ROPP should not be viewed as a “black box” processor but as a suite of library functions and example applications (written in Fortran 95). The software was originally intended for users who wish to combine RO-specific routines with their own code, but by now ROPP has developed into a package which offers validated standalone tools for format conversion and RO data processing. Whichever way ROPP is used, users are welcome to modify or replace components in ROPP to suit their existing local systems.

Updates to ROPP – which include new science, modifications in response to new data or software dependencies, and bug fixes – are regularly released by the ROM SAF after a period of review and beta-testing by interested parties.

ROPP functionality mirrors most aspects of the ROM SAF operational data production chain (i.e. the generation of NRT

near-real time

ROPP consists of a number of modules, some of which depend on others. Modules not only contain source code but also build and test scripts, data, example test results and user documentation. The ROPP-7.0 modules and their headline functionalities are listed in Table , and the relations between them are indicated in Fig. . The main purpose and functionality of each module are discussed in the following sections, but, in brief, the two service modules and three scientific modules of ROPP are as follows.

The utilities module of ROPP includes quality control and range-checking tools, and a variety of conversion routines, including co-ordinate transformations (between Earth-centred inertial (ECI) and Earth-centred, Earth-fixed (ECEF) co-ordinates, geopotential and geometric heights, etc.) and date/time and unit conversions.

The input and output module of ROPP provides access to a variety of data formats:

EUMETSAT's EPS CGS

European Polar System Core Ground Segment

ROPP handles these diverse data formats by converting them to its own well-defined RO data structure (in netCDF).

The preprocessing module contains tools to undertake the staged preprocessing from excess phase (i.e. the phase accumulated by the carrier wave during transit of the atmosphere and ionosphere above that which would be accumulated along a straight line path in vacuo between the transmitter and receiver) to bending angle, through to refractivity and dry temperature . It also contains tools to diagnose tropopause heights from profiles of bending angle, refractivity, dry temperature or background model temperature .

The forward modelling module contains forward operators (including tangent linear, adjoint and gradient calculation code) for pressure-based, height-based and hybrid NWP model vertical grids, to generate refractivities and bending angles from model state variables . It also includes a 2-D bending angle calculation tool .

The 1D-Var module contains cost function minimisers that allow the retrieval of pressure/height, temperature and humidity profiles from refractivity or bending angle profiles, given colocated NWP model background profiles .

ROPP also includes sample reference data files and example output test files, as well as full user documentation. Further details of its contents and capabilities can be found in the “ROPP Overview Guide” document at http://www.romsaf.org.

The ROPP UTILS module provides height- and date-conversion routines, and other general purpose library functions such as string handling, message output, array manipulation and basic mathematical routines. These are used by other ROPP modules and would probably not be called directly by users from their own programs. Table  lists some of the routines in this module.

ROPP is designed for terrestrial applications. If a user wished to develop RO tools appropriate to other planetary atmospheres, the ROPP UTILS module is where the bulk of the changes (to planetary radius, gravity, rotation rate etc.) would need to be made.

The ROPP IO module reads radio occultation data from a variety of sources (EUMETSAT; BUFR; UCAR; GFZ; and, for background profiles, text and GRIB files) and converts them to ROPP's internal, netCDF-based format for radio occultation data. ROPP can also write out such data in BUFR format. Most of these data-reading tools use data thinning and range-checking routines which are themselves part of the module. Table  lists some of the routines and tools in the IO module.

Figure  shows the results of passing a rising COSMIC-1 “atmPhs” profile (20.3∘ W, 19.5∘ S, 01:02 UTC, 1 October 2012) – containing excess phase and amplitude data, and downloaded from the CDAAC website (http://cdaac-www.cosmic.ucar.edu/cdaac) – through ucar2ropp. It also shows the background temperatures and humidities that result when GRIB2-formatted ECMWF analyses, downloaded from the ECMWF website (http://www.ecmwf.int), are passed through grib2bgrasc and bgrasc2ropp.

The ROPP PP module has been largely adopted from the OCC code developed by Michael Gorbunov at the Institute for Atmospheric Physics, Moscow. OCC has been shown to generate refractivities that are in excellent agreement (less than 0.2 % systematic difference) with those calculated at UCAR and by forward modelling ECMWF analyses http://www.ecmwf.int;.

ROPP PP provides routines to compute L1 and L2 bending angles from excess phase data by geometrical optics and wave optics methods. Ionospherically corrected bending angle profiles are derived by combining L1 and L2 bending angles linearly or in a statistically optimised way. Climatological bending angle profiles are appended above the corrected ones, in order that refractivity profiles can be calculated by means of an inverse Abel transform. Dry temperatures are generated from the refractivities. ROPP PP also contains code to calculate tropopause heights from a variety of fields in an RO profile. Table  lists some of the routines and tools in this module.

In more detail, the tools in the ropp_pp module perform the following tasks.

processes excess phase and amplitude data into refractivity, bending angle and dry temperature profiles, in the following steps.

Read “level 1a” data, i.e. satellite positions, L1 and L2 signal amplitudes and phases.

Figure  shows the output of ropp_pp_occ_tool when the unprocessed COSMIC excess phase data shown in Fig.  are passed through it. The derived bending angles are also displayed.

is almost the same as ropp_pp_occ_tool, but starts from “level 1b” L1 and L2 bending angles before generating linearly combined bending angles, statistically optimised bending angles, refractivities and dry temperature profiles, as before.

diagnoses tropopause heights, as follows.

