Andrew Molthan

Comparisons of Single- and Double-Moment Microphysics Schemes in the Simulation of a Synoptic-Scale Snowfall Event

AbstractThe Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) provided aircraft, surface, and remotely sensed observations of cloud and precipitation characteristics to support improved simulation of cold-season precipitation within weather forecast models and new developments in satellite and radar precipitation retrievals. On 22 January 2007, the C3VP campaign executed an intensive observation period to sample widespread snowfall that occurred as a midlatitude cyclone tracked along the U.S.–Canadian border. Surface air temperature and precipitation measurements, combined with aircraft measurement of hydrometeor content and size distribution, are used to examine various assumptions and parameterizations included within four bulk water microphysics schemes available within the Weather Research and Forecasting Model (WRF).In a simulation of the 22 January 2007 event, WRF forecasts reproduced the overall precipitation pattern observed du...

Evaluating the Snow Crystal Size Distribution and Density Assumptions within a Single-Moment Microphysics Scheme

ValidationProject(C3VP)wasafieldcampaigndesignedtoobtainaircraft,surface,andradarobservationsof clouds and precipitation in support of improving the simulation of snowfall and cold season precipitation, their microphysical processes represented within forecast models, and radiative properties relevant to remotely sensed retrievals. During the campaign, a midlatitude cyclone tracked along the U.S.‐Canadian border on 22 January 2007, producing an extensive area of snowfall. Observations of ice crystals from this event are used to evaluate the assumptions and physical relationships for the snow category within the Goddard six-class, single-moment microphysics scheme, as implemented within the Weather Research and Forecasting (WRF) model. The WRF model forecast generally reproduced the precipitation and cloud structures sampled by radars and aircraft, permitting a comparison between C3VP observations and model snowfall characteristics. Key snowfall assumptions in the Goddard scheme are an exponential size distribution with fixed intercept and effective bulk density, and the relationship between crystal diameter and terminal velocity. Fixed values for the size distribution intercept and density did not represent the vertical variability of naturally occurring populations of aggregates, and the current diameter and fall speed relationship underestimated terminal velocities for all sizes of crystals.

Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas

Natural and anthropogenic hazards are frequently responsible for disaster events, leading to damaged physical infrastructure, which can result in loss of electrical power for affected locations. Remotely-sensed, nighttime satellite imagery from the Suomi National Polar-orbiting Partnership (Suomi-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) can monitor power outages in disaster-affected areas through the identification of missing city lights. When combined with locally-relevant geospatial information, these observations can be used to estimate power outages, defined as geographic locations requiring manual intervention to restore power. In this study, we produced a power outage product based on Suomi-NPP VIIRS DNB observations to estimate power outages following Hurricane Sandy in 2012. This product, combined with known power outage data and ambient population estimates, was then used to predict power outages in a layered, feedforward neural network model. We believe this is the first attempt to synergistically combine such data sources to quantitatively estimate power outages. The VIIRS DNB power outage product was able to identify initial loss of light following Hurricane Sandy, as well as the gradual restoration of electrical power. The neural network model predicted power outages with reasonable spatial accuracy, achieving Pearson coefficients (r) between 0.48 and 0.58 across all folds. Our results show promise for producing a continental United States (CONUS)- or global-scale power outage monitoring network using satellite imagery and locally-relevant geospatial data.

Incorporating Ice Crystal Scattering Databases in the Simulation of Millimeter-Wavelength Radar Reflectivity

Abstract The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) was designed to acquire aircraft, surface, and satellite observations of particle size distributions during cold season precipitation events for the purposes of validating and improving upon satellite-based retrievals of precipitation and the representation of cloud and precipitation processes within numerical weather prediction schemes. During an intensive observation period on 22 January 2007, an instrumented aircraft measured ice crystal size distributions, ice and liquid water contents, and atmospheric state parameters within a broad shield of precipitation generated by a passing midlatitude cyclone. The 94-GHz CloudSat radar acquired vertical profiles of radar reflectivity within light to moderate snowfall, coincident with C3VP surface and aircraft instrumentation. Satellite-based retrievals of cold season precipitation require relationships between remotely sensed qua...

Clouds in the Cloud: Weather Forecasts and Applications within Cloud Computing Environments

AbstractCloud computing offers new opportunities to the scientific community through cloud-deployed software, data-sharing and collaboration tools, and the use of cloud-based computing infrastructure to support data processing and model simulations. This article provides a review of cloud terminology of possible interest to the meteorological community, and focuses specifically on the use of infrastructure as a service (IaaS) concepts to provide a platform for regional numerical weather prediction. Special emphasis is given to developing countries that may have limited access to traditional supercomputing facilities. Amazon Elastic Compute Cloud (EC2) resources were used in an IaaS capacity to provide regional weather simulations with costs ranging from

Satellite Observations Monitor Outages From Superstorm Sandy

40 to

NASA satellite data assist in tornado damage assessments

75 per 48-h forecast, depending upon the configuration. Simulations provided a reasonable depiction of sensible weather elements and precipitation when compared against typical validation data available over Central America and the Caribbean.

Structure and Evolution of a Warm Frontal Precipitation Band during the GPM Cold Season Precipitation Experiment (GCPEx)

In late October 2012, Hurricane Sandy traveled across Jamaica, Cuba, and the Bahamas, then progressed northward along the eastern seaboard of the United States, resulting in numerous tropical storm warnings along the coasts of Florida and North Carolina. As the storm approached the Mid-Atlantic region, interaction with an upper-level low drew the cyclone inland, with the center passing just north of Atlantic City, N. J. In what media reports dubbed a “superstorm,” Sandy produced hurricane-force winds, significant coastal storm surge, torrential rain, inland flooding, and extensive damage over a vast area. Further west of the cyclone center, strong winds increased wave activity throughout the Great Lakes, and heavy snowfall occurred across portions of Tennessee, Kentucky, and West Virginia. As of early November, more than 100 fatalities had been attributed to Sandy in the northeastern United States, with total economic losses of up to

Evaluation of Cloud Microphysical Schemes for a Warm Frontal Snowband during the GPM Cold Season Precipitation Experiment (GCPEx)

50 billion [New York Times, 2012, and Walsh and Schwartz, 2012].

Transforming Satellite Data into Weather Forecasts

During the period of 25–28 April 2011, the southeastern United States was raked by several episodes of severe weather. Numerous tornadoes caused extensive damage and, tragically, the deaths of more than 300 people. Meteorologists from the National Oceanic and Atmospheric Administrations (NOAA) National Weather Service (NWS) performed extensive surveys to assess the intensity, duration, and ground track of tornadoes reported during the event. Survey activities included visits to the affected locations, analysis of radar data, aerial surveys, and interviews with eyewitnesses.