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Dr Muhammad Adnan Abid

Postdoctoral Research Assistant

Research theme

  • Climate physics

Sub department

  • Atmospheric, Oceanic and Planetary Physics

Research groups

  • Predictability of weather and climate
adnan.abid@physics.ox.ac.uk
Robert Hooke Building, room S38
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  • About
  • Publications

SPEEDY-NEMO: performance and applications of a fully-coupled intermediate-complexity climate model

Climate Dynamics Springer 62:5 (2024) 3763-3781

Authors:

Paolo Ruggieri, Muhammad Adnan Abid, Javier García-Serrano, Carlo Grancini, Fred Kucharski, Salvatore Pascale, Danila Volpi

Abstract:

A fully-coupled general circulation model of intermediate complexity is documented. The study presents an overview of the model climatology and variability, with particular attention to the phenomenology of processes that are relevant for the predictability of the climate system on seasonal-to-decadal time-scales. It is shown that the model can realistically simulate the general circulation of the atmosphere and the ocean, as well as the major modes of climate variability on the examined time-scales: e.g. El Niño-Southern Oscillation, North Atlantic Oscillation, Tropical Atlantic Variability, Pacific Decadal Variability, Atlantic Multi-decadal Variability. Potential applications of the model are discussed, with emphasis on the possibility of generating sets of low-cost large-ensemble retrospective forecasts. We argue that the presented model is suitable to be employed in traditional and innovative model experiments that can play a significant role in future developments of seasonal-to-decadal climate prediction.
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Predictability of Indian Ocean precipitation and its North Atlantic teleconnections during early winter

npj Climate and Atmospheric Science Springer Nature 6:1 (2023) 17

Authors:

Muhammad Adnan Abid, Fred Kucharski, Franco Molteni, Mansour Almazroui
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Separating the Indian and Pacific Ocean Impacts on the Euro-Atlantic Response to ENSO and Its Transition from Early to Late Winter

Journal of Climate American Meteorological Society 34:4 (2021) 1531-1548

Authors:

Muhammad Adnan Abid, Fred Kucharski, Franco Molteni, In-Sik Kang, Adrian M Tompkins, Mansour Almazroui
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An Adaptive Nudging Scheme with Spatially Varying Gain for Improving the Ability of Ocean Temperature Assimilation in SPEEDY-NEMO

(2026)

Authors:

Yushan Wang, Fei Zheng, Changxiang Yan, Muhammad Adnan Abid

Abstract:

Nudging still is a cost-effective data assimilation technique in coupled climate models, but conventional schemes apply fixed spatial strengths and are less effective in representing heterogeneous ocean processes. An adaptive nudging framework based on a spatially varying gain matrix is proposed to dynamically balance model and observational errors. The method not only preserves the merits of the latitude-dependent nudging approach but also provides a more physically consistent determination of the spatial distribution of nudging coefficients. Implemented in the SPEEDY-NEMO coupled model, the framework is systematically evaluated against the traditional latitude-dependent scheme. Results show that the adaptive approach substantially improves subsurface temperature assimilation, particularly in the Niño3.4 region, the tropical Indian Ocean, North Pacific, North Atlantic, and the northeastern Pacific. In the tropics, the improvement is mainly achieved above and within the thermocline (roughly 100--200 m), where strong vertical stratification and sharp gradients make fixed nudging strengths inadequate:the RMSE decreases by 20% and the correlation with observations increases by 30% compared with the traditional latitude-dependent scheme. By dynamically adjusting the assimilation strength, the adaptive scheme better constrains the thermocline variability and surface-subsurface interactions. In mid- to high-latitude regions, the improvement extends to greater depths, consistent with a deeper thermocline, where oceanic processes dominated by the mixed layer dynamics and convection exhibit large regional biases that require spatially adaptive correction. In addition, compared with the latitude-dependent nudging scheme, the adaptive approach achieves simultaneous corrections of both the systematic bias term and the variance term of temperature deviations, thereby enhancing not only the mean state but also the model’s ability to capture variability. Generally, the root-mean-square errors decrease by 20-30% and the correlation with observations increases around 30-50% by the adaptive scheme. Beyond temperature, improvements are also evident in salinity, currents, and sea surface height anomalies, indicating the broader benefits of the adaptive scheme. These results indicate that spatially adaptive nudging provides a more effective and practical alternative to fixed schemes, offering a solid basis for improving ocean state estimation in coupled models.
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Response of Early Winter Precipitation and Storm Activity in the North Atlantic–European–Mediterranean Region to Indian Ocean SST Variability

Geophysical Research Letters Wiley 52:20 (2025) e2025GL116732

Authors:

M Reale, A Raganato, F D'Andrea, M Adnan Abid, A Hochman, NR Chowdhury, S Salon, F Kucharski

Abstract:

Plain Language Summary: We investigate how the variability in the Indian Ocean Sea Surface Temperature in autumn, known as the Indian Ocean Dipole (IOD), influences the precipitation regime and storm activity in the North Atlantic, Europe, and Mediterranean regions during the winter season. Our results indicate that IOD variability triggers December shifts in atmospheric pressure over these regions and alters precipitation patterns, influencing the frequency and intensity of precipitation events. The strongest impacts are observed at mid‐latitudes, with storm activity decreasing over the Eastern Atlantic and Western Mediterranean. These storm changes are tied to stronger temperature contrasts between the north and south part of the domain, which produce significant changes in the vertical wind shear. Our study further supports the idea that Indian Ocean variability may influence the early winter weather in Europe and the Mediterranean—an important insight for improving sub‐seasonal to seasonal forecasts.
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