Read the bending angle, refractivity, dry temperature or background model temperature profile.

Figure  shows the tropopause heights for the COSMIC occultation and colocated/simultaneous ECMWF background profile used in this paper. All six are reasonably close, and the four “observationally” based TPHs are within 400 m after the impact altitude of the bending-angle-based TPH has been converted to altitude by dividing by the refractive index at the tropopause (a downward shift of around 200 m).

The ROPP FM module contains forward operators which calculate refractivity and bending angle profiles from background model data on pressure-based, height-based and “hybrid” NWP model vertical grids. Tangent linear, adjoint and gradient codes of the forward operators are provided for use in assimilation processing. Table  lists some of the routines and tools in this module.

In more detail, the tools in the ropp_fm module perform the following tasks.

forward models 1-D background fields into profiles of refractivity and bending angle, in the following steps.

Read level 2b input model data (ECMWF pressure-based or Met Office height-based) and generate a “state vector” x of pressure p, temperature T and humidity q as functions of geopotential height Z.

The “innovation” curves (i.e. observation minus forward modelled background) in the top two panels of Fig.  show the bending angles and refractivities that result from passing the background profiles in the bottom two panels of Fig.  through ropp_fm_bg2ro_1d.

extends the forward modelling of ropp_fm_bg2ro_1d by accounting for variation of the refractivity across the occultation plane, rather than just in the vertical at the tangent point. This has been found to have a beneficial effect on O–B differences in the lower troposphere . It works as follows.

Read 2-D level 2b input model data (ECMWF pressure-based or Met Office height-based) and generate a 2-D state vector x of pressure p, temperature T and humidity q as functions of geopotential height Z and (uniformly spaced) horizontal angle θ.

The ROPP 1DVAR module provides quality control, minimisation and diagnostic routines for the retrieval of pressure, geopotential height, temperature and humidity profiles from profiles of refractivity or bending angle and (colocated, simultaneous) NWP background profiles, together with error covariance matrices of the observation and background. Table  lists some of the routines and tools in this module.

In more detail, the tools in the ropp_1dvar module perform the following tasks.

carries out a 1D-Var minimisation of the usual cost function J, where 2J(x)=(x-b)TB-1(x-b)+(o-H(x))TO-1(o-H(x)), where x is the state vector, b is the background state vector, o is the vector of bending angle observations, H is the (non-linear) forward model (Sect. ), B is the background error covariance matrix and O is the covariance matrix of the combined measurement and forward model error. It works as follows.

Read input model data (ECMWF pressure-based or Met Office height-based) and generate the background state vector b of temperature T and humidity q as functions of geopotential height Z.

Figure  shows the result of passing the (LC) bending angle profile shown in Fig.  and the colocated ECMWF background profile shown in Fig.  through ropp_1dvar_bangle. The retrieval has generally pulled the background towards the observations, as expected. Temperature increments of around 1 K and specific humidity increments of around 1 g kg-1 near the surface result.

Figure  also compares the ROPP-derived bending angles and refractivities with those in the corresponding “atmPrf” file, as processed by UCAR. Below 40 km the ROPP refractivities are closer to those of UCAR than they are to the forward modelled ECMWF background, which lends confidence to the integrity of the ROPP refractivities for this occultation. Above 40 km the ROPP refractivities are up to 5 % larger than those of UCAR. This may be due to different statistical optimisation (blending of noisy bending angles with smoother climatology) applied in the two codes. ROPP is closer to the ECMWF background in this regime.

The UCAR and ROPP bending angles are also closer to each other than either is to the forward modelled ECMWF background between 10 and 40 km. Below 10 km the difference between UCAR and ROPP is possibly due to different treatments of the open loop data in this regime. Above 40 km the differences may again be due to different statistical optimisation in the two codes.

does the same as ropp_1dvar_bangle but uses refractivity observations instead of bending angles. Naturally, different observation background errors O are needed.

The O–B and O–A profiles of a retrieval based on the refractivities generated (automatically) by ropp_pp_occ_tool, by inverse Abel transform of the bending angles of Fig. , are shown in the top right element of Fig. . Again, the 1D-Var retrieval procedure has drawn the background to the observations. (Note that the temperature and humidity increments in this figure come from the bending angle retrieval.)

The ROPP TEST module comprises a comprehensive suite of test routines, and associated test data sets, which can be run on a range of compilers and platforms. This “Test Folder” is one of the main ways of formally validating the ROPP code prior to public release of a new major version of the package. Table  lists some of the elements of this module.

Note that the complete ropp_test suite is not intended for users but for internal validation of the ROPP code, although some functionality of ropp_test is included in ropp_io, ropp_pp, ropp_fm and ropp_1dvar for users to verify that the code has been correctly built.

Full implementation of ROPP requires the installation of some standard freely available third-party software packages, principal among which is the netCDF library for general data input and output. Some tools need access to a BUFR library for reading or writing NWP data in that format. Another uses routines in a GRIB library to extract background profiles from a gridded data set. The ROPP documentation clearly indicates which packages are needed by which modules and tools. Naturally, any licence restrictions associated with these packages must be adhered to by ROPP users.