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At least 433 records · Page 24

Operational seasonal and interannual predictions of ocean conditions

Dr. Leetmaa described current work at the U.S. National Meteorological Center (NMC) on coupled systems leading to a seasonal prediction system. He described the way in which ocean thermal data is quality controlled and used in a four dimensional data assimilation system. This consists of a statistical interpolation scheme, a primitive equation ocean general circulation model, and the atmospheric fluxes that are required to force this. This whole process generated dynamically consist thermohaline and velocity fields for the ocean. Currently routine weekly analyses are performed for the Atlantic and Pacific oceans. These analyses are used for ocean climate diagnostics and as initial conditions for coupled forecast models. Specific examples of output products were shown both in the Pacific and the Atlantic Ocean.

Leetmaa, Ants↗

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by 1 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5 %) and +/- 5.0 K (+/- 15 %), respectively. At a given tropospheric level, such perturbations can cause a +/- 25 % variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by +/- 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5%) and +/- 5.0 K (+/- 15%), respectively. At a given tropospheric level, such perturbations can cause a +/- 25% variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗

The Transition of Satellite Observations Assimilated in GEOS to JEDI

In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) in the Goddard Earth Observing System (GEOS), which is used for weather, climate, and air quality forecasts and producing reanalysis datasets, it is necessary to validate the observing system in JEDI. NASA’s Global Modeling and Assimilation Office (GMAO), with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) and adding all the necessary features to replicate existing capability. Various satellite and conventional observations are assimilated by the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures including the GEOS all-sky microwave radiance assimilation framework to assimilate those observation in UFO. Robust tests are conducted to ensure correct configurations of observational data bias correction (BC), quality control (QC), and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations is reported in this presentation.

Jianjun Jin↗

A Comparison of Wind Speed Data from Mechanical and Ultrasonic Anemometers

This study compared the performance of mechanical and ultrasonic anemometers at the Eastern Range (ER; Kennedy Space Center and Cape Canaveral Air Force Station on Florida's Atlantic coast) and the Western Range (WR; Vandenberg Air Force Base on California's Pacific coast). Launch Weather Officers, forecasters, and Range Safety analysts need to understand the performance of wind sensors at the ER and WR for weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The current ER and WR weather tower wind instruments are being changed from the current propeller-and-vane (ER) and cup-and-vane (WR) sensors to ultrasonic sensors through the Range Standardization and Automation (RSA) program. The differences between mechanical and ultrasonic techniques have been found to cause differences in the statistics of peak wind speed in previous studies. The 45th Weather Squadron (45 WS) and the 30th Weather Squadron (30 WS) requested the Applied Meteorology Unit (AMU) to compare data between RSA and current sensors to determine if there are significant differences. Approximately 3 weeks of Legacy and RSA wind data from each range were used in the study, archived during May and June 2005. The ER data spanned the full diurnal cycle, while the WR data was confined to 1000-1600 local time. The sample of 1-minute data from numerous levels on 5 different towers on each range totaled more than 500,000 minutes of data (482,979 minutes of data after quality control). The 10 towers were instrumented at several levels, ranging from 12 ft to 492 ft above ground level. The RSA sensors were collocated at the same vertical levels as the present sensors and typically within 15 ft horizontally of each another. Data from a total of 53 RSA ultrasonic sensors, collocated with present sensors were compared. The 1-minute average wind speed/direction and the 1-second peak wind speed/direction were compared.

Short, D.↗

Some comparison of ECMWF 3b and GFDL 3b analyses in the tropics

Owing to the problems that data assimilation procedures have in analyzing data in the tropics and to the apparent differences in the descriptions of the European Center for Medium Range Weather Forecasts (ECMWF) and Geophysical Fluid Dynamics Laboratory (GFDL) assimilation suites, a brief comparison was done of the resulting analyses in the tropics. Three cases each were selected for Standard Operating Procedures 1 and 2 at the 200 and 850 mb levels, the wind fields for 25 deg N 25 deg S were partitioned into a rotational and divergent component, and various statistics of each were calculated.

