The Temporal and Probabilistic Relationship between Lightning Jump Occurrence and Radar-Derived Thunderstorm Intensification
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A localized precipitation network has been established over a 4000 sq km region of northern Alabama in support of local weather and climate research at the Global Hydrology and Climate Center (GHCC) in Huntsville. This Cooperative Huntsville-Area Rainfall Measurement (CHARM) network is comprised of over 80 volunteers who manually take daily rainfall measurements from 85 sites. The network also incorporates 20 automated gauges that report data at 1-5 minute intervals on a 24 h a day basis. The average spacing of the gauges in the network is about 6 kin, however coverage in some regions benefit from gauges every 1-2 km. The 24 h rainfall totals from the CHARM network have been used to validate Stage III rainfall estimates of daily and storm totals derived from the WSR-88D radars that cover northern Alabama. The Stage III rainfall product is produced by the Lower Mississippi River Forecast Center (LMRFC) in support of their daily forecast operations. The intercomparisons between the local rain gauge and the radar estimates have been useful to understand the accuracy and utility of the Stage III data. Recently, the Stage III and CHARM rainfall measurements have been combined to produce an hourly rainfall dataset at each CHARM observation site. The procedure matches each CHARM site with a time sequence of Stage III radar estimates of precipitation. Hourly stage III rainfall estimates were used to partition the rain gauge values to the time interval over which they occurred. The new hourly rain gauge dataset is validated at selected points where 1-5 minute rainfall measurements have been made. This procedure greatly enhances the utility of the CHARM data for local weather and hydrologic modeling studies. The conference paper will present highlights of the Stage III intercomparison and some examples of the combined radar / rain gauge product demonstrating its accuracy and utility in deriving an hourly rainfall product from the 24 h CHARM totals.
Ground truth data collected during the experiment systems calibration and evaluation phase of the Geodynamics experimental Ocean Satellite (GEOS-3) experiment are summarized. Both National Weather Service analyses and aircraft sensor data are included. The data are structured to facilitate the use of the various data products in calibrating the GEOS-3 radar altimeter and in assessing the altimeter's sensitivity to geophysical phenomena. Brief statements are made concerning the quality and completeness of the included data.
The capabilities of the first Space Shuttle scientific payload for remote sensing observations of the earth are evaluated, and the instruments used are from the Office of Space and Terrestrial Applications (OSTA-1). The payload gathered 10 million square kilometers of data over the earth's oceans, 6 million square kilometers of data over land masses, and global atmospheric data on carbon monoxide concentration. Shuttle imaging radar collected data over a 10,000 km sweep from Spain to Australia, a Shuttle multispectral infrared radiometer obtained 400,000 ten-channel spectra in clear weather conditions over four continents, and the Ocean Color Experiment detected water color for interpretation of major water constituents. The mission is considered to be a success based on the amount of data collected, and scientific and technical insight gained for the development of Shuttle flight instruments.
A plausible scenario for the existence of a persistent back-ground of turbulence in the free atmosphere is described. The MST radar technique is the only existing technique that can be used to describe the morphology of occurrence of turbulence as a function of altitude, wind speed, shear, weather conditions, geographical location, etc. This technique was used also to assess the degree of universality of shape and amplitude of the buoyancy wave spectrum and the relation between the buoyancy wave spectrum and turbulence.
The radar altimeter is the only satellite remote sensor with a proven capability for synoptically measuring an integral property of the dynamic ocean on a near global, all weather basis. Because acquisition of global, in situ ocean data with space/time resolution adequate to describe dynamically important ocean features is practically impossible, any attempt to develop a global ocean monitoring and forecasting system will rely heavily on altimetric data for initialization and updating. Maximizing useful information from the altimeter while minimizing error sources and developing methods for assimilating altimeter data into dynamical models are, therefore, vital areas for research and development. The limits imposed on ocean prediction by errors in the geoid or apparent errors associated with ground track variations near strong geopotential gradients are examined.
