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27 records · Page 2

Correlation of Lightning Flash Rates with a Microburst Event

In 1986 the MIST (Microburst and Severe - Thunderstorm) field study took place over northern Alabama. It was noted that the time of day when a peak in microburst activity was observed usually took place around 2000 UTC. It was further confirmed through the examination of the various PAM (Portable Automated Mesonet) stations that this was also the time of day where temperatures would reach their peak. On the afternoon of 18 August 2002, as the temperature approached a daily high temperature of 32 C, the first radar indication of the HSV microburst-producing storm initiated at 2020 UTC.

Altino, Karen M.↗

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

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

Case, Jonathan L.↗

Influence of Satellite-Based Heterogeneous Vegetation Momentum Roughness on Mesoscale Model Dynamics During IHOP 2002

The sensitivity of mesoscale weather prediction model to a vegetation roughness initialization is investigated for the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database previously derived using a physically based procedure and MODIS imagery, and iii) a MODIS climatologic roughness database that possesses the same spatial heterogeneity as (i) but with mean land class values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations from meteorological stations within the Oklahoma mesonet and surrounding region during IHOP20O2. A sensitivity analysis on the impact the MODIS-based roughness fields is also made through a time-series intercomparison of temperature bias, probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE) the results that, for the current replacement of the standard land-cover type based roughness values with the satellite-derived fields statistically improves model performance for most of the observed variables. Further, the satellite-based roughness enhances the surface wind speed, PBL height and TKE production on the order of 3 to l0 percent, with a lesser effect over grassland and cropland domains, and the greater effect over mixed land cover domains

Jasinski, Michael↗

Statistical Analysis of Model Data for Operational Space Launch Weather Support at Kennedy Space Center and Cape Canaveral Air Force Station

The 12-km resolution North American Mesoscale (NAM) model (MesoNAM) is used by the 45th Weather Squadron (45 WS) Launch Weather Officers at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to support space launch weather operations. The 45 WS tasked the Applied Meteorology Unit to conduct an objective statistics-based analysis of MesoNAM output compared to wind tower mesonet observations and then develop a an operational tool to display the results. The National Centers for Environmental Prediction began running the current version of the MesoNAM in mid-August 2006. The period of record for the dataset was 1 September 2006 - 31 January 2010. The AMU evaluated MesoNAM hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The MesoNAM forecast winds, temperature and dew point were compared to the observed values of these parameters from the sensors in the KSC/CCAFS wind tower network. The data sets were stratified by model initialization time, month and onshore/offshore flow for each wind tower. Statistics computed included bias (mean difference), standard deviation of the bias, root mean square error (RMSE) and a hypothesis test for bias = O. Twelve wind towers located in close proximity to key launch complexes were used for the statistical analysis with the sensors on the towers positioned at varying heights to include 6 ft, 30 ft, 54 ft, 60 ft, 90 ft, 162 ft, 204 ft and 230 ft depending on the launch vehicle and associated weather launch commit criteria being evaluated. These twelve wind towers support activities for the Space Shuttle (launch and landing), Delta IV, Atlas V and Falcon 9 launch vehicles. For all twelve towers, the results indicate a diurnal signal in the bias of temperature (T) and weaker but discernable diurnal signal in the bias of dewpoint temperature (T(sub d)) in the MesoNAM forecasts. Also, the standard deviation of the bias and RMSE of T, T(sub d), wind speed and wind direction indicated the model error increased with the forecast period all four parameters. The hypothesis testing uses statistics to determine the probability that a given hypothesis is true. The goal of using the hypothesis test was to determine if the model bias of any of the parameters assessed throughout the model forecast period was statistically zero. For th is dataset, if this test produced a value >= -1 .96 or <= 1.96 for a data point, then the bias at that point was effectively zero and the model forecast for that point was considered to have no error. A graphical user interface (GUI) was developed so the 45 WS would have an operational tool at their disposal that would be easy to navigate among the multiple stratifications of information to include tower locations, month, model initialization times, sensor heights and onshore/offshore flow. The AMU developed the GUI using HyperText Markup Language (HTML) so the tool could be used in most popular web browsers with computers running different operating systems such as Microsoft Windows and Linux.

