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Heating distributions from analysis of the National Meteorological Center and European Center for Medium Range Weather Forecasts data sets; methods used and problems involved in the inference of diabatic heating; the relationship between differential heating and energy transport; and recommendations on the inference of heat soruces and heat sinks for the planetary show are discussed.
The National Center of Atmospheric Research (NCAR) Community Climate Model Version 1 (CCM1's) simulation of the modern arctic climate is evaluated by comparing a five-year seasonal cycle simulation with the European Center for Medium-Range Weather Forecasts (ECMWF) global analyses. The sea level pressure (SLP), storm tracks, vertical cross section of height, 500-hPa height, total energy budget, and moisture budget are analyzed to investigate the biases in the simulated arctic climate. The results show that the model simulates anomalously low SLP, too much storm activity, and anomalously strong baroclinicity to the west of Greenland and vice versa to the east of Greenland. This bias is mainly attributed to the model's topographic representation of Greenland. First, the broadened Greenland topography in the model distorts the path of cyclone waves over the North Atlantic Ocean. Second, the model oversimulates the ridge over Greenland, which intensifies its blocking effect and steers the cyclone waves clockwise around it and hence produces an artificial circum-Greenland trough. These biases are significantly alleviated when the horizontal resolution increases to T42. Over the Arctic basin, the model simulates large amounts of low-level (stratus) clouds in winter and almost no stratus in summer, which is opposite to the observations. This bias is mainly due to the location of the simulated SLP features and the negative anomaly of storm activity, which prevent the transport of moisture into this region during summer but favor this transport in winter. The moisture budget analysis shows that the model's net annual precipitation (P-E) between 70 deg N and the North Pole is 6.6 times larger than the observations and the model transports six times more moisture into this region. The bias in the advection term is attributed to the positive moisture fixer scheme and the distorted flow pattern. However, the excessive moisture transport into the Arctic basin does not solely result from the advection term. The contribution by the moisture fixer is as large as from advection. By contrast, the semi-Lagrangian transport scheme used in the CCM2 significantly improves the moisture simulation for this region; however, globally the error is as serious as for the positive moisture fixer scheme. Finally, because the model has such serious problems in simulating the present arctic climate, its simulations of past and future climate change for this region are questionable.
Alfvn waves play critical roles in the electrodynamic coupling of plasmas at magnetically conjugate regions in near-Earth space. Associated electric (E*) and magnetic (dec B*) field perturbations sampled by sensors on satellites in low-Earth orbits are generally super positions of incident and reflected waves. However, lack of knowledge about ionospheric reflection coefficients (alpha) hinders understanding of generator outputs and load absorption of Alfvn wave energies. Here we demonstrate a new method for estimating using satellite measurements of ambient E* and dec B* then apply it to a case in which the Communication Navigation Outage Forecasting System (CNOFS) satellite flew conjugate to the field of view of a 630.0 nm all-sky imager at El Leoncito, Argentina, while medium-scale traveling ionosphere disturbances were detected in its field of view. In regions of relatively large amplitudes of E* and B*,calculated values ranged between 0.67 and 0.88. This implies that due to impedance mismatches, the generator ionosphere puts out significantly more electromagnetic energy than the load can absorb. Our analysis also uncovered caveats concerning the methods range of applicability in regions of low E* and B*. The method can be validated in future satellite-based auroral studies where energetic particle precipitation fluxes can be used to make independent estimates of alpha.
Topics covered include: 3D Endoscope to Boost Safety, Cut Cost of Surgery; Audio App Brings a Better Night's Sleep Liquid Cooling Technology Increases Exercise Efficiency; Algae-Derived Dietary Ingredients Nourish Animals; Space Grant Research Launches Rehabilitation Chair; Vision Trainer Teaches Focusing Techniques at Home; Aircraft Geared Architecture Reduces Fuel Cost and Noise; Ubiquitous Supercritical Wing Design Cuts Billions in Fuel Costs; Flight Controller Software Protects Lightweight Flexible Aircraft; Cabin Pressure Monitors Notify Pilots to Save Lives; Ionospheric Mapping Software Ensures Accuracy of Pilots' GPS; Water Mapping Technology Rebuilds Lives in Arid Regions; Shock Absorbers Save Structures and Lives during Earthquakes; Software Facilitates Sharing of Water Quality Data Worldwide; Underwater Adhesives Retrofit Pipelines with Advanced Sensors; Laser Imaging Video Camera Sees through Fire, Fog, Smoke; 3D Lasers Increase Efficiency, Safety of Moving Machines; Air Revitalization System Enables Excursions to the Stratosphere; Magnetic Fluids Deliver Better Speaker Sound Quality; Bioreactor Yields Extracts for Skin Cream; Private Astronaut Training Prepares Commercial Crews of Tomorrow; Activity Monitors Help Users Get Optimum Sun Exposure; LEDs Illuminate Bulbs for Better Sleep, Wake Cycles; Charged Particles Kill Pathogens and Round Up Dust; Balance Devices Train Golfers for a Consistent Swing; Landsat Imagery Enables Global Studies of Surface Trends; Ruggedized Spectrometers Are Built for Tough Jobs; Gas Conversion Systems Reclaim Fuel for Industry; Remote Sensing Technologies Mitigate Drought; Satellite Data Inform Forecasts of Crop Growth; Probes Measure Gases for Environmental Research; Cloud Computing Technologies Facilitate Earth Research; Software Cuts Homebuilding Costs, Increases Energy Efficiency; Portable Planetariums Teach Science; Schedule Analysis Software Saves Time for Project Planners; Sound Modeling Simplifies Vehicle Noise Management; Custom 3D Printers Revolutionize Space Supply Chain; Improved Calibration Shows Images' True Colors; Micromachined Parts Advance Medicine, Astrophysics, and More; Metalworking Techniques Unlock a Unique Alloy; Low-Cost Sensors Deliver Nanometer-Accurate Measurements; Electrical Monitoring Devices Save on Time and Cost; Dry Lubricant Smooths the Way for Space Travel, Industry; and Compact Vapor Chamber Cools Critical Components.
