with a focus on the derived center of projections of its markers, rather than tracking its individual markers one at a time. This approach can be the most favorable to address the intended machining accuracy of the QA phantom and the CBCT spatial resolution limitations, primarily 1 mm min slice thickness, simultaneously. With the current design, ±0.1 mm congruencemore » of the resultant center of gravity of the markers with reference CT (0.6 mm minimum slice thickness) vs CBCT (1.0 mm minimum slice thickness) can be achieved. If successful, the QA device should be qualified to test 6DoF couch performance with a gauged accuracy of ±0.3 degrees/±0.3 mm. Testing is performed for the Varian True Beam 2.0 6DoF system. Results: Once the QA phantom is constructed and tested, agreement of the center of gravity of the reference CT scan and the CBCT scan of ±0.1 mm is achieved. This has translated into a consistent 3D-3D match on the treatment machine, CT vs CBCT, with a repetitive ±0.1 mm variation, thus exceeding our expectations. We have deployed the phantom for daily QA on one of our accelerators, and found that the QA time has increased by only 10 minutes. Conclusion: A 6DoF phantom has been designed (patent pending) and built with a realistic work flow in mind where the daily couch accuracy QA checks taking less than 10 minutes. Current developments include integration with the Varian’s Machine Performance Check consistency module.« less

Analysing the Advantages of High Temporal Resolution Geostationary MSG SEVIRI Data Compared to Polar Operational Environmental Satellite Data for Land Surface Monitoring in Africa

NASA Technical Reports Server (NTRS)

Fensholt, R.; Anyamba, A.; Huber, S.; Proud, S. R.; Tucker, C. J.; Small, J.; Pak, E.; Rasmussen, M. O.; Sandholt, I.; Shisanya, C.

2011-01-01

Since 1972, satellite remote sensing of the environment has been dominated by polar-orbiting sensors providing useful data for monitoring the earth s natural resources. However their observation and monitoring capacity are inhibited by daily to monthly looks for any given ground surface which often is obscured by frequent and persistent cloud cover creating large gaps in time series measurements. The launch of the Meteosat Second Generation (MSG) satellite into geostationary orbit has opened new opportunities for land surface monitoring. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on-board MSG with an imaging capability every 15 minutes which is substantially greater than any temporal resolution that can be obtained from existing polar operational environmental satellites (POES) systems currently in use for environmental monitoring. Different areas of the African continent were affected by droughts and floods in 2008 caused by periods of abnormally low and high rainfall, respectively. Based on the effectiveness of monitoring these events from Earth Observation (EO) data the current analyses show that the new generation of geostationary remote sensing data can provide higher temporal resolution cloud-free (less than 5 days) measurements of the environment as compared to existing POES systems. SEVIRI MSG 5-day continental scale composites will enable rapid assessment of environmental conditions and improved early warning of disasters for the African continent such as flooding or droughts. The high temporal resolution geostationary data will complement existing higher spatial resolution polar-orbiting satellite data for various dynamic environmental and natural resource applications of terrestrial ecosystems.

The Effects of Employment Status and Daily Stressors on Time Spent on Daily Household Chores in Middle-Aged and Older Adults

ERIC Educational Resources Information Center

Wong, Jen D.; Almeida, David M.

2013-01-01

Purpose of the study: This study examines how employment status (worker vs. retiree) and life course influences (age, gender, and marital status) are associated with time spent on daily household chores. Second, this study assesses whether the associations between daily stressors and time spent on daily household chores differ as a function of…

Lessons Learned from OMI Observations of Point Source SO2 Pollution

NASA Technical Reports Server (NTRS)

