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NASA NTRS2019

Assessing Uncertainties of a Geophysical Approach to Estimate Surface Fine Particulate Matter Distributions from Satellite-Observed Aerosol Optical Depth

Health impact analyses are increasingly tapping the broad spatial coverage of satellite aerosol optical depth (AOD) products to estimate human exposure to fine particulate matter (PM2.5). We use a forward geophysical approach to derive ground-level PM2.5 distributions from satellite AOD at 1 km2(exp) resolution for 2011 over the northeastern US by applying relationships between surface PM2.5 and column AOD (calculated offline from speciated mass distributions) from a regional air quality model (CMAQ; 12×12 km2(exp) horizontal resolution). Seasonal average satellite-derived PM2.5 reveals more spatial detail and best captures observed surface PM2.5 levels during summer. At the daily scale, however, satellite-derived PM2.5 is not only subject to measurement uncertainties from satellite instruments, but more importantly to uncertainties in the relationship between surface PM2.5 and column AOD. Using 11 ground-based AOD measurements within 10 km of surface PM2.5 monitors, we show that uncertainties in modeled PM2.5∕AOD can explain more than 70 % of the spatial and temporal variance in the total uncertainty in daily satellite-derived PM2.5 evaluated at PM2.5 monitors. This finding implies that a successful geophysical approach to deriving daily PM2.5 from satellite AOD requires model skill at capturing day-to-day variations in PM2.5∕AOD relationships. Overall, we estimate that uncertainties in the modeled PM2.5∕AOD lead to an error of 11 µg m−3(exp) in daily satellite-derived PM2.5, and uncertainties in satellite AOD lead to an error of 8 µg m−3(exp). Using multi-platform ground, airborne, and radiosonde measurements, we show that uncertainties of modeled PM2.5∕AOD are mainly driven by model uncertainties in aerosol column mass and speciation, while model representation of relative humidity and aerosol vertical profile shape contributes some systematic biases. The parameterization of aerosol optical properties, which determines the mass extinction efficiency, also contributes to random uncertainty, with the size distribution being the largest source of uncertainty and hygroscopicity of inorganic salt the second largest. Future efforts to reduce uncertainty in geophysical approaches to derive surface PM2.5 from satellite AOD would thus benefit from improving model representation of aerosol vertical distribution and aerosol optical properties, to narrow uncertainty in satellite-derived PM2.5.

aerosol optical depth↗
NASA NTRS2015

Basin-Scale Assessment of the Land Surface Energy Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

This paper compares the annual and monthly components of the simulated energy budget from the North American Land Data Assimilation System phase 2 (NLDAS-2) with reference products over the domains of the 12 River Forecast Centers (RFCs) of the continental United States (CONUS). The simulations are calculated from both operational and research versions of NLDAS-2. The reference radiation components are obtained from the National Aeronautics and Space Administration Surface Radiation Budget product. The reference sensible and latent heat fluxes are obtained from a multitree ensemble method applied to gridded FLUXNET data from the Max Planck Institute, Germany. As these references are obtained from different data sources, they cannot fully close the energy budget, although the range of closure error is less than 15%formean annual results. The analysis here demonstrates the usefulness of basin-scale surface energy budget analysis for evaluating model skill and deficiencies. The operational (i.e., Noah, Mosaic, and VIC) and research (i.e., Noah-I and VIC4.0.5) NLDAS-2 land surface models exhibit similarities and differences in depicting basin-averaged energy components. For example, the energy components of the five models have similar seasonal cycles, but with different magnitudes. Generally, Noah and VIC overestimate (underestimate) sensible (latent) heat flux over several RFCs of the eastern CONUS. In contrast, Mosaic underestimates (overestimates) sensible (latent) heat flux over almost all 12 RFCs. The research Noah-I and VIC4.0.5 versions show moderate-to-large improvements (basin and model dependent) relative to their operational versions, which indicates likely pathways for future improvements in the operational NLDAS-2 system.

Energy↗
NASA NTRSDate not supplied

Tracking Magnetic Perturbations, dB/dt and Geomagnetic Indices for Geospace Storms on a Routine Basis at the CCMC

The first comprehensive assessment of geospace model skill to specify magnetic perturbations (delta-B) on the ground and their time derivative (dB/dt) was performed at the Community Coordinated Modeling Center starting in 2010. This study resulted in the addition of the Space Weather Modling Framework to the suite of operational models run by the NOAA Space Weather Prediction Center (SWPC). Since then, magnetic pertubations have been made available on a larger scale for Run-on-Request simulations in geospace at the CCMC. We will demonstrate recent additions to the suite of analysis tools and model results including magnetic perturbations at more stations and on a grid of positions from both, original model outputs (SWMF using preset run configurations) and post-processed calculations using CalcDeltaB and their analysis and visualization using the open-source Kamodo data access and analysis suite and the Comprehensive Assessment of Models and Events using Library tools (CAMEL) application.

