Cooperative Institute for Research in the Atmosphere

About: Cooperative Institute for Research in the Atmosphere is a based out in . It is known for research contribution in the topics: Snow & Data assimilation. The organization has 332 authors who have published 997 publications receiving 38835 citations. The organization is also known as: CIRA.

Forecasting Tropical Cyclone Eye Formation and Dissipation in Infrared Imagery

Abstract: The development of an infrared (IR; specifically near 11 μm) eye probability forecast scheme for tropical cyclones is described. The scheme was developed from an eye detection algorithm that used a linear discriminant analysis technique to determine the probability of an eye existing in any given IR image given information about the storm center, motion, and latitude. Logistic regression is used for the model development and predictors were selected from routine information about the current storm (e.g., current intensity), forecast environmental factors (e.g., wind shear, oceanic heat content), and patterns/information (e.g., convective organization, tropical cyclone size) extracted from the current IR image. Forecasts were created for 6-, 12-, 18-, 24-, and 36-h forecast leads. Forecasts were developed using eye existence probabilities from North Atlantic tropical cyclone cases (1996–2014) and a combined North Atlantic and North Pacific (i.e., Northern Hemisphere) sample. The performance of Nort...

Idealized Mesoscale Convective System Structure and Propagation Using Convective Parameterization

Abstract: The development and propagation of mesoscale convective systems (MCSs) was examined within the Weather Research and Forecasting (WRF) model using the Kain–Fritsch (KF) cumulus parameterization scheme and a modified version of this scheme. Mechanisms that led to propagation in the parameterized MCS are evaluated and compared between the versions of the KF scheme. Sensitivity to the convective time step is identified and explored for its role in scheme behavior. The sensitivity of parameterized convection propagation to microphysical feedback and to the shape and magnitude of the convective heating profile is also explored. Each version of the KF scheme has a favored calling frequency that alters the scheme’s initiation frequency despite using the same convective trigger function. The authors propose that this behavior results in part from interaction with computational damping in WRF. A propagating convective system develops in simulations with both versions, but the typical flow structures are di...

Weather SDM: estimating snow density with high precision using snow depth and local climate

Abstract: Snow density is an important measure in hydrology used to convert snow depth to the snow water equivalent (SWE). A model developed by Sturm, Tara and Liston predicts the snow density by using snow depth, the snow age and a snow class defined by the location. In this work this model is extended to include location and seasonal weather-specific variables. The model is named Weather Snow Density Model (Weather SDM). A Bayesian framework is chosen, and the model is fitted to and tested for 4,040 Norwegian snow depth and densities measurements between 1998 and 2011. The final model improved the snow density predictions for the Norwegian data compared to the model of Sturm by up to 50%. Further, the Weather SDM is extended to utilize local year-specific snow density observations (Weather&ObsDensity SDM). This reduced the prediction error an additional 16%, indicating a significant improvement when utilizing information provided by annual snow density measurements.

The Role of Gravity Waves in Slowly Varying in Time Mesoscale Motions

Abstract: Pressure oscillations with amplitudes of the deviations from the horizontal mean and periods considerably less than those for the large-scale case have been observed in a number of summer and winter storms. However, there is conflicting evidence about the role of these waves in mesoscale storms. In the case of mesoscale heating that is a prescribed function of the independent variables, it has been proven that the dominant component of the corresponding slowly varying in time solution is accurately described by a simple dynamical (reduced) system in which gravity waves play no role. This paper proves that large spatial-scale gravity waves with amplitudes and periods of the pressure perturbations the same as the reduced system component of the solution can be generated by mesoscale storms. Because the amplitudes and the periods of the pressure perturbations for the two components of the solution are similar, it is difficult to distinguish between them using temporal plots of the pressure at a sing...

Variational assimilation of radar reflectivities in a cirrus model. I: Model description and adjoint sensitivity studies

Abstract: This paper presents an ice microphysics model to be used in variational assimilation of cloud-radar data. The model predicts the vertical and temporal evolution of the parameters of a modified gamma size distribution describing an ice-cloud crystal population, given an initial atmospheric state. Microphysical variables are mapped onto radar reflectivities using an explicit radar forward model. Evolution equations take into account microphysical processes relevant to ice-crystal growth, such as vapour-diffusion growth, aggregation, and gravitational sedimentation. The thermodynamic and dynamic state is specified from a numerical forecast or a radiosonde sounding and is assumed constant over the model integration time. Due to this assumption, the model provides no feedback to the environmental state and thus cannot be used for long-term cloud forecasts. However, when the model is integrated over a short time interval, and the atmospheric conditions are close to water saturation at cloud levels, the model is shown to compare well with observations. An adjoint of a linearized version of the cloud model is derived and applied to investigate model sensitivities to input variables and model parameters. Results show a large sensitivity of model outputs to temperature and selected parameters related to the crystal fall-velocity parametrization. Copyright © 2003 Royal Meteorological Society