Krotkov, N.; Fioletov, V.; McLinden, Chris

2011-01-01

The Ozone Monitoring Instrument (OMI) on NASA Aura satellite makes global daily measurements of the total column of sulfur dioxide (SO2), a short-lived trace gas produced by fossil fuel combustion, smelting, and volcanoes. Although anthropogenic SO2 signals may not be detectable in a single OMI pixel, it is possible to see the source and determine its exact location by averaging a large number of individual measurements. We describe new techniques for spatial and temporal averaging that have been applied to the OMI SO2 data to determine the spatial distributions or "fingerprints" of SO2 burdens from top 100 pollution sources in North America. The technique requires averaging of several years of OMI daily measurements to observe SO2 pollution from typical anthropogenic sources. We found that the largest point sources of SO2 in the U.S. produce elevated SO2 values over a relatively small area - within 20-30 km radius. Therefore, one needs higher than OMI spatial resolution to monitor typical SO2 sources. TROPOMI instrument on the ESA Sentinel 5 precursor mission will have improved ground resolution (approximately 7 km at nadir), but is limited to once a day measurement. A pointable geostationary UVB spectrometer with variable spatial resolution and flexible sampling frequency could potentially achieve the goal of daily monitoring of SO2 point sources and resolve downwind plumes. This concept of taking the measurements at high frequency to enhance weak signals needs to be demonstrated with a GEOCAPE precursor mission before 2020, which will help formulating GEOCAPE measurement requirements.

Optimising Habitat-Based Models for Wide-Ranging Marine Predators: Scale Matters

NASA Astrophysics Data System (ADS)

Scales, K. L.; Hazen, E. L.; Jacox, M.; Edwards, C. A.; Bograd, S. J.

2016-12-01

Predicting the responses of marine top predators to dynamic oceanographic conditions requires habitat-based models that sufficiently capture environmental preferences. Spatial resolution and temporal averaging of environmental data layers is a key aspect of model construction. The utility of surfaces contemporaneous to animal movement (e.g. daily, weekly), versus synoptic products (monthly, seasonal, climatological) is currently under debate, as is the optimal spatial resolution for predictive products. Using movement simulations with built-in environmental preferences (correlated random walks, multi-state hidden Markov-type models) together with modeled (Regional Oceanographic Modeling System, ROMS) and remotely-sensed (MODIS-Aqua) datasets, we explored the effects of degrading environmental surfaces (3km - 1 degree, daily - climatological) on model inference. We simulated the movements of a hypothetical wide-ranging marine predator through the California Current system over a three month period (May-June-July), based on metrics derived from previously published blue whale Balaenoptera musculus tracking studies. Results indicate that models using seasonal or climatological data fields can overfit true environmental preferences, in both presence-absence and behaviour-based model formulations. Moreover, the effects of a degradation in spatial resolution are more pronounced when using temporally averaged fields than when using daily, weekly or monthly datasets. In addition, we observed a notable divergence between the `best' models selected using common methods (e.g. AUC, AICc) and those that most accurately reproduced built-in environmental preferences. These findings have important implications for conservation and management of marine mammals, seabirds, sharks, sea turtles and large teleost fish, particularly in implementing dynamic ocean management initiatives and in forecasting responses to future climate-mediated ecosystem change.

Optimising Habitat-Based Models for Wide-Ranging Marine Predators: Scale Matters

NASA Astrophysics Data System (ADS)

Scales, K. L.; Hazen, E. L.; Jacox, M.; Edwards, C. A.; Bograd, S. J.

2016-02-01

Predicting the responses of marine top predators to dynamic oceanographic conditions requires habitat-based models that sufficiently capture environmental preferences. Spatial resolution and temporal averaging of environmental data layers is a key aspect of model construction. The utility of surfaces contemporaneous to animal movement (e.g. daily, weekly), versus synoptic products (monthly, seasonal, climatological) is currently under debate, as is the optimal spatial resolution for predictive products. Using movement simulations with built-in environmental preferences (correlated random walks, multi-state hidden Markov-type models) together with modeled (Regional Oceanographic Modeling System, ROMS) and remotely-sensed (MODIS-Aqua) datasets, we explored the effects of degrading environmental surfaces (3km - 1 degree, daily - climatological) on model inference. We simulated the movements of a hypothetical wide-ranging marine predator through the California Current system over a three month period (May-June-July), based on metrics derived from previously published blue whale Balaenoptera musculus tracking studies. Results indicate that models using seasonal or climatological data fields can overfit true environmental preferences, in both presence-absence and behaviour-based model formulations. Moreover, the effects of a degradation in spatial resolution are more pronounced when using temporally averaged fields than when using daily, weekly or monthly datasets. In addition, we observed a notable divergence between the `best' models selected using common methods (e.g. AUC, AICc) and those that most accurately reproduced built-in environmental preferences. These findings have important implications for conservation and management of marine mammals, seabirds, sharks, sea turtles and large teleost fish, particularly in implementing dynamic ocean management initiatives and in forecasting responses to future climate-mediated ecosystem change.