Bauman, William H., III↗

Investigation of the 2006 Drought and 2007 Flood Extremes at the Southern Great Plains Through an Integrative Analysis of Observations

Hydrological years 2006 (HY06, 10/2005-09/2006) and 2007 (HY07, 10/2006-09/2007) provide a unique opportunity to examine hydrological extremes in the central US because there are no other examples of two such highly contrasting precipitation extremes occurring in consecutive years at the Southern Great Plains (SGP) in recorded history. The HY06 annual precipitation in the state of Oklahoma, as observed by the Oklahoma Mesonet, is around 61% of the normal (92.84 cm, based on the 1921-2008 climatology), which results in HY06 the second-driest year in the record. In particular, the total precipitation during the winter of 2005-06 is only 27% of the normal, and this winter ranks as the driest season. On the other hand, the HY07 annual precipitation amount is 121% of the normal and HY07 ranks as the seventh-wettest year for the entire state and the wettest year for the central region of the state. Summer 2007 is the second-wettest season for the state. Large-scale dynamics play a key role in these extreme events. During the extreme dry period (10/2005-02/2006), a dipole pattern in the 500-hPa GH anomaly existed where an anomalous high was over the southwestern U.S. region and an anomalous low was over the Great Lakes. This pattern is associated with inhibited moisture transport from the Gulf of Mexico and strong sinking motion over the SGP, both contributing to the extreme dryness. The precipitation deficit over the SGP during the extreme dry period is clearly linked to significantly suppressed cyclonic activity over the southwestern U.S., which shows robust relationship with the Western Pacific (WP) teleconnection pattern. The precipitation events during the extreme wet period (May-July 2007) were initially generated by active synoptic weather patterns, linked with moisture transport from the Gulf of Mexico by the northward low level jet, and enhanced by the mesoscale convective systems. Although the drought and pluvial conditions are dominated by large-scale dynamic patterns, we have demonstrated that the two positive feedback processes during the extreme dry and wet periods found in this study play a key role to maintain and reinforce the length and severity of existing drought and flood events. For example, during the extreme dry period, with less clouds, LWP, PWV, precipitation, and thinner Cu cloud thickness, more net radiation was absorbed and used to evaporate water from the ground. The evaporated moisture, however, was removed by low-level divergence. Thus, with less precipitation and removed atmospheric moisture, more absorbed incoming solar radiation was used to increase surface temperature and to make the ground drier.

Dong, Xiquan↗

Applied Meteorology Unit (AMU) Quarterly Report First Quarter FY-04

This report summarizes the Applied Meteorology Unit (AMU) activities for the First Quarter of Fiscal Year 2004 (October - December 2003). Tasks reviewed are: (1) Objective Lightning Probability Forecast, (2) Mesonet Temperature and Wind Climatology, (3) Severe Weather Forecast Decision Aid and (4) Anvil Transparency Relationship to Radar Reflectivity

Bauman, William↗

Ohio River Basin Water Resources: Monitoring Flash Drought Potential and Quantifying the Hydrologic Impacts in the Ohio River Basin

Flash drought conditions emerge in a matter of weeks following persistent weather anomalies, such as high temperatures or large vapor pressure deficits, that drive increased evaporative demand. Vegetation response rapidly depletes soil moisture, threatening surface water supplies, triggering significant crop loss, and increasing wildfire risk. Drought indices sensitive to flash drought are currently not included in drought forecast models in the Ohio River Basin (ORB). The team assessed and compared drought indices, gauge-based data, and satellite measurements over the course of the September 2019 flash drought event in the Ohio River Basin to investigate environmental fingerprints throughout flash drought evolution. Potential leading flash drought indicators were compared to the Standardized Precipitation Index (SPI) to aid the National Weather Service (NWS) Ohio River Forecast Center and Kentucky Climate Center in producing early warning flash drought forecasts. These drought indices included Evaporative Demand Drought Index (EDDI), Standardized Precipitation Evapotranspiration Index (SPEI), and Landscape Evaporative Response Index (LERI) (derived from Terra Moderate Resolution Imaging Spectroradiometer (MODIS)). Drought index behavior inherently varies based on parameters incorporated - EDDI measures evaporative demand through potential evapotranspiration, and demonstrates more variations due to sensitivity to seasonal changes in evaporative demand throughout the 2010-2019 study period. Conversely, LERI measures evaporative response through actual evapotranspiration, representing different environmental changes. Soil moisture response was evaluated using Soil Moisture Active Passive (SMAP) L-band radiometer data and Kentucky Mesonet gauge-based measurements. This analysis enables climatologists and weather forecasters to keep decision-makers and stakeholders better informed about drought risks, and to implement the appropriate actions for preparation of drought onset.