Lutz Rastaetter↗
NASA NTRS1984

Forecasts of the 500 mb height using a dynamically oriented statistical model

The forecast skill of a simple dynamically inspired statistical model of the Northern Hemisphere 500 mb height field is evaluated in spectral and physical space for a variety of forecast lead times (1-32 days) and predictand averaging times (1-32 days). The model includes viscous damping, wave propagation, climatology and implicit stochastic forcing. The largest model skill was found for forecasts of the zonal flow and the largest waves. In general, the largest forecast skills were also associated with the largest forecast error, there being a slight geographic phase shift of the skill with respect to the error. Model skills for climate (time-averaged) forecasts are greater when using instantaneous rather than time averages to forecast time averages. Analysis of model errors suggests areas for improvement in representing forcing terms and model physics. However, the model error fields are largely 'white noise' which suggests that global forecast skills substantially larger than those obtained here are unlikely to be achieved by more sophisticated models.

Roads, J. O.↗
NASA NTRS2009

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

Reichle, Rolf↗
NASA NTRS1995

Mean Sea Level Derived from Altimetry and Wind-Driven Numerical Models in the Indian Ocean

Wind-driven model skill in simulating sea level variations in the Indian Ocean depends on our knowledge of the mean ocean dynamic topography. This is demonstrated by running the nonlinear or linear version of a shallow-water model driven by observed winds over Geosat and TOPEX periods. Geosat variations are assimilated in the nonlinear shallow-water model with the objective of obtaining topography data.

numerical models Indian ocean mean sea level remot↗
NASA NTRS2016

A Model-Model and Data-Model Comparison for the Early Eocene Hydrological Cycle

A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP=dT ) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a match with geologic data. Further data from low-latitude regions and better constraints on early Eocene CO2 are now required to discriminate between these model simulations given the large error bars on paleoprecipitation estimates. Given the clear differences between simulated precipitation distributions within the ensemble, our results suggest that paleohydrological data offer an independent means by which to evaluate model skill for warm climates.

Boundary conditions↗
NASA NTRS2016

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters : Aerosols - Part 2

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

aerosol retrieval↗
NASA NTRS2021

Diagnosing Seasonal to Multi-decadal Phytoplankton Group Dynamics in a Highly Productive Coastal Ecosystem

The Santa Barbara Channel, CA (SBC) is a biodiverse marine ecosystem fueled largely by phytoplankton productivity, and the composition of the phytoplankton community influences the magnitude and fates of this productivity. Here, we create a 22-year monthly time series of phytoplankton biomarker pigment concentrations in the SBC by combining 12 years of high performance liquid chromatography phytoplankton pigment concentrations with bio-optical models and 10 additional years of bio-optical observations. The bio-optical models skillfully predict biomarker pigment concentrations representative of five distinct phytoplankton groups (PGs; diatoms, dinoflagellates, chlorophytes, prymnesiophytes, and picophytoplankton) and resolve seasonal responses to the annual upwelling-relaxation cycle for all PGs except the dinoflagellates. Our observations indicate that nanophytoplankton groups respond most rapidly to seasonal upwelling, followed by diatoms, and then by picophytoplankton as the water column stratifies in the summer. A Regional Ocean Modeling System (ROMS) solution is used to relate advection of different source waters to the observed PG dynamics. The ROMS simulation results suggest that, on seasonal time scales, pronounced cross-SBC differences in PG seasonality are related to cross-SBC differences in source waters. El Niño Southern Oscillation events drive interannual variability in the upwelling response of most PGs. On decadal time scales, dinoflagellate blooms are associated with the warm phase of the North Pacific Gyre Oscillation and anomalous advection of Southern California Bight source waters into the SBC. Taken together, our results provide a novel view of phytoplankton community succession in response to seasonal upwelling by considering the dynamics of pico- and nano-phytoplankton and suggest that regional surface ocean advection plays a substantial role in driving phytoplankton composition in the SBC.