Pressure mapping with textile sensors for compression therapy monitoring.

PubMed

Baldoli, Ilaria; Mazzocchi, Tommaso; Paoletti, Clara; Ricotti, Leonardo; Salvo, Pietro; Dini, Valentina; Laschi, Cecilia; Francesco, Fabio Di; Menciassi, Arianna

2016-08-01

Compression therapy is the cornerstone of treatment in the case of venous leg ulcers. The therapy outcome is strictly dependent on the pressure distribution produced by bandages along the lower limb length. To date, pressure monitoring has been carried out using sensors that present considerable drawbacks, such as single point instead of distributed sensing, no shape conformability, bulkiness and constraints on patient's movements. In this work, matrix textile sensing technologies were explored in terms of their ability to measure the sub-bandage pressure with a suitable temporal and spatial resolution. A multilayered textile matrix based on a piezoresistive sensing principle was developed, calibrated and tested with human subjects, with the aim of assessing real-time distributed pressure sensing at the skin/bandage interface. Experimental tests were carried out on three healthy volunteers, using two different bandage types, from among those most commonly used. Such tests allowed the trends of pressure distribution to be evaluated over time, both at rest and during daily life activities. Results revealed that the proposed device enables the dynamic assessment of compression mapping, with a suitable spatial and temporal resolution (20 mm and 10 Hz, respectively). In addition, the sensor is flexible and conformable, thus well accepted by the patient. Overall, this study demonstrates the adequacy of the proposed piezoresistive textile sensor for the real-time monitoring of bandage-based therapeutic treatments. © IMechE 2016.

Using SAS functions and high-resolution isotope data to unravel travel time distributions in headwater catchments

NASA Astrophysics Data System (ADS)

Benettin, Paolo; Soulsby, Chris; Birkel, Christian; Tetzlaff, Doerthe; Botter, Gianluca; Rinaldo, Andrea

2017-03-01

We use high-resolution tracer data from an experimental site to test theoretical approaches that integrate catchment-scale flow and transport processes in a unified framework centered on selective age sampling by streamflow and evapotranspiration fluxes. Transport processes operating at the catchment scale are reflected in the evolving residence time distribution of the catchment water storage and in the age selection operated by out-fluxes. Such processes are described here through StorAge Selection (SAS) functions parameterized as power laws of the normalized rank storage. Such functions are computed through appropriate solution of the master equation defining formally the evolution of residence and travel times. By representing the way in which catchment storage generates outflows composed by water of different ages, the main mechanism regulating the tracer composition of runoff is clearly identified and detailed comparison with empirical data sets are possible. Properly calibrated numerical tools provide simulations that convincingly reproduce complex measured signals of daily deuterium content in stream waters during wet and dry periods. Results for the catchment under consideration are consistent with other recent studies indicating a tendency for natural catchments to preferentially release younger available water. The study shows that power law SAS functions prove a powerful tool to explain catchment-scale transport processes that also has potential in less intensively monitored sites.

Greenland ice sheet melt from MODIS and associated atmospheric variability.

PubMed

Häkkinen, Sirpa; Hall, Dorothy K; Shuman, Christopher A; Worthen, Denise L; DiGirolamo, Nicolo E

2014-03-16

Daily June-July melt fraction variations over the Greenland ice sheet (GIS) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) (2000-2013) are associated with atmospheric blocking forming an omega-shape ridge over the GIS at 500 hPa height. Blocking activity with a range of time scales, from synoptic waves breaking poleward (<5 days) to full-fledged blocks (≥5 days), brings warm subtropical air masses over the GIS controlling daily surface temperatures and melt. The temperature anomaly of these subtropical air mass intrusions is also important for melting. Based on the years with the greatest melt (2002 and 2012) during the MODIS era, the area-average temperature anomaly of 2 standard deviations above the 14 year June-July mean results in a melt fraction of 40% or more. Though the summer of 2007 had the most blocking days, atmospheric temperature anomalies were too small to instigate extreme melting. Short-term atmospheric blocking over Greenland contributes to melt episodesAssociated temperature anomalies are equally important for the meltDuration and strength of blocking events contribute to surface melt intensity.