The Soil Moisture Active Passive (SMAP) mission is an L-band mission scheduled for launch in Jan. 2015. The SMAP instruments consist of a radar and a radiometer to obtain complementary information from space for soil moisture and freeze/thaw state research and applications. By utilizing novel designs in antenna construction, retrieval algorithms, and acquisition hardware, SMAP provides a capability for global mapping of soil moisture and freeze/thaw state with unprecedented accuracy, resolution, and coverage. This improvement in hydrosphere state measurement is expected to advance our understanding of the processes that link the terrestrial water, energy and carbon cycles, improve our capability in flood prediction and drought monitoring, and enhance our skills in weather and climate forecast. For swath-based soil moisture measurement, SMAP generates three operational geophysical data products: (1) the radiometer-only soil moisture product (L2_SM_P) posted at 36-kilometer resolution, (2) the radar-only soil moisture product (L2_SM_A) posted at 3-kilometers resolution, and (3) the radar-radiometer combined soil moisture product (L2_SM_AP) posted at 9-kilometers resolution. Each product draws on the strengths of the underlying sensor(s) and plays a unique role in hydroclimatological and hydrometeorological applications. A full suite of SMAP data products is given in Table 1.
The author has identified the following significant results. The total cost associated with satellite snow cover area measurement (SATSCAM) in the Colorado ASVT was $2,050 which equates to 0.22/sq km. When extrapolated to the 2,238,890 km area impacted by snow-survey forecasting in the Western United States, the total yearly cost of employing SATSCAM is approximately $493k. The estimated total benefits to hydroeletric energy production is $10m yearly, with the Pacific Northwest receiving the smallest benefits, and the Rio Grande region the highest. Irrigated agriculture receives a yearly total benefit of $38m, with the Lower Colorado region receiving the largest per acre benefit and the Pacific Northwest receiving the lowest.
A conceptual models of the commercial air transportation industry is developed which can be used to predict trends in economics, demand, and consumption. The methodology is based on digraph theory, which considers the interaction of variables and propagation of changes. Air transportation economics are treated by examination of major variables, their relationships, historic trends, and calculation of regression coefficients. A description of the modeling technique and a compilation of historic airline industry statistics used to determine interaction coefficients are included. Results of model validations show negligible difference between actual and projected values over the twenty-eight year period of 1959 to 1976. A limited application of the method presents forecasts of air tranportation industry demand, growth, revenue, costs, and fuel consumption to 2020 for two scenarios of future economic growth and energy consumption.
The purpose of this Science and Implementation Plan is to describe GAPP science objectives and the activities required to meet these objectives, both specifically for the near-term and more generally for the longer-term. The GEWEX Americas Prediction Project (GAPP) is part of the Global Energy and Water Cycle Experiment (GEWEX) initiative that is aimed at observing, understanding and modeling the hydrological cycle and energy fluxes at various time and spatial scales. The mission of GAPP is to demonstrate skill in predicting changes in water resources over intraseasonal-to-interannual time scales, as an integral part of the climate system.