Phytoplankton↗
NASA NTRS2020

A Statistical Model to Predict the Extratropical Transition of Tropical Cyclones

This paper introduces a logistic regression model for the extratropical transition(ET) of tropical cyclones in the North Atlantic and the Western North Pacific, using elastic net regularization to select predictors and estimate coefficients.Predictors are chosen from the 1979-2017 best track and reanalysis datasets, and verification is done against the tropical/extratropical labels in the best track data. In an independent test set, the model skillfully predicts ET at lead times up to two days, with latitude and sea surface temperature as its most important predictors. At a lead time of 24 h, it predicts ET with a Matthews correlation coefficient of 0.4 in the North Atlantic, and 0.6 in the Western North Pacific. It identifies 80% of storms undergoing ET in the North Atlantic, and 92% of those in the Western North Pacific. 90% of transition time errors are less than 24 h. Select examples of the model's performance on individual storms illustrate its strengths and weaknesses.Two versions of the model are presented: an "operational model" that may provide baseline guidance for operational forecasts, and a "hazard model"that can be integrated into statistical TC risk models. As instantaneous diagnostics for tropical/extratropical status, both models' zero lead time predictions perform about as well as the widely used Cyclone Phase Space (CPS) in the Western North Pacific and better than the CPS in the North Atlantic, and predict the timings of the transitions better than CPS in both basins.

Melanie Bieli↗
NASA NTRS2006

Metrics for Linear Kinematic Features in Sea Ice

The treatment of leads as cracks or discontinuities (see Coon et al. presentation) requires some shift in the procedure of evaluation and comparison of lead-resolving models and their validation against observations. Common metrics used to evaluate ice model skills are by and large an adaptation of a least square "metric" adopted from operational numerical weather prediction data assimilation systems and are most appropriate for continuous fields and Eilerian systems where the observations and predictions are commensurate. However, this class of metrics suffers from some flaws in areas of sharp gradients and discontinuities (e.g., leads) and when Lagrangian treatments are more natural. After a brief review of these metrics and their performance in areas of sharp gradients, we present two new metrics specifically designed to measure model accuracy in representing linear features (e.g., leads). The indices developed circumvent the requirement that both the observations and model variables be commensurate (i.e., measured with the same units) by considering the frequencies of the features of interest/importance. We illustrate the metrics by scoring several hypothetical "simulated" discontinuity fields against the lead interpreted from RGPS observations.

Levy, G.↗
NASA NTRS2019

Evaluating the Operational Application of SMAP for Global Agricultural Drought Monitoring

Over the past two decades, remote sensing has made possible the routine global monitoring of surface soil moisture. Regionalagricultural drought monitoring is one of the most logicalapplication areas for such monitoring. However, remote sensing alone provides soil moisture information for only the top few centimetersof the soil profile, while agricultural drought monitoring requires knowledge of the amount of water present in the entireroot zone. The assimilation of remotely sensed soil moisture productsinto continuous soil water balance models provides a way ofaddressing this shortcoming. Here, we describe the assimilationof NASA's soil moisture active passive (SMAP) surface soil moisture data into the United States Department of Agriculture Foreign Agricultural Service (USDA FAS) Palmer model and assess the impactof SMAP on USDA FAS drought monitoring capabilities. Theassimilation of SMAP is specifically designed to enhance the model skill and the USDA FAS drought capabilities by correcting for randomerrors inherent in its rainfall forcing data. The performanceof this SMAP-based assimilation system is evaluated using two approaches.At global scale, the accuracy of the system is assessed by examining the lagged correlation agreement between soil moistureand the normalized difference vegetation index (NDVI). Additional regional-scale evaluation using in situ-based soil moisture estimatesis carried out at seven of the SMAP core Cal/Val sites located in theUSA. Both types of analysis demonstrate the value of assimilating SMAP into the USDA FAS Palmer model and its potential to enhance operational USDA FAS root-zone soil moisture information.