Comparing different snow products to assess spatio-temporal snow cover patterns in the Central Taurus Mountains, Turkey

NASA Astrophysics Data System (ADS)

Sturm, K.; Helmschrot, J.

2013-12-01

Snow and its spatial and temporal patterns are important for catchment hydrology in the semi-arid eastern Mediterranean. Since most of the annual rainfall is stored as snow during winter and released during drier conditions in spring and summer, downstream regions of the Taurus Mountains relying on snow water temporarily stored in reservoirs for agricultural use are heavily dependent on the timing of snowmelt discharge. Runoff is controlled by the amount of accumulated snow, its distribution, and the climatic conditions controlling spring snowmelt. Thus, knowledge about spatial and temporal snow cover dynamics is essential for sustainable water resources management. The lack of observations in high-altitude regions reinforces the application of different snow products for a better assessment of spatio-temporal snow cover patterns. To better assess the quality of such products, simulated daily snow cover and EO-based snow cover products were compared for the Egribuk subcatchment, in the Central Taurus Mountains, Turkey. Daily information on snow cover, depths, and snow water equivalent was derived from distributed hydrological modeling using the J2000 model. Furthermore, 8-day MODIS snow cover data from Terra (MOD10A2) and Aqua (MYD10A2) satellites at a spatial resolution of 500 m were synchronized to receive cloud-free images. From this effort, 253 images covering the period between 07/04/2002 and 12/27/2007 were used for further analyses. The products were analyzed individually to determine the number of snow-covered days in relation to freezing days, spring snowmelt onsets, and temporal patterns, reflecting the effect of altitude on the percentage snow-covered area (SCA) along a topographic gradient at various time-steps. Monthly and 8-day spatial patterns of a single snow season were also examined. When SCA peaks at all altitudes, in February and March, the results of both products show a good agreement regarding SCA extent. In contrast, the extent of SCA differs notably during snow accumulation and ablation periods, the highest deviations occurring in December, April, and May. The highest SCA inconsistencies are observed in the low and mid altitudes, whereas the higher elevations are snow-covered very early in the snow season as modeled by J2000. During these periods, J2000 simulates a significantly larger SCA than MODIS. The analysis of individual time steps suggests that the J2000 daily model does capture individual snow events, whereas the MODIS products fail to do so due to their temporal resolution. Furthermore, acquisition time and inner-daily melt and re-freezing effects may affect SCA estimates from MODIS data. In other cases, differences can clearly be associated to insufficient model input data, primarily due to limited spatial precipitation and temperature data. Our study indicates that individual products might provide inconsistent information on temporal and spatial snow cover. We recommend considering a combined analysis of different snow products in order to provide reliable information on snow cover dynamics, in particular in eastern Mediterranean high-altitude environments.

A New Hybrid Method for Remote Sensing Time Series Reconstruction in Support of Land Surface Phenology

NASA Astrophysics Data System (ADS)

Barreto-Munoz, A.; Didan, K.; Riveracamacho, J.; Yitayew, M.