Julian, P. R.↗

Climate Change Adaptation Activities at the NASA John F. Kennedy Space Center, FL., USA

In 2010, the Office of Strategic Infrastructure and Earth Sciences established the Climate Adaptation Science Investigators (CASI) program to integrate climate change forecasts and knowledge into sustainable management of infrastructure and operations needed for the NASA mission. NASA operates 10 field centers valued at $32 billion dollars, occupies 191,000 acres and employs 58,000 people. CASI climate change and sea-level rise forecasts focus on the 2050 and 2080 time periods. At the 140,000 acre Kennedy Space Center (KSC) data are used to simulate impacts on infrastructure, operations, and unique natural resources. KSC launch and processing facilities represent a valued national asset located in an area with high biodiversity including 33 species of special management concern. Numerical and advanced Bayesian and Monte Carlo statistical modeling is being conducted using LiDAR digital elevation models coupled with relevant GIS layers to assess potential future conditions. Results are provided to the Environmental Management Branch, Master Planning, Construction of Facilities, Engineering Construction Innovation Committee and our regional partners to support Spaceport development, management, and adaptation planning and design. Potential impacts to natural resources include conversion of 50% of the Center to open water, elevation of the surficial aquifer, alterations of rainfall and evapotranspiration patterns, conversion of salt marsh to mangrove forest, reductions in distribution and extent of upland habitats, overwash of the barrier island dune system, increases in heat stress days, and releases of chemicals from legacy contamination sites. CASI has proven successful in bringing climate change planning to KSC including recognition of the need to increase resiliency and development of a green managed shoreline retreat approach to maintain coastal ecosystem services while maximizing life expectancy of Center launch and payload processing resources.

plant communities↗

Impacts of Marine Surface Pressure Observations From A Spaceborne Differential Absorption Radar Investigated With an Observing System Simulation Experiment

A new instrument has been proposed for measuring surface air pressure over the marine surface with a combined active/passive scanning multi-channel differential absorption radar (DAR) to provide an estimate of the total atmospheric column oxygen content. A demonstrator instrument, the Microwave Barometric Radar and Sounder (MBARS), has been funded by the National Aeronautics and Space Administration (NASA) for airborne test missions. Here, a proof-of-concept study to evaluate the potential impact of spaceborne surface pressure data on numerical weather prediction is performed using the Goddard Modeling and Assimilation Office global observing system simulation experiment (OSSE) framework. This OSSE framework employs the Goddard Earth Observing System model and the hybrid 4D ensemble variational Gridpoint Statistical Interpolation data assimilation system. Multiple flight and scanning configurations of potential spaceborne orbits are examined. Swath width and observation spacing for the surface pressure data are varied to explore a range of sampling strategies. For wider swaths, the addition of surface pressures reduces the root mean square surface pressure analysis error by as much as 20% over some ocean regions. The forecast sensitivity observation impact tool estimates impacts on the Pacific Ocean basin boundary layer 24-hour forecast temperatures for spaceborne surface pressures on par with rawinsondes and aircraft, and greater impacts than the current network of ships and buoys. The largest forecast impacts are found in the southern hemisphere extratropics.

N.C. Privé↗

Stochastic modeling of the time-advanced equations for climate dynamics

Long term, climatologically significant statistical properties of the atmospheric component of the climate system are examined in an effort to correctly and efficiently incorporate this component into larger models for climate that include oceanic and cryospheric influences and deal realistically with climate replication. The magnetic of the unpredictable (noise) component of long term atmospheric behavior is also studied in order to develop the potential for viable climatological forecasting.

Laurmann, J. A.↗

Study of explosive and nonexplosive cyclogenesis during FGGE

Explosive cyclogenesis during the winter of the First Global GARP Experiment (January-February 1979) is analyzed using the revised European Centre for Medium Range Weather Forecasts (ECMWF) analyses. Explosive cyclogenesis is defined as a decrease in the sea level pressure at the rate of 1 mb/h for at least 12 h. Diagnostics for 23 explosively developing cases and 16 nonexplosive cases are evaluated. Parameters compared include the dry static stability, low-level relative vorticity, vorticity advection, upper-level divergence, and kinematic vertical velocities. These parameters are compared statistically at the initial, 12-, and 24-h time periods. Parameters for which the explosive and nonexplosive cyclone ensembles were statistically separable are the kinematic vertical velocity and the upper-level divergence and vorticity advection. The strong upper-level processes for the explosive cases at the initial time indicate the importance of upper-tropospheric features in producing the stronger vertical motions and more rapid cyclogenesis.

