Investigation of features of May, 2001 tropical cyclone over the Arabian Sea through IRS-P4 and other satellite data

In this paper, utility of satellite derived atmospheric motion vectors and geophysical parameters is brought out to discern appropriate signals for improving short-range forecasts in respect of development/dissipation of tropical cyclones over the Indian region. Results of a particular case study of May, 2001 cyclone, which formed in the Arabian Sea are reported. Analysis of wind field with input of modified cloud motion vectors and water vapour wind vectors is performed utilizing Optimum Interpolation (OI) technique at 850 and 200 hPa for finding dynamical changes such as vorticity, convergence and divergence for the complete life period of this cyclone. Simultaneously, variations in geophysical parameters obtained from IRS-P4 and TRMM satellites in ascending and descending nodes are compared with dynamical variations for discerning some positive signals to improve short range forecasts over the Indian region. The enhancement of cyclonic vorticity at 200 hPa over larger area surrounding center of cyclone was observed from 26 to 28 May 2001 which gave a positive signal for dissipation of storm.

Climate data record of atmospheric motion vectors at EUMETSAT for usage in reanalysis

<p>This presentation provides an overview of the different upper-air wind data records available at EUMETSAT for usage in global and regional reanalysis. The assimilation of Atmospheric Motion Vectors (AMV) is recognised to be important to reduce the forecast errors in NWP model runs. In support of the Copernicus Climate Change Service (C3S), EUMETSAT produced several AMV Climate Data Records (CDR) from geostationary and low-earth orbit satellites for assimilation into ECMWF’s next global reanalysis ERA6.</p><p>Since the launch of its first generation of geostationary satellites, EUMETSAT has developed its own unique algorithms to derive atmospheric motion vectors (AMVs). These algorithms are used to provide real time AMVs using images acquired from instruments on-board both polar and geostationary satellites. These AMVs are routinely assimilated into weather forecast models. EUMETSAT archived all image data from its instruments (MVIRI and SEVIRI) in geostationary orbit and the global record of Advanced Very High Resolution Radiometer (AVHRR) data back to the late 1970s providing a suitable data source for climate research allowing the production of consistent AMV CDRs over the entire period.</p><p>Two long AMV data records are available now from the geostationary sensors on Meteosat-2 to Meteosat-10 covering 1981-2017 over Africa and Europe and from AVHRR Global Area Coverage (GAC) data from 16 AVHRR instruments starting with the TIROS-N satellite and covering polar AMVs over the Northern and Southern hemisphere from 1978-2019. In addition, full resolution AVHRR images (Local Area Coverage (LAC)) from the AVHRR aboard the polar orbiting Metop-A and -B satellites were used to generate a CDR containing polar AMVs from single satellite retrievals and global AMVs from the combined Metop-A/B dual satellite retrieval starting in 2007 and 2013, respectively.</p><p>For all data records, the EUMETSAT AMV algorithm adapted for climate purposes was used and extensive validation of the data records were performed. It shows that the CDR are homogeneous and very stable over the period. They are suitable for usage in model reanalysis and climate analysis. The CDR are in agreement with ground based radiosonde and model data. For the polar AMVs, a remarkable agreement with MODIS AMVs has been found.</p><p>To better serve closer to real time needs for reanalysis, EUMETSAT is experimenting with the continuous production of an Interim Climate Data Record (ICDR) with a timeliness close to real-time. With a still not completely operational low-cost approach, a timeliness of 83% within 18 hours at similar quality was achieved.</p><p>In addition to the existing data records the presentation provides the plan for future improvements and new CDR releases for AMV data records in the coming years. In particular, the use of better information on multi-layer cloud objects in AMV retrievals is a central part for the improvements of the AMVs from geostationary orbit.  </p>

The Sentinel-3 SLSTR Atmospheric Motion Vectors Product at EUMETSAT

Atmospheric Motion Vectors (AMVs) are an important input to many Numerical Weather Prediction (NWP) models. EUMETSAT derives AMVs from several of its orbiting satellites, including the geostationary satellites (Meteosat), and its Low-Earth Orbit (LEO) satellites. The algorithm extracting the AMVs uses pairs or triplets of images, and tracks the motion of clouds or water vapour features from one image to another. Currently, EUMETSAT LEO satellite AMVs are retrieved from georeferenced images from the Advanced Very-High-Resolution Radiometer (AVHRR) on board the Metop satellites. EUMETSAT is currently preparing the operational release of an AMV product from the Sea and Land Surface Temperature Radiometer (SLSTR) on board the Sentinel-3 satellites. The main innovation in the processing, compared with AVHRR AMVs, lies in the co-registration of pairs of images: the images are first projected on an equal-area grid, before applying the AMV extraction algorithm. This approach has multiple advantages. First, individual pixels represent areas of equal sizes, which is crucial to ensure that the tracking is consistent throughout the processed image, and from one image to another. Second, this allows features that would otherwise leave the frame of the reference image to be tracked, thereby allowing more AMVs to be derived. Third, the same framework could be used for every LEO satellite, allowing an overall consistency of EUMETSAT AMV products. In this work, we present the results of this method for SLSTR by comparing the AMVs to the forecast model. We validate our results against AMVs currently derived from AVHRR and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI). The release of the operational SLSTR AMV product is expected in 2022.

Observations of Atypical Rapid Intensification Characteristics in Hurricane Dorian (2019)

Multiple observation and analysis datasets are used to demonstrate two key features of the Atypical Rapid Intensification (ARI) process that occurred in Atlantic Hurricane Dorian (2019): 1) precession and nutations of the vortex tilt and 2) blocking of the impinging upper-level environmental flow by the outflow. As Dorian came under the influence of an upper-level anticyclone, traditional methods of estimating vertical wind shear all indicated relatively low values were acting on the storm; however, high-spatiotemporal-resolution atmospheric motion vectors (AMVs) indicated that the environmental flow at upper levels was actually impinging on the vortex core, resulting in a vertical tilt. We employ a novel ensemble of centers of individual swaths of dual-Doppler radar data from WP-3D aircraft to characterize the precession and wobble of the vortex tilt. This tilting and wobbling preceded a sequence of outflow surges that acted to repel the impinging environmental flow, thereby reducing the shear and permitting ARI. We then apply prior methodology on satellite imagery for distinguishing ARI features. Finally, we use the AMV dataset to experiment with different shear calculations and show that the upper-level cross-vortex flow approaches zero. We discuss the implication of these results with regards to prior works on ARI and intensification in shear.