2010-12-01

Remote sensing vegetation indices (NDVI, EVI, and EVI2) are proxies for studying vegetation states and enable the effective and consistent monitoring of global vegetation. Records of daily global satellite images are available from the last three decades, however, the presence of clouds, aerosols, variable viewing geometry and less than ideal processing techniques makes it difficult to obtain high quality data every time; resulting in incomplete daily coverage (80% of the data is either missing or useless sometimes). In order to improve the temporal frequency and coverage, gap fill techniques are usually employed. There are several methods that are mostly based on the use of complex Fourier Transform (TF) functions, Gaussian fitting models, or simple compositing techniques. The first two methods are extremely CPU and memory intensive and the results tend to be biased towards the periods of time when data is available . The composite-method sacrifices the temporal frequency in order to achieve higher quality data over longer periods of time by combining several images into one to insure the elimination of problematic data Long composite period interval tend to inhibit proper change detection during periods of rapid change and periods of land cover disturbance. Because this method is based on maximizing the vegetation index value during the composite period, longer composite interval will shift the start of season towards later dates, the end of season towards earlier dates, and consequently shorter growing season. These slight errors and uncertainties interfere with accurate change detection as they add a level of uncertainty to the estimated Phenology parameters. In this research we’re developing a new technique that aims at producing consistently high quality vegetation index data, while preserving adequate temporal resolution to support accurate phenological studies. This method involves finding the optimum number of days for compositing and then using an interpolation approach for filling the remaining temporal gaps. The seasonally variable per-pixel optimum composite period is obtained by minimizing the number of temporal gaps when varying the composite period from 1 day to 16 days. Remaining gaps are then estimated using a local linear function that uses as input only the nearest high quality observation days. We further constrain this method by a moving window long term average to address biases that may result from over- or under-fitting. This method was evaluated using the 30+ year Climate Modeling Grid resolution (CMG, 0.05 deg.) records of AVHRR and MODIS Terra/Aqua daily surface reflectance. We note several advantages to this method: 1) Simpler and less computer intensive to implement, 2) Superior to other methods since it only looked at the data around the temporal gap which helps eliminate the biases that may result from methods that simultaneously use the full annual cycle, and 3) Most importantly it kept a balance between providing higher frequency and high quality data and the potential noise that results from daily data. It is currently being implemented as a package to support the estimation of global phenology and to generate high quality long term Earth System Data Records of Vegetation Index from multiple sensors.

Reconstruction from EOF analysis of SMOS salinity data in Mediterranean Sea

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Prospective evaluation of pain, swelling, and disability from copperhead envenomation.

PubMed

Roth, Brett; Sharma, Kapil; Onisko, Nancy; Chen, Tiffany

2016-03-01

In light of the existing controversy regarding antivenin treatment for copperhead envenomation, a more detailed analysis of the disability from this species is needed. Our objective was to prospectively determine the duration of pain, swelling, and functional disability, i.e., residual venom effects, in patients with copperhead envenomation. Patients with venomous snakebite reported to the North Texas Poison Center between April 2009 and November 2011 were assessed. Patients with confirmed envenomations were contacted by a specialist in poison information. Day zero was the day of the bite and verbal phone consent for study enrollment was obtained at that time. The patient (or their guardian) was contacted by phone daily thereafter, and asked to rate their pain, edema/swelling, and disability using the modified DASH and LEFS scales. Patients were followed to resolution of all symptoms or return to baseline. About 104 cases of venomous snakebite were followed; of which 17 were excluded due to being a dry bites (5) or for having insufficient data during follow-up (11) or due to coagulopathy (1). Overall, residual venom effects from copperhead bites for most patients last between 7 and 13 days. Median time to complete pain resolution was 7 days (mean = 10.7 days). Median length of time to resolution of swelling was 10 days (mean = 13 days) and median length of time to resolution of functional disability was 9 days (mean = 12.2 days). Residual venom effects from copperhead envenomation in this study had a slightly shorter duration than some other studies. Data are skewed due to outliers where residual venom effects lasted for up to 89 days. Initial reoccurrence of some symptoms may be seen. Antivenom (AV) is currently being used for a large percentage of patients with copperhead envenomation. Finally, no differences in duration of venom effects were seen based on age or location of bite. Our study suggests that residual venom effects from copperhead species persist for between 10 and 13 days but may persist for months. Future studies are necessary to identify risk factors for severe/prolonged injury and to define the benefit of AV in patients with copperhead envenomation.

The performance of the new enhanced-resolution satellite passive microwave dataset applied for snow water equivalent estimation

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Jiang, L.; Liu, D.

