Quantum Computing For Climate Model
Nandini
, Nayana P R , Pushpanjali
– quantum computing, climate modeling, quantum simulation, Variational Quantum Eigensolver (VQE), Quantum Approximate Optimization Algorithm (QAOA), Quantum Machine Learning (QML), General Circulation Model (GCM), Noisy Intermediate-Scale Quantum (NISQ) devices, Fault-Tolerant Quantum Computing, hybrid quantum-classical algorithms.
Climate modeling is one of the most complex computational tasks in today’s world since it involves modeling extremely complex physical systems of atmosphere, oceans, land surfaces, and cryosphere, from micrometre-scale droplets in clouds to kilometerscale atmospheric currents on planetary scale and from weather phenomena lasting minutes to thousands-yearly climate variations. Modern HPC systems are highly efficient in terms of computing power, but due to their intrinsic architectural constraints of computing speed, memory bandwidth, and energy consumption, there exist limitations in the resolution, quality, and number of possible simulation runs. The recently emerged field of quantum computing utilizes quantum mechanical effects, such as superposition, entanglement, and quantum interference, in order to offer a whole new suite of techniques and algorithms which could solve many problems faster than any existing classical methods do. In particular, thanks to the peculiar properties of qubits, the quantum equivalent of binary bits, the solutions of certain problems can be explored in exponentially large spaces at once. Here, we review the topic of the relationship between quantum computing and climate modeling in great depth. First, we analyze the bottlenecks of classical computer resources in the existing Earth System Models (ESMs). We explore the landscape of quantum computers and algorithms for application in climate science. Finally, we devise a step-by-step framework to implement quantum computing into climate prediction operations. Important highlights from this study are:
"Quantum Computing For Climate Model", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 4, page no.c558-c563, April-2026, Available :https://rjpn.org/JETNR/papers/JETNR2604339.pdf
Volume 4
Issue 4,
April-2026
Pages : c558-c563
Paper Reg. ID: JETNR_234047
Published Paper Id: JETNR2604339
Downloads: 00022
Research Area: Science and Technology
Country: Ramanagara, Karnataka, India
ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: RJPN (IJPublication) Janvi Wave