Mladenova, Iliana E.↗
NASA NTRS2018

Electrodynamic Dust Shield (EDS) Preparation for MISSE-11 Launch

The dusty surfaces of the Moon, Mars, and various asteroids present a significant challenge to NASA’s manned and unmanned space exploration efforts. The fine, electrostatically charged dust is difficult to remove and has resulted in vision obscuration, false instrument readings, contamination, elevated temperatures, performance reduction, and equipment failure. To alleviate these problems, NASA KSC’s Electrostatics and Surface Physics Laboratory (ESPL) is developing active dust mitigation systems for solar system exploration and in situ resource utilization (ISRU). Part of KSC’s Swamp Works system, the lab emphasizes fast-paced, hands-on, cost-effective, and collaborative innovation. The Electrodynamic Dust Shield (EDS) is an ESPL technology being developed to prevent dust accumulation on space components. It consists of a dielectric substrate embedded with parallel electrodes which, when applied with high voltage out-of-phase waveforms, produce a traveling electric field wave that scatters dust particles from its surface via dielectrophoretic and electrostatic forces. The EDS is currently fully functional and has been tested for scalability and endurance in reduced gravity/pressure flight. Next, it will be part of the May 2019 Materials International Space Station Experiment-11 (MISSE-11) payload, which will test small shield samples for performance durability with exposure to the harsh space environment. The summer objective was to test EDS functionality before active and passive dust shield samples launch on MISSE-11, in order to screen for good flight/control samples as well as to compare pre-flight and post-flight clearing efficiencies. I imaged glass and Kapton shields of 2-phase and 3-phase electrode configurations with the Keyence VHX-5000 digital microscope to check for damage before and after all testing for a qualitative pre-flight baseline; helped with vacuum testing of high-voltage shield breakdown; assembled shields and wires using Electrobond 004 silver epoxy; and helped with vacuum and cryogenic dust clearance testing of assembled EDS systems. I learned CAD (computer-aided design) and 3D printing skills to create parts for a shaker table/motor assembly, which will allow for repeatable experiments by evening out EDS dust distribution in a consistent manner prior to dust scattering testing. I will also be improving the interfacing with Alpha Space’s prototype Data Communications Unit (DCU), a payload component to control power to the EDS and store data, by mapping the DCU structure upon power-up and writing shell scripts to improve various processes. Finally, I also CADed and 3D-printed plastic supports for three different geometries of the Electrostatic Precipitator (ESP), a project that aims to use high voltage electrodes to charge and filter out dust from the Martian atmosphere drawn for ISRU devices. This work on dust mitigation technologies will help to support future robotic and human space exploration missions, including NASA’s Journey to Mars; the EDS has especially significant applications to spacecraft solar panels, thermal radiators, viewports, and astronaut visors. This opportunity has also allowed me to become more familiar with various lab equipment and hardware testing, develop key modeling skills in SolidWorks, explore past and present components critical to America’s space program, work with inspiring peers and mentors, and ascertain my dream of working permanently for NASA.

space↗
NASA NTRS2020

GISS‐E2.1: Configurations and Climatology

This paper describes the GISS‐E2.1 contribution to the Coupled Model Intercomparison Project, Phase 6 (CMIP6). This model version differs from the predecessor model (GISS‐E2) chiefly due to parameterization improvements to the atmospheric and ocean model components, while keeping atmospheric resolution the same. Model skill when compared to modern era climatologies is significantly higher than in previous versions. Additionally, updates in forcings have a material impact on the results. In particular, there have been specific improvements in representations of modes of variability (such as the Madden‐Julian Oscillation and other modes in the Pacific) and significant improvements in the simulation of the climate of the Southern Oceans, including sea ice. The effective climate sensitivity to 2xCO2 is slightly higher than previously at 2.7‐‐3.1°C (depending on version), and is a result of lower CO2 radiative forcing and stronger positive feedbacks.

General Circulation Model↗
NASA NTRS2002

Forcing a Global, Offline Land Surface Modeling System with Observation-Based Fields

The Global Land Data Assimilation System (GLDAS) drives multiple uncoupled land surface models in order to produce optimal output fields of surface states in near-real time, globally, at 1/4 degree spatial resolution. These fields are then made available for coupled atmospheric model initialization and further research. One of the unique aspects of GLDAS is its ability to ingest both modeled and observation-derived forcing for running global scale land surface models. This paper compares results of runs forced by modeled and observed precipitation and shortwave radiation fields. Differences are examined and the impact of the observations on model skill is assessed.