2017-12-01

The newly-processed NASA MEaSures Calibrated Enhanced-Resolution Brightness Temperature (CETB) reconstructed using antenna measurement response function (MRF) is considered to have significantly improved fine-resolution measurements with better georegistration for time-series observations and equivalent field of view (FOV) for frequencies with the same monomial spatial resolution. We are looking forward to its potential for the global snow observing purposes, and therefore aim to test its performance for characterizing snow properties, especially the snow water equivalent (SWE) in large areas. In this research, two candidate SWE algorithms will be tested in China for the years between 2005 to 2010 using the reprocessed TB from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E), with the results to be evaluated using the daily snow depth measurements at over 700 national synoptic stations. One of the algorithms is the SWE retrieval algorithm used for the FengYun (FY) - 3 Microwave Radiation Imager. This algorithm uses the multi-channel TB to calculate SWE for three major snow regions in China, with the coefficients adapted for different land cover types. The second algorithm is the newly-established Bayesian Algorithm for SWE Estimation with Passive Microwave measurements (BASE-PM). This algorithm uses the physically-based snow radiative transfer model to find the histogram of most-likely snow property that matches the multi-frequency TB from 10.65 to 90 GHz. It provides a rough estimation of snow depth and grain size at the same time and showed a 30 mm SWE RMS error using the ground radiometer measurements at Sodankyla. This study will be the first attempt to test it spatially for satellite. The use of this algorithm benefits from the high resolution and the spatial consistency between frequencies embedded in the new dataset. This research will answer three questions. First, to what extent can CETB increase the heterogeneity in the mapped SWE? Second, will the SWE estimation error statistics be improved using this high-resolution dataset? Third, how will the SWE retrieval accuracy be improved using CETB and the new SWE retrieval techniques?

Climatology and Interannual Variability of Quasi-Global Intense Precipitation Using Satellite Observations

NASA Technical Reports Server (NTRS)

Ricko, Martina; Adler, Robert F.; Huffman, George J.

2016-01-01

Climatology and variations of recent mean and intense precipitation over a near-global (50 deg. S 50 deg. N) domain on a monthly and annual time scale are analyzed. Data used to derive daily precipitation to examine the effects of spatial and temporal coverage of intense precipitation are from the current Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 version 7 precipitation product, with high spatial and temporal resolution during 1998 - 2013. Intense precipitation is defined by several different parameters, such as a 95th percentile threshold of daily precipitation, a mean precipitation that exceeds that percentile, or a fixed threshold of daily precipitation value [e.g., 25 and 50 mm day(exp -1)]. All parameters are used to identify the main characteristics of spatial and temporal variation of intense precipitation. High correlations between examined parameters are observed, especially between climatological monthly mean precipitation and intense precipitation, over both tropical land and ocean. Among the various parameters examined, the one best characterizing intense rainfall is a fraction of daily precipitation Great than or equal to 25 mm day(exp. -1), defined as a ratio between the intense precipitation above the used threshold and mean precipitation. Regions that experience an increase in mean precipitation likely experience a similar increase in intense precipitation, especially during the El Nino Southern Oscillation (ENSO) events. Improved knowledge of this intense precipitation regime and its strong connection to mean precipitation given by the fraction parameter can be used for monitoring of intense rainfall and its intensity on a global to regional scale.

Development and Evaluation of High-Resolution Climate Simulations Over the Mountainous Northeastern United States

NASA Technical Reports Server (NTRS)

Winter, Jonathan M.; Beckage, Brian; Bucini, Gabriela; Horton, Radley M.; Clemins, Patrick J.

2016-01-01

The mountain regions of the northeastern United States are a critical socioeconomic resource for Vermont, New York State, New Hampshire, Maine, and southern Quebec. While global climate models (GCMs) are important tools for climate change risk assessment at regional scales, even the increased spatial resolution of statistically downscaled GCMs (commonly approximately 1/ 8 deg) is not sufficient for hydrologic, ecologic, and land-use modeling of small watersheds within the mountainous Northeast. To address this limitation, an ensemble of topographically downscaled, high-resolution (30"), daily 2-m maximum air temperature; 2-m minimum air temperature; and precipitation simulations are developed for the mountainous Northeast by applying an additional level of downscaling to intermediately downscaled (1/ 8 deg) data using high-resolution topography and station observations. First, observed relationships between 2-m air temperature and elevation and between precipitation and elevation are derived. Then, these relationships are combined with spatial interpolation to enhance the resolution of intermediately downscaled GCM simulations. The resulting topographically downscaled dataset is analyzed for its ability to reproduce station observations. Topographic downscaling adds value to intermediately downscaled maximum and minimum 2-m air temperature at high-elevation stations, as well as moderately improves domain-averaged maximum and minimum 2-m air temperature. Topographic downscaling also improves mean precipitation but not daily probability distributions of precipitation. Overall, the utility of topographic downscaling is dependent on the initial bias of the intermediately downscaled product and the magnitude of the elevation adjustment. As the initial bias or elevation adjustment increases, more value is added to the topographically downscaled product.