Wash, Carlyle H.↗

Development and Application of Computational/In Vitro Toxicological Methods for Chemical Hazard Risk Reduction of New Materials for Advanced Weapon Systems

The development of quantitative structure-activity relationship (QSAR) is essential for reducing the chemical hazards of new weapon systems. The current collaboration between HEST (toxicology research and testing), MLPJ (computational chemistry) and PRS (computational chemistry, new propellant synthesis) is focusing R&D efforts on basic research goals that will rapidly transition to useful products for propellant development. Computational methods are being investigated that will assist in forecasting cellular toxicological end-points. Models developed from these chemical structure-toxicity relationships are useful for the prediction of the toxicological endpoints of new related compounds. Research is focusing on the evaluation tools to be used for the discovery of such relationships and the development of models of the mechanisms of action. Combinations of computational chemistry techniques, in vitro toxicity methods, and statistical correlations, will be employed to develop and explore potential predictive relationships; results for series of molecular systems that demonstrate the viability of this approach are reported. A number of hydrazine salts have been synthesized for evaluation. Computational chemistry methods are being used to elucidate the mechanism of action of these salts. Toxicity endpoints such as viability (LDH) and changes in enzyme activity (glutahoione peroxidase and catalase) are being experimentally measured as indicators of cellular damage. Extrapolation from computational/in vitro studies to human toxicity, is the ultimate goal. The product of this program will be a predictive tool to assist in the development of new, less toxic propellants.

Frazier, John M.↗

Journal of Air Transportation, Volume 8, No. 2

The mission of the Journal of Air Transportation (JAT) is to provide the global community immediate key resource information in all areas of air transportation. This journal contains articles on the following:Fuel Consumption Modeling of a Transport Category Aircraft: A FlightOperationsQualityAssurance (F0QA) Analysis;Demand for Air Travel in the United States: Bottom-Up Econometric Estimation and Implications for Forecasts by Origin and Destination Pairs;Blind Flying on the Beam: Aeronautical Communication, Navigation and Surveillance: Its Origins and the Politics of Technology: Part I1 Political Oversight and Promotion;Blind Flying on the Beam: Aeronautical Communication, Navigation and Surveillance: Its Origins and the Politics of Technology: Part 111: Emerging Technologies;Ethics Education in University Aviation Management Programs in the US: Part Two B-Statistical Analysis of Current Practice;Integrating Human Factors into the Human-computer Interface: and How Best to Display Meteorological Information for Critical Aviation Decision-making and Performance.

Bowen, Brent↗

Quantifying the Importance of Selected Drought Indicators for the United States Drought Monitor

Using information theory, our study quantifies the importance of selected indicators for the U.S. Drought Monitor (USDM) maps. We use the technique of mutual information (MI) to measure the importance of any indicator to the USDM, and because MI is derived solely from the data, our findings are independent of any model structure (conceptual, physically-based, or empirical). We also compare these MIs against the drought representation effectiveness ratings in the North America Drought Indices and Indicators Assessment (NADIIA) survey for Koeppen climate zones. This reveals: [1] agreement between some ratings and our MI values (high for example indicators like Standardized Precipitation-Evapotranspiration Index or SPEI); [2] some divergences (for example, soil moisture has high ratings but near-zero MIs for ESA-CCI soil moisture in the Western U.S., indicating the need of another remotely sensed soil moisture source); and [3] new insights into the importance of variables such as Snow Water Equivalent (SWE) that are not included in sources like NADIIA. Further analysis of the MI results yields findings related to: [1] hydrological mechanisms (summertime SWE domination during individual drought events through snowmelt into the water-scarce soil); [2] hydroclimatic types (the top pair of inputs in the Western and non-Western regions are SPEIs and soil moistures respectively); and [3] predictability (high for the California 2012-2017 event, with longer-timescale indicators dominating). Finally, the high MIs between multiple indicators jointly and the USDM indicate potentially high drought forecasting accuracies achievable using only model-based inputs, and the potential for global drought monitoring using only remotely sensed inputs, especially for locations having insufficient in situ observations.

Drought↗

Assimilation of Cloud- and Land-Affected TOVS/ATOVS Level 1B Radiances in DAO's Next Generation Finite-Volume Data Assimilation System

The Physical-space/Finite-volume Data Assimilation System (fvDAS) is the next generation global atmospheric data assimilation system in development at the Data Assimilation Office (DAO) at NASA's Goddard Space Flight Center. It is based on a new finite-volume general circulation model jointly developed by NASA and NCAR, and on the Physical-Space Statistical Analysis System (PSAS) developed at the DAO. In this talk we will focus on the assimilation of data from the (Advanced) TIROS Operational Vertical Sounder (ATOVS), with emphasis on the impact of cloud- and land-affected level 1B radiances. Recently, it has been shown that the use of observations from satellite-borne microwave and infrared radiometers in data assimilation systems consistently increases forecast skill. Considerable effort has been expended over the past two decades, particularly with the (Advanced) TIROS Operational Vertical Sounder (ATOVS), to achieve this result. The positive impact on forecast skill has resulted from improvements in quality control algorithms, systematic error correction schemes, and more sophisticated data assimilation algorithms. Despite these advances, there are still many issues regarding the use of satellite data in data assimilation systems that remain unresolved. In particular, most operational centers still do not assimilate cloud- and land-affected TOVS data. In this study, we evaluate the impact of assimilating cloud-and land-affected TOVS/ATOVS level 1B data in DAO's next generation fvDAS, using a 1D variational scheme. We will discuss the impact of these data on both tropospheric and stratospheric forecasts, as well as on the general aspects of the earth climate system.