This paper presents the process used by the Marshall Space Flight Center Natural Environments Branch (EV44) to quality control (QC) data from the Kennedy Space Center's 50-MHz Doppler Radar Wind Profiler for use in vehicle wind loads and steering commands. The database has been built to mitigate limitations of using the currently archived databases from weather balloons. The DRWP database contains wind measurements from approximately 2.7-18.6 km altitude at roughly five minute intervals for the August 1997 to December 2009 period of record, and the extensive QC process was designed to remove spurious data from various forms of atmospheric and non-atmospheric artifacts. The QC process is largely based on DRWP literature, but two new algorithms have been developed to remove data contaminated by convection and excessive first guess propagations from the Median Filter First Guess Algorithm. In addition to describing the automated and manual QC process in detail, this paper describes the extent of the data retained. Roughly 58% of all possible wind observations exist in the database, with approximately 100 times as many complete profile sets existing relative to the EV44 balloon databases. This increased sample of near-continuous wind profile measurements may help increase launch availability by reducing the uncertainty of wind changes during launch countdown
NASA's Earth observing Soil Moisture Active & Passive (SMAP) Mission is scheduled to launch in November 2014 into a 685 km near-polar, sun synchronous orbit. SMAP will provide comprehensive global mapping measurements of soil moisture and freeze/thaw state in order to enhance understanding of the processes that link the water, energy, and carbon cycles. The primary objectives of SMAP are to improve worldwide weather and flood forecasting, enhance climate prediction, and refine drought and agriculture monitoring during its 3 year mission. The SMAP instrument architecture incorporates an L-band radar and an L-band radiometer which share a common feed horn and parabolic mesh reflector. The instrument rotates about the nadir axis at approximately 15 rpm, thereby providing a conically scanning wide swath antenna beam that is capable of achieving global coverage within 3 days. In order to make the necessary precise surface emission measurements from space, a temperature knowledge of 60 deg C for the mesh reflector is required. In order to show compliance, a thermal vacuum test was conducted using a portable solar simulator to illuminate a non flight, but flight-like test article through the quartz window of the vacuum chamber. The molybdenum wire of the antenna mesh is too fine to accommodate thermal sensors for direct temperature measurements. Instead, the mesh temperature was inferred from resistance measurements made during the test. The test article was rotated to five separate angles between 10 deg and 90 deg via chamber breaks to simulate the maximum expected on-orbit solar loading during the mission. The resistance measurements were converted to temperature via a resistance versus temperature calibration plot that was constructed from data collected in a separate calibration test. A simple thermal model of two different representations of the mesh (plate and torus) was created to correlate the mesh temperature predictions to within 60 deg C. The on-orbit mesh temperature will be predicted using the correlated analytical thermal model since direct measurements from in-situ flight thermal sensors are not possible.
NASA's Earth Observing Soil Moisture Active and Passive (SMAP) Mission is scheduled to launch in November 2014 into a 685 kilometer near-polar, sun-synchronous orbit. SMAP will provide comprehensive global mapping measurements of soil moisture and freeze/thaw state in order to enhance understanding of the processes that link the water, energy, and carbon cycles. The primary objectives of SMAP are to improve worldwide weather and flood forecasting, enhance climate prediction, and refine drought and agriculture monitoring during its three year mission. The SMAP instrument architecture incorporates an L-band radar and an L-band radiometer which share a common feed horn and parabolic mesh reflector. The instrument rotates about the nadir axis at approximately 15 revolutions per minute, thereby providing a conically scanning wide swath antenna beam that is capable of achieving global coverage within three days. In order to make the necessary precise surface emission measurements from space, the electronics and hardware associated with the radiometer must meet tight short-term (instantaneous and orbital) and long-term (monthly and mission) thermal stabilities. Maintaining these tight thermal stabilities is quite challenging because the sensitive electronics are located on a fast spinning platform that can either be in full sunlight or total eclipse, thus exposing them to a highly transient environment. A passive design approach was first adopted early in the design cycle as a low-cost solution. With careful thermal design efforts to cocoon and protect all sensitive components, all stability requirements were met passively. Active thermal control (ATC) was later added after the instrument Preliminary Design Review (PDR) to mitigate the threat of undetected gain glitches, not for thermal-stability reasons. Gain glitches are common problems with radiometers during missions, and one simple way to avoid gain glitches is to use the in-flight set point programmability that ATC affords to operate the radiometer component away from the problematic temperature zone. A simple ThermXL model (10 nodes) was developed to exercise quick trade studies among various proposed control algorithms: Modified P control vs. PI control. The ThermXL results were then compared with the detailed Thermal Desktop (TD) model for corroboration. Once done, the simple ThermXL model was used to evaluate parameter effects such as temperature digitization, heater size and gain margin, time step, and voltage variation of power supply on the ATC performance. A Modified P control algorithm was implemented into the instrument flight electronics based on the ThermXL results. The thermal short-term stability margin decreased by 10 percent with ATC and a wide temperature error band (plus or minus 0.1 degrees Centigrade) compared to the original passive thermal design. However, a tighter temperature error band (plus or minus 0.1 degrees Centigrade) increased the thermal short-term stability margin by a factor of three over the passive thermal design. The current ATC design provides robust thermal control, tighter stability, and greater in-flight flexibility even though its implementation was prompted by non-thermal performance concerns.