Toward Improved Land Surface Initialization in Support of Regional WRF Forecasts at the Kenya Meteorological Department

NASA Technical Reports Server (NTRS)

Case. Jonathan; Mungai, John; Sakwa, Vincent; Kabuchanga, Eric; Zavodsky, Bradley T.; Limaye, Ashutosh S.

2014-01-01

Flooding and drought are two key forecasting challenges for the Kenya Meteorological Department (KMD). Atmospheric processes leading to excessive precipitation and/or prolonged drought can be quite sensitive to the state of the land surface, which interacts with the boundary layer of the atmosphere providing a source of heat and moisture. The development and evolution of precipitation systems are affected by heat and moisture fluxes from the land surface within weakly-sheared environments, such as in the tropics and sub-tropics. These heat and moisture fluxes during the day can be strongly influenced by land cover, vegetation, and soil moisture content. Therefore, it is important to represent the land surface state as accurately as possible in numerical weather prediction models. Enhanced regional modeling capabilities have the potential to improve forecast guidance in support of daily operations and high-end events over east Africa. KMD currently runs a configuration of the Weather Research and Forecasting (WRF) model in real time to support its daily forecasting operations, invoking the Nonhydrostatic Mesoscale Model (NMM) dynamical core. They make use of the National Oceanic and Atmospheric Administration / National Weather Service Science and Training Resource Center's Environmental Modeling System (EMS) to manage and produce the WRF-NMM model runs on a 7-km regional grid over eastern Africa. Two organizations at the National Aeronautics and Space Administration Marshall Space Flight Center in Huntsville, AL, SERVIR and the Short-term Prediction Research and Transition (SPoRT) Center, have established a working partnership with KMD for enhancing its regional modeling capabilities. To accomplish this goal, SPoRT and SERVIR will provide experimental land surface initialization datasets and model verification capabilities to KMD. To produce a land-surface initialization more consistent with the resolution of the KMD-WRF runs, the NASA Land Information System (LIS) will be run at a comparable resolution to provide real-time, daily soil initialization data in place of interpolated Global Forecast System soil moisture and temperature data. Additionally, real-time green vegetation fraction data from the Visible Infrared Imaging Radiometer Suite will be incorporated into the KMD-WRF runs, once it becomes publicly available from the National Environmental Satellite Data and Information Service. Finally, model verification capabilities will be transitioned to KMD using the Model Evaluation Tools (MET) package, in order to quantify possible improvements in simulated temperature, moisture and precipitation resulting from the experimental land surface initialization. The transition of these MET tools will enable KMD to monitor model forecast accuracy in near real time. This presentation will highlight preliminary verification results of WRF runs over east Africa using the LIS land surface initialization.

Daily computer usage correlated with undergraduate students' musculoskeletal symptoms.

PubMed

Chang, Che-Hsu Joe; Amick, Benjamin C; Menendez, Cammie Chaumont; Katz, Jeffrey N; Johnson, Peter W; Robertson, Michelle; Dennerlein, Jack Tigh

2007-06-01

A pilot prospective study was performed to examine the relationships between daily computer usage time and musculoskeletal symptoms on undergraduate students. For three separate 1-week study periods distributed over a semester, 27 students reported body part-specific musculoskeletal symptoms three to five times daily. Daily computer usage time for the 24-hr period preceding each symptom report was calculated from computer input device activities measured directly by software loaded on each participant's primary computer. General Estimating Equation models tested the relationships between daily computer usage and symptom reporting. Daily computer usage longer than 3 hr was significantly associated with an odds ratio 1.50 (1.01-2.25) of reporting symptoms. Odds of reporting symptoms also increased with quartiles of daily exposure. These data suggest a potential dose-response relationship between daily computer usage time and musculoskeletal symptoms.