Joiner, J.↗

Analysis and Prediction of Weather Impacted Ground Stop Operations

When the air traffic demand is expected to exceed the available airport's capacity for a short period of time, Ground Stop (GS) operations are implemented by Federal Aviation Administration (FAA) Traffic Flow Management (TFM). The GS requires departing aircraft meeting specific criteria to remain on the ground to achieve reduced demands at the constrained destination airport until the end of the GS. This paper provides a high-level overview of the statistical distributions as well as causal factors for the GSs at the major airports in the United States. The GS's character, the weather impact on GSs, GS variations with delays, and the interaction between GSs and Ground Delay Programs (GDPs) at Newark Liberty International Airport (EWR) are investigated. The machine learning methods are used to generate classification models that map the historical airport weather forecast, schedule traffic, and other airport conditions to implemented GS/GDP operations and the models are evaluated using the cross-validations. This modeling approach produced promising results as it yielded an 85% overall classification accuracy to distinguish the implemented GS days from the normal days without GS and GDP operations and a 71% accuracy to differentiate the GS and GDP implemented days from the GDP only days.

Analysis↗

A Multi-Sensor Water Vapor, Temperature and Cloud Climate Data Record: Status of Our MEaSUREs 2012 Project

- Our primary objectives: Incorporate all A-Train water vapor, including small-scale, horizontal and vertical water vapor structure from MODIS (Moderate Resolution Imaging Spectroradiometer) and GPS (Global Positioning System); Use MODIS cloud classification that is collocated at the pixel-scale over the full AIRS/AMSU (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit) swath; Extend summaries to PDFs (Probability Distribution Functions)/higher order moments of water vapor sorted by cloud classes; Establish robust, scale-dependent statistical relationships between cloud, temperature, and water vapor PDFs for the climate modeling community. - We will also: Update our current data record to new CloudSat/CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) cloud classification; Provide merged AIRS and MLS (Microwave Limb Sounder) water vapor profiles using averaging kernels; Include temperature and water vapor from models (ECMWF - European Centre for Medium-Range Weather Forecasts) and re-analyses (MERRA - Modern Era-Retrospective Analysis for Research and Applications); Classify METOP-A (Meteorological Operational Satellite-A) and NOAA (National Oceanic and Atmospheric Administration) satellite water vapor with AVHRR (Advanced Very High Resolution Radiometer) during SNOs (Solar Neutrino Oscillations); Compare with the NVAP-M (re-analysis and extension of the NASA Water Vapor Project (NVAP)) water vapor climatologies; Use existing data sources and mature algorithms, and document processing algorithms.

Fetzer, Eric↗

Evaluating the Impact of AIRS Observations on Regional Forecasts at the SPoRT Center

NASA Short-term Prediction Research and Transition (SPoRT) Center collaborates with operational partners of different sizes and operational goals to improve forecasts using targeted projects and data sets. Modeling and DA activities focus on demonstrating utility of NASA data sets and capabilities within operational systems. SPoRT has successfully assimilated the Atmospheric Infrared Sounder (AIRS) radiance and profile data. A collaborative project is underway with the Joint Center for Satellite Data Assimilation (JCSDA) to use AIRS profiles to better understand the impact of AIRS radiances assimilated within Gridpoint Statistical Interpolation (GSI) in hopes of engaging the operational DA community in a reassessment of assimilation methodologies to more effectively assimilate hyperspectral radiances.

Zavodsky, Bradley↗

Investigation of geomagnetic field forecasting and fluid dynamics of the core

It was established that the total absolute magnetic flux crossing the core- mantle boundary has been a constant of the core motion for the last 50 years. This provides a scalar constraint that could be added to the geometric modelling procedure. The GSFC 8 8/80 model is being evaluated. The absolute magnetic flux linking the CMB to that model was plotted as a function of time during the span covered by the data, and increasing truncation level. The inclusion of the standard error of each Gauss coefficient derived from the statistics of fit in the GSFC 9/80 model is useful. The magnitude and sense (upwelling or downe welling) of vertical fluid motion adjacent to the core-mantle boundary was calculated using the model. Standard errors were found to be sufficiently small at all but one or two of the 40 or more critical points of B sub r. They do not nearly overlap the value gamma u/gamma r = 0. It is concluded that the core is upwelling and downwelling at an observationally detectable level.

Benton, E. R.↗