Adelaide Schmid↗

Ohio River Basin Water Resources: Monitoring Flash Drought Potential and Quantifying the Hydrologic Impacts in the Ohio River Basin Utilizing NASA Earth Observations

Flash drought conditions emerge in a matter of weeks following persistent weather anomalies, such as high temperatures or large vapor pressure deficits, that drive increased evaporative demand. Vegetation response rapidly depletes soil moisture, threatening surface water supplies, triggering significant crop loss, and increasing wildfire risk. Drought indices sensitive to flash drought are currently not included in drought forecast models in the Ohio River Basin (ORB). The team assessed and compared drought indices, gauge-based data, and satellite measurements over the course of the September 2019 flash drought event in the Ohio River Basin to investigate environmental fingerprints throughout flash drought evolution. Potential leading flash drought indicators were compared to the Standardized Precipitation Index (SPI) to aid the National Weather Service (NWS) Ohio River Forecast Center and Kentucky Climate Center in producing early warning flash drought forecasts. These drought indices included Evaporative Demand Drought Index (EDDI), Standardized Precipitation Evapotranspiration Index (SPEI), and Landscape Evaporative Response Index (LERI) (derived from Terra Moderate Resolution Imaging Spectroradiometer (MODIS)). Drought index behavior inherently varies based on parameters incorporated -EDDI measures evaporative demand through potential evapotranspiration, and and demonstrates more variations due to sensitivity to seasonal changes in evaporative demand throughout the 2010-2019 study period. Conversely, LERI measures evaporative response through actual evapotranspiration, representing different environmental changes. Soil moisture response was evaluated using Soil Moisture Active Passive (SMAP) L-band radiometer data and Kentucky Mesonet gauge-based measurements. This analysis enables climatologists and weather forecasters to keep decision-makers and stakeholders better informed about drought risks to implement the appropriate actions for preparation of drought onset.

DEVELOP Project Summary↗

Modeling the Worst-Case-Scenario of Soil Drydown for Agricultural Drought Monitoring in Kansas Using NASA Earth Observations and In-situ Parameters

Climatologists in Kansas have observed rapid shifts from wet to dry conditions and rapid intensification of drought conditions for the state in recent years. As a leading state in agricultural production, drought events can lead to decreased crop yields and impact the state’s economy. The exponential decay of soil moisture content is a major consequence of drought and can exacerbate these impacts on agricultural production. This study examined the rate of soil moisture drydown in Kansas to understand and monitor the worst-case-scenario of short-term soil water shortage. Soil Moisture Active Passive (SMAP) L-band Radiometer rootzone soil moisture imagery from March 2015 to June 2019 was used to estimate the minimum and maximum soil moisture capacity throughout the state. In situ soil moisture parameters, such as the exponential decay constant, were approximated from the Kansas Mesonet system. These variables were inputs into an exponential decay model that forecasted gridded rootzone soil moisture in a scenario that assumed no precipitation for a user-identified period of time. The forecasts were output on the order of weeks to capture the rapid shifts in soil moisture content. Another model was used to identify areas in Kansas currently below a given percentage of the relative soil moisture saturation, measured as a function of minimum, maximum, and current soil moisture. This model forecasted the number of days until each cell in the soil moisture grid reached the input percentage of relative soil moisture saturation. The gridded model outputs and workflow were developed in partnership with the Kansas Water Office and Kansas Office of the State Climatologist at Kansas State University, as a part of their drought monitoring efforts.

NASA DEVELOP↗