Abstract. This paper describes the Radio Occultation Processing Package, ROPP, a product of the EUMETSAT Radio Occultation Meteorology Satellite Application Facility (ROM SAF) developed by a large number of scientists over many years. A brief review of the concepts, functionality and structure of ROPP is followed by more detailed descriptions of its key capabilities. Example results from a full chain of processing using some of the ROPP tools are presented. Some current and prospective uses of ROPP are given. Instructions on how to access the code and its supporting documentation are provided.
Abstract. The bending angle observation operator (forward model) currently used to assimilate radio occultation (RO) data at the Met Office, the European Centre for MediumRange Weather Forecasts (ECMWF) and other centres is the same as is included in the Radio Occultation Processing Package (ROPP), along with the corresponding tangentlinear and adjoint code. The functionality of this package will be described in another paper in this issue. The mean bending angle innovations produced with this operator using Met Office background fields show a bias that oscillates with height and whose magnitude peaks between the model levels. These oscillations have been attributed to shortcomings in the assumption of exponentially varying refractivity between model levels. This is used directly in the refractivity operator, and indirectly to produce forward-modelled bending angles via the Abel transform. When the spacing between the model levels is small, this assumption is acceptable, but at stratospheric heights where the model level spacing is large, these biases can be significant, and can potentially degrade analyses. This paper provides physically based improvements to the functional form of refractivity with height. These new assumptions considerably improve the oscillatory bias, and a number of approaches for practical implementation of the bending angle operator are provided.
A new method to estimate radiosonde temperature biases using radio occultation measurements as a reference has been developed. The bias is estimated as the difference between mean radio occultation and mean radiosonde departures from collocated profiles extracted from the Met Office global numerical weather prediction (NWP) system. Using NWP background profiles reduces the impact of spatial and temporal collocation errors. The use of NWP output also permits determination of the lowest level at which the atmosphere is sufficiently dry to analyze radio occultation dry temperature retrievals. The authors demonstrate the advantages of using a new tangent linear version of the dry temperature retrieval algorithm to propagate bending angle departures to dry temperature departures. This reduces the influence of a priori assumptions compared to a nonlinear retrieval. Radiosonde temperature biases, which depend on altitude and the solar elevation angle, are presented for five carefully chosen upper-air sites and show strong intersite differences, with biases exceeding 2 K at one of the sites. If implemented in NWP models to correct radiosonde temperature biases prior to assimilation, this method could aid the need for consistent anchor measurements in the assimilation system. The method presented here is therefore relevant to NWP centers, and the results will be of interest to the radiosonde community by providing site-specific temperature bias profiles. The new tangent linear version of the linear Abel transform and the hydrostatic integration are described in the interests of the radio occultation community.
Abstract. This paper describes the Radio Occultation Processing Package, ROPP, a product of the EUMETSAT Radio Occultation Meteorology Satellite Application Facility (ROM SAF) developed by a large number of scientists over many years. A brief review of the concepts, functionality and structure of ROPP is followed by more detailed descriptions of its key capabilities. Example results from a full chain of processing using some of the ROPP tools are presented. Some current and prospective uses of ROPP are given. Instructions on how to access the code and its supporting documentation are provided.
Abstract. The bending angle observation operator (forward model) currently used to assimilate radio occultation (RO) data at the Met Office, ECMWF and other centres is the same as is included in the Radio Occultation Processing Package (ROPP), along with the corresponding tangent-linear and adjoint code. The functionality of this package is described in another paper in this issue. The mean bending angle innovations produced with this operator using Met Office background fields show a bias that oscillates with height and whose magnitude peaks between the model levels. These oscillations have been attributed to shortcomings in the assumption of exponentially varying refractivity between model levels. This is used directly in the refractivity operator, and indirectly to produce forward-modelled bending angles via the Abel transform. When the spacing between the model levels is small, this assumption is acceptable, but at stratospheric heights where the model level spacing is large, these biases can be significant, and can potentially degrade analyses. This paper provides physically-based improvements to the functional form of refractivity with height. These new assumptions considerably improve the oscillatory bias, and a number of approaches for practical implementation of the bending angle operator are provided.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.