Aims. Our main aim is to study the relationship between low-energy solar particles (energies below 1 MeV) and very narrow coronal mass ejections (“jets” with angular width ≤ 20°). Methods. For this purpose, we considered 125 very narrow coronal mass ejections (CMEs) from 1999 to 2003 that are potentially associated with low-energy solar particles (LESPs). These events were chosen on the basis of their source location. We studied only very narrow CMEs at the western limb, which are expected to have good magnetic connectivity with Earth. Results. We found 24 very narrow CMEs associated with energetic particles such as ions (protons and 3He), electrons, or both. We show that arrival times at Earth of energetic particles are consistent with onset times of the respective CMEs, and that in the same time intervals, there are no other potential sources of energetic particles. We also demonstrate statistical differences for the angular width distributions using the Kolmogorov–Smirnov test for angular widths for these 24 events. We consider a coherent sample of jets (mostly originating from boundaries of coronal holes) to identify properties of events that produce solar energetic particles (velocities, widths, and position angles). Our study presents a new approach and result: very narrow CMEs can generate low-energy particles in the vicinity of Earth without other activity on the Sun. The results could be very useful for space weather forecasting.
Solar drivers of severe space weather can be predicted from line-of-sight magnetograms, via a free-energy proxy measured from the neutral lines. This can be done in near real time. In addition to depending strongly on the free magnetic energy, an active region's chance of having a major eruption depends strongly on other aspects of the evolving magnetic field (e.g., its complexity and flux emergence).
A forecasting protocol termed the "prospective approach' was used to examine probable futures relative to coastal applications of satellite data. Significant variables include the energy situation, the national economy, national Earth satellite programs, and coastal zone research, commercial activity, and regulatory activity. Alternative scenarios for the period until 1986 are presented. Possible response by state/local remote sensing centers include operational applications for users, input to geo-base information systems (GIS), development of decision-making algorithms using GIS data, and long term research programs for coastal management using merged satellite and traditional data.
Fundamental to improving the understanding of the total Earth system are increased and improved observations. In the coming decade several spaceborne instrumented platforms will be constructed and implemented. These platforms will, in large, be housing the NASA Earth Observing System (EOS) instrument suite. One of the proposed instruments is a wind profiling system which is currently referred to as the Laser Atmospheric Wind Sounder (LAWS). This instrument will use a CO2 Doppler lidar wind profiler to give wind measurements with a vertical and horizontal resolution which has yet to be seen globally. The LAWS instrument is now a candidate for launch on a NASA EOS-B platform and is fundamental to increasing our understanding of Earth system science. The LAWS data sets will form an integral component of the temporally continuous data base needed for research of the coupled climate systems. This instrument's observations will aid in giving an improved description of the atmospheric circulation, including the transports of energy, momentum, moisture, trace gases, and aerosols. Also, the wind data will be assimilated and used as the initial state for many global forecast models at various operational centers. Results of system simulation experiments are discussed, and future experiments are described.
VAS satellite retrievals and derived parameters used in forecasting severe local storms were evaluated against corresponding radiosonde values. VAS products were also compared with the first-guess input to the retrieval algorithm. The evaluation methodology was to pair each radiosonde observation with the closest VAS retrieval within 50 km during a four-month period in 1986. VAS temperatures agreed closely with radiosonde values; dewpoints showed less agreement. Sounding differences were poorly correlated with the number of pixels from which the retrievals were prepared. VAS discrepancies usually were not well correlated with first-guess errors. Horizontal gradients of VAS products were stronger than those from radiosondes. VAS precipitable water agreed better with ground truth than did dewpoints at individual levels, but VAS thicknesses were not much improved. Results for severe storms forecasting parameters indicated that discrepancies increased with the amount of manipulation required during computation. The lifted index showed the best agreement; positive bouyant energy showed poor comparisons.
We outline a plan to develop a physics based predictive toolset RISCS to describe the interplanetary energetic particle and radiation environment throughout the inner heliosphere, including at the Earth. To forecast and "nowcast" the radiation environment requires the fusing of three components: 1) the ability to provide probabilities for incipient solar activity; 2) the use of these probabilities and daily coronal and solar wind observations to model the 3D spatial and temporal heliosphere, including magnetic field structure and transients, within 10 AU; and 3) the ability to model the acceleration and transport of energetic particles based on current and anticipated coronal and heliospheric conditions. We describe how to address 1) - 3) based on our existing, well developed, and validated codes and models. The goal of RISCS toolset is to provide an operational forecast and "nowcast" capability that will a) predict solar energetic particle (SEP) intensities; b) spectra for protons and heavy ions; c) predict maximum energies and their duration; d) SEP composition; e) cosmic ray intensities, and f) plasma parameters, including shock arrival times, strength and obliquity at any given heliospheric location and time. The toolset would have a 72 hour predicative capability, with associated probabilistic bounds, that would be updated hourly thereafter to improve the predicted event(s) and reduce the associated probability bounds. The RISCS toolset would be highly adaptable and portable, capable of running on a variety of platforms to accommodate various operational needs and requirements.
Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.