Spatial and temporal variations in near-surface soil moisture are important to measure for climate studies, numerical weather forecasts, and drought monitoring. Several previous studies have shown success in using ground-reflected Global Navigation Satellite System (GNSS) signals as a form of bistatic radar to sense soil moisture. However, the ability of this type of data to sense soil moisture variations from space is still a nascent field of study. In the past two years, three satellites have been launched that were either designed to capture ground-reflected GNSS signals or have been modified to record these signals. The data provided by these satellites are giving scientists an unprecedented opportunity to investigate their ability to detect changes in Earth’s land surface, including but certainly not limited to near-surface soil moisture. This paper will present spaceborne observations of ground-reflected GNSS signals and evaluate their sensitivity to near-surface soil moisture. This sensitivity will be compared to empirical and theoretical sensitivities of monostatic L-band radar measurements to soil moisture. We will also comment on possibilities for retrieval algorithm development, using techniques employed for monostatic radar as a guide.
The close and productive collaborations between the NWS Warning and Forecast Office, the Short Term Prediction and Research Transition Center at NASA Marshall Space Flight Center and the University of Alabama in Huntsville have provided a unique opportunity for science sharing and technology transfer. One significant technology transfer that has provided immediate benefits to NWS forecast and warning operations is the use of data from the North Alabama Lightning Mapping Array. This network consists of ten VHF receivers deployed across northern Alabama and a base station located at the National Space Science and Technology Center. Preliminary investigations done at WFO Huntsville, along with other similar total lightning networks across the country, have shown distinct correlations between the time rate-of-change of total lightning and trends in intensity/severity of the parent convective cell. Since May 2003 when WFO HUN began receiving these data - in conjunction with other more traditional remotely sensed data (radar, satellite, and surface observations) -- have improved the situational awareness of the WFO staff. The use of total lightning information, either from current ground based systems or future space borne instrumentation, may substantially contribute to the NWS mission, by enhancing severe weather warning and decision-making processes. Operational use of the data has been maximized at WFO Huntsville through a process that includes forecaster training, product implementation, and post event analysis and assessments. Since receiving these data, over 50 surveys have been completed highlighting the use of total lightning information during significant events across the Tennessee Valley. In addition, around 150 specific cases of interest have been archived for collaborative post storm analysis. From these datasets, detailed trending information from radar and total lightning can be compared to corresponding damage reports. This presentation will emphasize the effective use of total lightning information in warning decision making along with best practices for implementation of new technologies into operations.
Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds.
For the past decade, the NASA Orbital Debris Program Office (ODPO) has relied on using various ground-based telescopes in Chile to acquire statistical survey data as well as photometric and spectroscopic data of orbital debris in geosynchronous Earth orbit (GEO). The statistical survey data have been used to supply the Orbital Debris Engineering Model (ORDEM) v.3.0 with debris detections in GEO to better model the environment at altitudes where radar detections are limited. The data produced for the statistical survey ranged from 30 to 40 nights per year, which only accounted for ~10% of the possible observing time. Data collection was restricted by ODPO resources and weather conditions. In order to improve the statistical sampling in GEO, as well as observe and sample other orbits, NASA's ODPO with support from the Air Force Research Laboratory (AFRL), has constructed a new observatory dedicated to orbital debris - the Meter Class Autonomous Telescope (MCAT) on Ascension Island. This location provides MCAT with the unique ability to access targets orbiting at an altitude of less than 1,000 km and low inclinations (< 20 deg). This orbital regime currently has little to no coverage by the U.S. Space Surveillance Network. Unlike previous ODPO optical assets, the ability to operate autonomously will allow rapid response observations of break-up events, an observing mode that was only available via radar tasking prior to MCAT's deployment. The primary goal of MCAT is to statistically characterize GEO via daily tasking files uploaded from ODPO. These tasking files define which operating mode to follow, providing the field center, rates, and/or targets to observe over the entire observing period. The system is also capable of tracking fast-moving targets in low Earth orbit (LEO), middle Earth orbit (MEO), as well as highly eccentric orbits like geostationary transfer orbits. On 25 August 2015, MCAT successfully acquired scientific first light, imaging the Bug Nebula and tracked objects in LEO, MEO, and GEO. NASA is working towards characterizing the system and thoroughly testing the integrated hardware and software control to achieve fully autonomous operations by late 2016. This paper will review the history and current status of the MCAT project, the details of the telescope system, and its five currently manifested operating modes.
