@article{Ishraque2026,
  title = {Assessing Challenges for U.S.-Based Polar Early Career Scientists During Science Policy Changes},
  url = {http://dx.doi.org/10.31223/X5NR5S},
  DOI = {10.31223/x5nr5s},
  publisher = {California Digital Library (CDL)},
  author = {Ishraque,  Fairuz and Shadab,  Mohammad Afzal and Shionalyn,  Kevin and Narayanan,  Neosha and Schaberg,  Meghan and Gaikwad,  Shreyas and Ezukanma,  Izuchukwu and Lauter,  Olga and Higgins,  John},
  year = {2026},
  month = Sept 
}
}

@inbook{doi:10.1137/1.9781611979039.10,
author = {Laurent Hascoët and Jean-Luc Bouchot and Shreyas Sunil Gaikwad and Sri Hari Krishna Narayanan and Jan Hückelheim},
title = {Profiling Checkpointing Schedules in Adjoint Source-Transformation AD},
booktitle = {Proceedings of the 2024 International Conference on Algorithmic Differentiation (AD)},
chapter = {},
pages = {137-149},
doi = {10.1137/1.9781611979039.10},
URL = {https://epubs.siam.org/doi/abs/10.1137/1.9781611979039.10},
eprint = {https://epubs.siam.org/doi/pdf/10.1137/1.9781611979039.10},
    abstract = { Abstract. Checkpointing is a cornerstone of data-flow reversal in adjoint algorithmic differentiation. It is a trade-off between storage and recomputation that can be applied at different levels, one of which being the call tree. We are looking for good placements of checkpoints onto the call tree of a given application, to reduce run time and memory footprint of its adjoint. There is no known optimal solution to this problem other than a combinatorial search on all placements. We propose a heuristics based on run-time profiling of the adjoint code. We describe an implementation of this profiling tool in an existing source-transformation automatic differentiation tool. We demonstrate the interest of this approach on test cases taken from the MITgcm ocean and atmospheric global circulation model. We discuss the limitations of our approach and propose directions to lift them. }
}
}

@article{GAIKWAD2024107512,
title = {MITgcm-AD v2: Open source tangent linear and adjoint modeling framework for the oceans and atmosphere enabled by the Automatic Differentiation tool Tapenade},
journal = {Future Generation Computer Systems},
pages = {107512},
year = {2024},
issn = {0167-739X},
doi = {https://doi.org/10.1016/j.future.2024.107512},
url = {https://www.sciencedirect.com/science/article/pii/S0167739X2400476X},
author = {Shreyas Sunil Gaikwad and Sri Hari Krishna Narayanan and Laurent Hascoet and Jean-Michel Campin and Helen Pillar and An Nguyen and Jan Hückelheim and Paul Hovland and Patrick Heimbach},
keywords = {Automatic differentiation, Differentiable programming, Adjoints, Ocean modeling, Data assimilation, Climate science, MITgcm, Tapenade},
abstract = {The Massachusetts Institute of Technology General Circulation Model (MITgcm) is widely used by the climate science community to simulate planetary atmosphere and ocean circulations. A defining feature of the MITgcm is that it has been developed to be compatible with an algorithmic differentiation (AD) tool, TAF, enabling the generation of tangent-linear and adjoint models. These provide gradient information which enables dynamics-based sensitivity and attribution studies, state and parameter estimation, and rigorous uncertainty quantification. Importantly, gradient information is essential for computing comprehensive sensitivities and performing efficient large-scale data assimilation, ensuring that observations collected from satellites and in-situ measuring instruments can be effectively used to optimize a large uncertain control space. As a result, the MITgcm forms the dynamical core of a key data assimilation product employed by the physical oceanography research community: Estimating the Circulation and Climate of the Ocean (ECCO) state estimate. Although MITgcm and ECCO are used extensively within the research community, the AD tool TAF is proprietary and hence inaccessible to a large proportion of these users. The new version 2 (MITgcm-AD v2) framework introduced here is based on the source-to-source AD tool Tapenade, which has recently been open-sourced. Another feature of Tapenade is that it stores required variables by default (instead of recomputing them) which simplifies the implementation of efficient, AD-compatible code. The framework has been integrated with the MITgcm model’s main branch and is now freely available.}
}

@article { Earthsystemreanalysisinsupportofclimatemodelimprovements,
      author = "Detlef Stammer and Daniel E. Amrhein and Magdalena Alonso Balmaseda and Laurent Bertino and Massimo Bonavita and Carlo Buontempo and Nico Caltabiano and Francois Counillon and Ian Fenty and Raffaele Ferrari and Yosuke Fujii and Shreyas Sunil Gaikwad and Pierre Gentine and Andrew Gettelman and Ganesh Gopalakrishnan and Patrick Heimbach and Hans Hersbach and Chris Hill and Shinya Kobayashi and Armin Köhl and Paul J. Kushner and Matthew Mazloff and Hisashi Nakamura and Stephen G. Penny and Laura Slivinski and Susann Tegtmeier and Laure Zanna",
      title = "Earth system reanalysis in support of climate model improvements",
      journal = "Bulletin of the American Meteorological Society",
      year = "2024",
      publisher = "American Meteorological Society",
      address = "Boston MA, USA",
      doi = "10.1175/BAMS-D-24-0110.1",
      url = "https://journals.ametsoc.org/view/journals/bams/aop/BAMS-D-24-0110.1/BAMS-D-24-0110.1.xml"}

@article{Gaikwad2023, 
doi = {10.21105/joss.04679}, 
url = {https://doi.org/10.21105/joss.04679}, 
year = {2023}, 
publisher = {The Open Journal}, 
volume = {8}, number = {83}, pages = {4679}, 
author = {Shreyas Sunil Gaikwad and Laurent Hascoet and Sri Hari Krishna Narayanan and Liz Curry-Logan and Ralf Greve and Patrick Heimbach}, 
title = {SICOPOLIS-AD v2: tangent linear and adjoint modeling framework for ice sheet modeling enabled by automatic differentiation tool Tapenade}, 
journal = {Journal of Open Source Software} }