We outline a plan to develop and transition a physics based predictive toolset called The Radiation, Interplanetary Shocks, and Coronal Sources (RISCS) to describe the interplanetary energetic particle and radiation environment throughout the inner heliosphere, including at the Earth. To forecast and "nowcast" the radiation environment requires the fusing of three components: 1) the ability to provide probabilities for incipient solar activity; 2) the use of these probabilities and daily coronal and solar wind observations to model the 3D spatial and temporal heliosphere, including magnetic field structure and transients, within 10 Astronomical Units; and 3) the ability to model the acceleration and transport of energetic particles based on current and anticipated coronal and heliospheric conditions. We describe how to address 1) - 3) based on our existing, well developed, and validated codes and models. The goal of RISCS toolset is to provide an operational forecast and "nowcast" capability that will a) predict solar energetic particle (SEP) intensities; b) spectra for protons and heavy ions; c) predict maximum energies and their duration; d) SEP composition; e) cosmic ray intensities, and f) plasma parameters, including shock arrival times, strength and obliquity at any given heliospheric location and time. The toolset would have a 72 hour predicative capability, with associated probabilistic bounds, that would be updated hourly thereafter to improve the predicted event(s) and reduce the associated probability bounds. The RISCS toolset would be highly adaptable and portable, capable of running on a variety of platforms to accommodate various operational needs and requirements. The described transition plan is based on a well established approach developed in the Earth Science discipline that ensures that the customer has a tool that meets their needs
The space power system has two sources of energy: photo-voltaic blankets and batteries. The optimal power management problem on-board has two broad operations: off-line power scheduling to determine the load allocation schedule of the next several hours based on the forecast of load and solar power availability. The nature of this study puts less emphasis on speed requirement for computation and more importance on the optimality of the solution. The second category problem, on-line power rescheduling, is needed in the event of occurrence of a contingency to optimally reschedule the loads to minimize the 'unused' or 'wasted' energy while keeping the priority on certain type of load and minimum disturbance of the original optimal schedule determined in the first-stage off-line study. The computational performance of the on-line 'rescheduler' is an important criterion and plays a critical role in the selection of the appropriate tool. The Howard University Center for Energy Systems and Control has developed a hybrid optimization-expert systems based power management program. The pre-scheduler has been developed using a non-linear multi-objective optimization technique called the Outer Approximation method and implemented using the General Algebraic Modeling System (GAMS). The optimization model has the capability of dealing with multiple conflicting objectives viz. maximizing energy utilization, minimizing the variation of load over a day, etc. and incorporates several complex interaction between the loads in a space system. The rescheduling is performed using an expert system developed in PROLOG which utilizes a rule-base for reallocation of the loads in an emergency condition viz. shortage of power due to solar array failure, increase of base load, addition of new activity, repetition of old activity etc. Both the modules handle decision making on battery charging and discharging and allocation of loads over a time-horizon of a day divided into intervals of 10 minutes. The models have been extensively tested using a case study for the Space Station Freedom and the results for the case study will be presented. Several future enhancements of the pre-scheduler and the 'rescheduler' have been outlined which include graphic analyzer for the on-line module, incorporating probabilistic considerations, including spatial location of the loads and the connectivity using a direct current (DC) load flow model.
The representation of convective processes, particularly deep convection in the tropics, remains a persistent problem in climate models. In fact structural biases in the distribution of tropical rainfall in the CMIP5 models is hardly different than that of the CMIP3 versions. Given that regional climate change at higher latitudes is sensitive to the configuration of tropical forcing, this persistent bias is a major issue for the credibility of climate change projections. In this study we use model output from integrations of the NASA Global Earth Observing System Five (GEOS5) climate modeling system to study the evolution of biases in the location and intensity of convective processes. We take advantage of a series of hindcast experiments done in support of the US North American Multi-Model Ensemble (NMME) initiative. For these experiments a nine-month forecast using a coupled model configuration is made approximately every five days over the past 30 years. Each forecast is started with an updated analysis of the ocean, atmosphere and land states. For a given calendar month we have approximately 180 forecasts with daily means of various quantities. These forecasts can be averaged to essentially remove "weather scales" and highlight systematic errors as they evolve. Our primary question is to ask how the spatial structure of daily mean precipitation over the tropics evolves from the initial state and what physical processes are involved. Errors in parameterized convection, various water and energy fluxes and the divergent circulation are found to set up on fast time scales (order five days) compared to errors in the ocean, although SST changes can be non-negligible over that time. For the month of June the difference between forecast day five versus day zero precipitation looks quite similar to the difference between the June precipitation climatology and that from the Global Precipitation Climatology Project (GPCP). We focus much of our analysis on the influence of SST gradients, associated PBL baroclinicity enabled by turbulent mixing, the ensuing PBL moisture convergence, and how changes in these processes relate to convective precipitation bias growth over this short period.