Some operational and experimental products developed for aviation weather forecasting are briefly described. Experimental products include surface dew point, obstructions to vision, boundary layer model, computer-worded terminal forecasts, terminal alerting procedure, generalized equivalent Markov, and radar forecasts (0-2 hours).
Urbanization is one of the extreme cases of land use change. Most of world's population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in d e near future. It is estimated that by the year 2025, 60% of the world's population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause-effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. We will also present results from experiments using a regional atmospheric-land surface modeling system. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.
SPoRT (NASA's Short-term Prediction Research and Transition Center) has collaboratively worked with Alaska WFOs (Weather Forecast Offices) to introduce RGB (Red/Green/Blue false color image) imagery to prepare for NOAA-20 (National Oceanic and Atmospheric Administration, JPSS (Joint Polar Satellite System) series-20 satellite) VIIRS (Visible Infrared Imaging Radiometer Suite) and improve forecasting aviation-related hazards. Last R2O/O2R (Research-to-Operations/Operations-to-Research) steps include incorporating NOAA-20 VIIRS in RGB suite and fully transitioning client-side RGB processing to GINA (Geographic Information Network of Alaska) and Alaska Region. Alaska Region WFOs have been part of the successful R2O/O2R story to assess the use of NESDIS (National Environmental Satellite, Data, and Information Service) Snowfall Rate product in operations. SPoRT introduced passive microwave rain rate and IMERG (Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement)) (IMERG) to Alaska WFOs for use in radar-void areas and assessing flooding potential. SPoRT has been part of the multi-organization collaborative effort to introduce Gridded NUCAPS (NOAA Unique CrIS/ATMS (Crosstrack Infrared Sounder/Advanced Technology Microwave Sounder) Processing System) to the Anchorage CWSU (Center Weather Service Unit) to assess Cold Air Aloft events, [and as part of NOAA's PG (Product Generation) effort].
During the early morning hours of February 23 1998, the worst tornado outbreak ever recorded occurred over the central Florida peninsula. At least 7 confirmed tornadoes, associated with 4 supercells, developed, with 3 of the tornadoes reaching F3 intensity. Many of the tornadoes where on the ground for tens of miles, uncommon for the state of Florida. A total of 42 people were killed, with over 250 people injured. During the outbreak, National Weather Service Melbourne, in collaboration with the National Aeronautics and Space Administration and the Massachusetts Institute of Technology was collecting data from a unique lightning observing system called Lightning Imaging Sensor Data Applications Display (LISDAD, Boldi et.al., this conference). This system marries radar data collected from the KMLB WSR-88D, cloud to ground data collected from the National Lightning Detection Network, and total lightning data collected from NASKs Lightning Detection And Ranging system. This poster will display, concurrently, total lightning data (displayed in 1 minute increments), time/height storm relative velocity products from the KMLB WSR-88D, and damage information (tornado/hail/wind) from each of the supercell thunderstorms. The primary objective of this poster presentation is to observe how total lightning activity changes as the convective storm intensifies, and how the lightning activity changes with respect to mesocyclone strength (vortex stretching) and damaging weather on the ground.
The second Wind Forecast Improvement Project (WFIP2) is an 18-month field campaign in the Pacific Northwest U.S.A., whose goal is to improve the accuracy of numerical-weather-prediction forecasts in complex terrain. The WFIP2 campaign involved the deployment of a large suite of in situ and remote sensing instrumentation, including eight 915-MHz wind-profiling radars, and surface meteorological stations. The evolution and annual variability of the daytime convective planetary-boundary-layer (PBL) height is investigated using the wind-profiling radars. Three models with different horizontal grid spacing are evaluated: the Rapid Refresh, the High-Resolution Rapid Refresh, and its nested version. The results are used to assess errors in the prediction of PBL height within the experimental and control versions of the models, with the experimental versions including changes and additions to the model parametrizations developed during the field campaign, and the control version using the parametrizations present in the National Oceanic and Atmospheric Administration/National Centers for Environmental Prediction operational version of the models at the start of the project. Results show that the high-resolution models outperform the low-resolution versions, the experimental versions perform better compared with the control versions, model PBL height estimations are more accurate on cloud-free days, and model estimates of the PBL height growth rate are more accurate than model estimates of the rate of decay. Finally, using surface sensors, we assess surface meteorological variables, finding improved surface irradiance and, to a lesser extent, improved 2-m temperature in the experimental version of the model.