Rodell, Matthew↗
NASA NTRS2004

An Enabling Technology for New Planning and Scheduling Paradigms

The Night Projects Directorate at NASA's Marshall Space Flight Center is developing a new planning and scheduling environment and a new scheduling algorithm to enable a paradigm shift in planning and scheduling concepts. Over the past 33 years Marshall has developed and evolved a paradigm for generating payload timelines for Skylab, Spacelab, various other Shuttle payloads, and the International Space Station. The current paradigm starts by collecting the requirements, called ?ask models," from the scientists and technologists for the tasks that are to be scheduled. Because of shortcomings in the current modeling schema, some requirements are entered as notes. Next, a cadre with knowledge of vehicle and hardware modifies these models to encompass and be compatible with the hardware model; again, notes are added when the modeling schema does not provide a better way to represent the requirements. Finally, the models are modified to be compatible with the scheduling engine. Then the models are submitted to the scheduling engine for automatic scheduling or, when requirements are expressed in notes, the timeline is built manually. A future paradigm would provide a scheduling engine that accepts separate science models and hardware models. The modeling schema would have the capability to represent all the requirements without resorting to notes. Furthermore, the scheduling engine would not require that the models be modified to account for the capabilities (limitations) of the scheduling engine. The enabling technology under development at Marshall has three major components: (1) A new modeling schema allows expressing all the requirements of the tasks without resorting to notes or awkward contrivances. The chosen modeling schema is both maximally expressive and easy to use. It utilizes graphical methods to show hierarchies of task constraints and networks of temporal relationships. (2) A new scheduling algorithm automatically schedules the models without the intervention of a scheduling expert. The algorithm is tuned for the constraint hierarchies and the complex temporal relationships provided by the modeling schema. It has an extensive search algorithm that can exploit timing flexibilities and constraint and relationship options. (3) An innovative architecture allows multiple remote users to simultaneously model science and technology requirements and other users to model vehicle and hardware characteristics. The architecture allows the remote users to submit scheduling requests directly to the scheduling engine and immediately see the results. These three components are integrated so that science and technology experts with no knowledge of the vehicle or hardware subsystems and no knowledge of the internal workings of the scheduling engine have the ability to build and submit scheduling requests and see the results. The immediate feedback will hone the users' modeling skills and ultimately enable them to produce the desired timeline. This paper summarizes the three components of the enabling technology and describes how this technology would make a new paradigm possible.

Jaap, John↗
NASA NTRS2004

Enabling a New Planning and Scheduling Paradigm

The Flight Projects Directorate at NASA's Marshall Space Flight Center is developing a new planning and scheduling environment and a new scheduling algorithm to enable a paradigm shift in planning and scheduling concepts. Over the past 33 years Marshall has developed and evolved a paradigm for generating payload timelines for Skylab, Spacelab, various other Shuttle payloads, and the International Space Station. The current paradigm starts by collecting the requirements, called "tasks models," from the scientists and technologists for the tasks that they want to be done. Because of shortcomings in the current modeling schema, some requirements are entered as notes. Next a cadre with knowledge of vehicle and hardware modifies these models to encompass and be compatible with the hardware model; again, notes are added when the modeling schema does not provide a better way to represent the requirements. Finally, another cadre further modifies the models to be compatible with the scheduling engine. This last cadre also submits the models to the scheduling engine or builds the timeline manually to accommodate requirements that are expressed in notes. A future paradigm would provide a scheduling engine that accepts separate science models and hardware models. The modeling schema would have the capability to represent all the requirements without resorting to notes. Furthermore, the scheduling engine would not require that the models be modified to account for the capabilities (limitations) of the scheduling engine. The enabling technology under development at Marshall has three major components. (1) A new modeling schema allows expressing all the requirements of the tasks without resorting to notes or awkward contrivances. The chosen modeling schema is both maximally expressive and easy to use. It utilizes graphics methods to show hierarchies of task constraints and networks of temporal relationships. (2) A new scheduling algorithm automatically schedules the models without the intervention of a scheduling expert. The algorithm is tuned for the constraint hierarchies and the complex temporal relationships provided by the modeling schema. It has an extensive search algorithm which can exploit timing flexibilities and constraint and relationship options. (3) A web-based architecture allows multiple remote users to simultaneously model science and technology requirements and other users to model vehicle and hardware characteristics. The architecture allows the users to submit scheduling requests directly to the scheduling engine and immediately see the results. These three components are integrated so that science and technology experts with no knowledge of the vehicle or hardware subsystems and no knowledge of the internal workings of the scheduling engine have the ability to build and submit scheduling requests and see the results. The immediate feedback will hone the users' modeling skills and ultimately enable them to produce the desired timeline. This paper summarizes the three components of the enabling technology and describes how this technology would make a new paradigm possible.

Jaap, John↗
NASA NTRS2005

A Global Rapid Integrated Monitoring System for Water Cycle and Water Resource Assessment (Global-RIMS)

The main focus of our work was to solidify underlying data sets, the data processing tools and the modeling environment needed to perform a series of long-term global and regional hydrological simulations leading eventually to routine hydrometeorological predictions. A water and energy budget synthesis was developed for the Mississippi River Basin (Roads et al. 2003), in order to understand better what kinds of errors exist in current hydrometeorological data sets. This study is now being extended globally with a larger number of observations and model based data sets under the new NASA NEWS program. A global comparison of a number of precipitation data sets was subsequently carried out (Fekete et al. 2004) in which it was further shown that reanalysis precipitation has substantial problems, which subsequently led us to the development of a precipitation assimilation effort (Nunes and Roads 2005). We believe that with current levels of model skill in predicting precipitation that precipitation assimilation is necessary to get the appropriate land surface forcing.

Roads, John↗