2017 CIRA Seminars
The Geolocated Information Processing System (GeoIPS) is a Python-based system for processing any data with latitudes and longitudes. It is composed of multiple high-level objects that define standard internal formats for data, description of domains, and construction of imagery and data product recipes. In addition to static sectors, dynamic sectors for following events such as tropical cyclones can be deployed. GeoIPS is currently capable of processing satellite data from a large number of meteorological satellites as well as some Navy models and is easily extendable to accept other da
Deep-layer (200−850 hPa) vertical wind shear is generally an inhibiting factor for tropical cyclone intensification. This negative relationship stems from a number of processes, including: vertical misalignment of the vortex, increased stability, ventilation of the upper-tropospheric warm core, and dry air entrainment. Despite these processes, many tropical cyclones can intensify under moderate vertical wind shear—the range of shear magnitudes that are neither too weak nor too strong (5–10 m s−1).
Storm tracks are regions where extratropical cyclones occur most frequently, they control weather and climate in the extratropics. Storm tracks shift latitudinally in response to energetic perturbations across a range of timescales. On seasonal timescales, the Northern Hemisphere storm track shifts poleward between winter and summer and equatorward between summer and winter. On interannual timescales, the storm tracks shift equatorward in response to El Nino minus La Nina conditions.
Methods to determine the physical properties of aerosol particles is important in a vast array of scientific and applied contexts. Due in part to the difficulty of collecting such particles, a variety of contact-free techniques have been developed that infer information about the particles in an indirect manner. A popular example is elastic light-scattering where the angular pattern of light scattered from a particle is analyzed to estimate particle properties like shape and size.
Geophysical systems can be characterised as complex, nonlinear and high dimensional. All of these provide major challenges to understanding and modelling. To explore observations and existing knowledge encoded in numerical models to their full extent one can try to combine both sources of information. A systematic tool for doing this is data assimilation. It can be used to provide a description of the full nonlinear evolution of the system including its uncertainty using all information we have.
There is considerable research and management interest in whether and how native faunas are responding to climate change. Evaluating whether empirical data support range-shift hypotheses is complicated by variation in climate, differences in response variables and the extent and resolution of analyses, and mismatches between the resolutions at which climate data typically are available and species respond to environmental heterogeneity.
Lidar remote sensing enables observations of various atmospheric properties and dynamics from the troposphere to the region of the atmosphere considered the edge of space near ~80-100 km. For some aspects of the atmosphere, studying coupling between different altitudes and regions is important for a more in depth understanding. Gravity waves are one aspect integral to understanding atmospheric coupling, as they strongly influence dynamics within the atmosphere via the transport of energy and momentum from the lower atmosphere to the middle and upper atmosphere.
Spatial variations in the solar heating of the climate system drive the atmospheric and oceanic circulation and set patterns of temperature and precipitation. This presentation explores the processes that determine the absorption of solar radiation in the climate system including latitudinal, vertical and seasonal distributions.
Currently, the scientific community is unable to identify how characteristics of clouds will alter as the climate warms in response to emissions of greenhouse gases from human activities, and to what extent changes in cloud characteristics will feed back on surface temperature responses. In particular, models disagree substantially in the magnitude of cloud feedback for the regimes of subtropical marine boundary-layer clouds.
Global warming simulations robustly show that mean precipitation increases at 1-3% per Kelvin, but we do not know what sets these values. Mean precipitation is constrained by radiative cooling, however, and we demonstrate here that radiative cooling profiles exhibit a certain invariance under warming when plotted in temperature coordinates. This invariance can then be leveraged to derive simple analytical equations for precipitation change with warming.
University of Wyoming King Air (UWKA) is a part of NSF-supported Lower Atmosphere Observing Facilities (LAOF). Through multi-year development efforts, UWKA has equipped with integrated observation capabilities for cloud dynamics and microphysics, aerosols, and environment conditions through combining lidar, radar, radiometer and in situ measurements. Approaches were developed to retrieve droplet and ice concentrations in stratiform clouds from combined lidar-radar measurements.
The weather forecasting process has grown more complex in recent years with the growing amount of observational data and model output available to weather forecasters and the trend toward providing more impact-based decision support services. In order to assist forecasters and end-users with the task of managing the firehose of data, I have developed and evaluated machine learning forecast guidance systems for different high-impact weather phenomena.
The extensive cloudiness and resulting high albedo of the Southern Oceans (SO) are predominantly due to the occurrence of widespread marine boundary layer (MBL) clouds. Recent work finds correlations between biogenically enhanced cloud condensation nuclei concentrations and cloud droplet number concentrations derived from passive satellite data.
A key project within the National Oceanic and Atmospheric Administration (NOAA) Global Observing Systems Analysis (GOSA) group is the Sensing Hazards with Operational Unmanned Technology (SHOUT) project. One of the main objectives of SHOUT is to conduct both Observing System Experiments (OSEs) and Observing System Simulation Experiments (OSSEs) to evaluate the impact of real and simulated Unmanned Aircraft Systems (UAS) data on weather forecasts of tropical cyclones and high-impact weather events over the United States.
Pressure perturbations are regions of anomalously low or high pressure in deep convection and play key roles in modulating the magnitude and distribution of vertical velocities within cumulus clouds. A cloud’s vertical momentum budget is primarily regulated by two pressure forces: Effective buoyancy pressure acceleration (EBPA), and dynamic pressure acceleration (DPA).