Language to modernize a scientific Fortran codebase
The modern language you are looking for is called modern Fortran 2018. Fortran 2008 and 2018 have everything a numerical computing project would need and so many features that many other languages mentioned here lack (including extremely pleasant array-syntax which has inspired all other languages such as MATLAB, Python, R, Julia, ..., even C++ numerical libraries). It is the only language that has native built-in parallelism and is the only language, along with C, for which the official MPI parallelism standard is released. It has also excellent vendor support for GPU parallel computing and as I heard in SC18, some vendors like NVIDIA/PGI have already started implementing the native parallelism features of Fortran via GPUs.
Modern Fortran is a high-level language comparable to MATLAB and Python, yet 100-500 times faster than both (https://modelingguru.nasa.gov/docs/DOC-2783). Using Coarray Fortran you can seamlessly parallelize your code with minimal effort to run it from your laptop to the largest supercomputers in the world. No other language has such capability at the moment. Fortran is also the only language that has all levels of parallelism, from instruction level to vectorized, concurrent, and coarray-distributed parallel computing. If such features are not considered &quot;modern&quot;, perhaps &quot;post-modern&quot; would be a better description.
Fortran has been a reliable lasting language for almost 3 quarters of a century and has excellent highly-optimized compiler support (Intel, GNU, NAG, IBM, PGI/NVIDIA, ...). If you want to write code that lasts decades, then port your FORTRAN77 code to modern Fortran with minimal effort and save yourself time, energy, money, and computational power.
A good start with modern parallel object-oriented Fortran is &quot;Modern Fortran Explained: Incorporating Fortran 2018&quot; by Metcalf et al.
If you decide to port your code effortlessly to modern Fortran, you can also get help from the official Fortran language website https://fortran-lang.org/ and the community of programmers on Fortran discourse: https://fortran-lang.discourse.group/
Update Nov 17, 2020
Just yesterday NVIDIA released a news post on its GPU implementation of the concurrent features of Fortran 2008 / 2018. Users can now write code in pure modern Fortran and let the compiler automatically offload it to GPUs for thousands-way parallelism.
What is the relevance and importance of this achievement? The same Fortran code that a user writes can now be parallelized via GPUs, distributed CPUs, OpenMP threads, or auto-parallelization features of the Fortran compiler depending on the user's platform and compiler choice. All of that complexity is hidden from the user. No need for preprocessing and conditional compilations anymore. This further enhances the excellent existing portability of Fortran programs across platforms and architectures.