Sensitivity of air pollution simulations with LOTOS-EUROS to the temporal distribution of anthropogenic emissions

NASA Astrophysics Data System (ADS)

Mues, A.; Kuenen, J.; Hendriks, C.; Manders, A.; Segers, A.; Scholz, Y.; Hueglin, C.; Builtjes, P.; Schaap, M.

2014-01-01

In this study the sensitivity of the model performance of the chemistry transport model (CTM) LOTOS-EUROS to the description of the temporal variability of emissions was investigated. Currently the temporal release of anthropogenic emissions is described by European average diurnal, weekly and seasonal time profiles per sector. These default time profiles largely neglect the variation of emission strength with activity patterns, region, species, emission process and meteorology. The three sources dealt with in this study are combustion in energy and transformation industries (SNAP1), nonindustrial combustion (SNAP2) and road transport (SNAP7). First of all, the impact of neglecting the temporal emission profiles for these SNAP categories on simulated concentrations was explored. In a second step, we constructed more detailed emission time profiles for the three categories and quantified their impact on the model performance both separately as well as combined. The performance in comparison to observations for Germany was quantified for the pollutants NO2, SO2 and PM10 and compared to a simulation using the default LOTOS-EUROS emission time profiles. The LOTOS-EUROS simulations were performed for the year 2006 with a temporal resolution of 1 h and a horizontal resolution of approximately 25 × 25km2. In general the largest impact on the model performance was found when neglecting the default time profiles for the three categories. The daily average correlation coefficient for instance decreased by 0.04 (NO2), 0.11 (SO2) and 0.01 (PM10) at German urban background stations compared to the default simulation. A systematic increase in the correlation coefficient is found when using the new time profiles. The size of the increase depends on the source category, component and station. Using national profiles for road transport showed important improvements in the explained variability over the weekdays as well as the diurnal cycle for NO2. The largest impact of the SNAP1 and 2 profiles were found for SO2. When using all new time profiles simultaneously in one simulation, the daily average correlation coefficient increased by 0.05 (NO2), 0.07 (SO2) and 0.03 (PM10) at urban background stations in Germany. This exercise showed that to improve the performance of a CTM, a better representation of the distribution of anthropogenic emission in time is recommendable. This can be done by developing a dynamical emission model that takes into account regional specific factors and meteorology.

Reduction of fibromyalgia symptoms through intravenous nutrient therapy: results of a pilot clinical trial.

PubMed

Massey, Patrick B

2007-01-01

To evaluate the effectiveness of a modified Myers' formula of intravenous nutrient therapy (IVNT) on the symptoms of fibromyalgia (FM) in therapy-resistant FM patients. In this pilot clinical trial, 7 participants with therapy resistant FM were given IVNT once per week for 8 weeks. Patient's pain levels, fatigue, and activities of daily living were evaluated weekly. All participants reported decreased pain levels, decreased fatigue, and increased activities of daily living. Participants noted increased energy levels within 24-48 hours of the initial infusion. At the end of the study, all participants reported increased energy and activities of daily living as well as a 60% reduction in pain (P=.005) and an 80% decrease in fatigue (P=-.005). No participants, however, reported complete or lasting resolution of pain or fatigue. No side effects were reported. Anecdotal reports have indicated benefit for IVNT for patients with chronic pain, including FM. However, except for 2 reports, the medical literature is devoid of any studies of IVNT for the treatment of FM. In this pilot study, 7 participants received IVNT once a week for 8 weeks. All participants had long-standing FM (at least 8 years) and had tried conventional therapies, such as antidepressants, nonsteroidal anti-inflammatory drugs, and exercise, without significant or lasting relief. All had improvement in symptoms and increases in their activities of daily living, although no participant reported complete resolution of symptoms. IVNT appears to be safe to reduce FM symptoms.