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.

Analysis of Information Content of Infrared Sounding Radiances in Cloudy Conditions

Abstract: Information content analysis of the Geostationary Operational Environmental Satellite (GOES) sounder observations in the infrared was conducted for use in satellite data assimilation. Information content is defined as a first-order response of the top-of-atmosphere brightness temperature to perturbations of simulated temperature and humidity profiles, obtained from a cloud-resolving model, both in the presence and absence of clouds. Sensitivity to the perturbations was numerically evaluated using an observational operator for visible and infrared radiative transfer developed within a research satellite data assimilation system. The vertical distribution of the sensitivities was analyzed as a function of cloud optical thickness covering the range from a cloud-free scene to an optically thick cloud. The clear-sky sensitivities to temperature and humidity perturbations for each channel are representative of the corresponding channel weighting functions for a clear-sky case. For optically thin–modera...

On the Origin of Rotation Derived from Super Rapid Scan Satellite Imagery at the Cloud Tops of Severe Deep Convection

Abstract: Severe thunderstorms routinely exhibit adjacent maxima and minima in cloud-top vertical vorticity (CTV) downstream of overshooting tops within flow fields retrieved using sequences of fine-temporal-resolution (1-min) Geostationary Operational Environmental Satellite (GOES)-R series imagery. Little is known about the origin of this socalled CTV couplet signature, and whether the signature is the result of flow-field derivational artifacts. Thus, the CTV signature’s relevance to research and operations is currently ambiguous. Within this study, we explore the origin of nearcloud-top rotation using an idealized supercell numerical model simulation. Employing an advanced dense optical flow algorithm, image stereoscopy, and numerical model background wind approximations, the artifacts commonwith cloud-top flow-field derivation are removed from two supercell case studies sampled by GOES-R imagers. It is demonstrated that the CTV couplet originates from tilted and converged horizontal vorticity that is baroclinically generated in the upper levels (above 10 km) immediately downstream of the overshooting top. This baroclinic generationwould not be possible without a strong and sustained updraft, implying an indirect relationship to rotationally maintained supercells. Furthermore, it is demonstrated that CTV couplets derived with optical flow algorithms originate from actual rotation within the storm anvils in the case studies explored here, though supercells with opaque above-anvil cirrus plumes and strong anvil-level negative vertical wind shear may produce rotation signals as an artifact without quality control. Artifact identification and quality control is discussed further here for future research and operations use.

Use of the advanced microwave sounding unit data to improve typhoon prediction

Abstract: The effects of incorporating the advanced microwave sounding unit (AMSU-A) data with a modified Zhu–Zhang–Weng vortex-bogussing algorithm on typhoon prediction are examined through the use of the PSU/NCAR Mesoscale Model version 5 (MM5). The AMSU-A data contain the vertical distribution of the retrieved temperature from satellite brightness temperature, with the geopotential height and wind fields derived through a series of statistical and diagnostic calculations. The advantages of the modified vortex-bogussing algorithm include the incorporation of realistic asymmetric typhoon structures, the balanced dynamics with the background field, the easiness to implement and the efficient computations. To test the efficiency of this vortex-bogussing algorithm, the Typhoon Dan event in 1999 is simulated by incorporating the derived AMSU-A fields into the initial conditions of the MM5 modeling system. Results show significant improvements in the track and intensity of the storm, as compared to the simulation without the AMSU-A data. Therefore, this modified vortex-bogussing algorithm can be easily implemented on any typhoon modeling system, which will improve the real-time forecast of tropical cyclones.

Combined Dust Detection Algorithm for Asian Dust Events Over East Asia Using GK2A/AMI: a Case Study in October 2019

Abstract: A combined algorithm comprising multiple dust detection methods was developed using infrared (IR) channels onboard the GEOstationary Korea Multi-Purpose SATellite 2A equipped with the Advanced Meteorological Imager (GK2A/AMI) Six cloud tests using brightness temperature difference (BTD) were utilized to reduce errors caused by clouds For detecting dust storms, three standard BTD tests (ie, $${BT}_{123}-{BT}_{105}$$ , $${BT}_{87}-{BT}_{105}$$ , and $${BT}_{112}-{BT}_{105}$$ ) were combined with the polarized optical depth index (PODI) The combined algorithm normalizes the indices for cloud and dust detection, and adopts weighted combinations of dust tests depending on the observation time (day/night) and surface type (land/sea) The dust detection results were produced as quantitative confidence factors and displayed as false color imagery, applying a dynamic enhancement background reduction algorithm (DEBRA) The combined dust detection algorithm was qualitatively assessed by comparing it with dust RGB imageries and ground-based lidar data The combined algorithm especially improved the discontinuity in weak dust advection to the sea and considerably reduced false alarms as compared to previous dust monitoring methods For quantitative validation, we used aerosol optical thickness (AOT) and fine mode fraction (FMF) derived from low Earth orbit (LEO) satellites in daytime For both severe and weakened dust cases, the probability of detection (POD) ranged from 0667 to 0850 and it indicated that the combined algorithm detects more potential dust pixels than other satellites In particular, the combined algorithm was advantageous in detecting weak dust storms passing over the warm and humid Yellow Sea with low dust height and small AOT