Toxicological safety and stress-reducing effects of Datura metel extract in juvenile Macrobrachium rosenbergii - Azhar Ismail; Kamariah Bakar; Tan Hock Seng; Liew Hon Jung; Mohd Amran Aaqillah-Amr; Nurul Ulfah Karim (Aquaculture, 2026)

Projecting future climate extremes in the glacier-fed upper indus basin using machine learning based downscaling of CMIP6 GCMs - Muhammad Amjad Saleem; Muhammad Shoaib; Sarfraz Hashim; Muhammad Shoaib; Hafiz Umar Farid; Muhammad Ismail; Mubashir Ali Ghaffar; Ahmad Mujtaba; Jinwook Lee; Muhammad Azhar Inam; Arshad Ameen (Theoretical and Applied Climatology, 2025)

Machine learning-based streamflow projections in the upper indus basin under CMIP6 climate scenarios - Muhammad Amjad Saleem; Muhammad Shoaib; Sarfraz Hashim; Muhammad Shoaib; Hafiz Umar Farid; Mubashir Ali Ghaffar; Muhammad Ismail; Arshad Ameen; Jinwook Lee; Muhammad Azhar Inam; Changhyun Jun (Physics and Chemistry of the Earth, Parts A/B/C, 2025)

ENSO teleconnections and predictability of the boreal summer temperature over the Arabian Peninsula in C3S and Saudi-KAU seasonal forecast systems - Mansour Almazroui; M. Salman Khalid; Muhammad Adnan Abid; Irfan Ur Rashid; Shahzad Kamil; Haroon Siddiqui; M. Nazrul Islam; Muhammad Ismail; Muhammad Azhar Ehsan; Enda O'Brien; Mazen Asiri; Rayees Ahmed; et al. (Atmospheric Research, 2025)

Analyses of groundwater level in a data-scarce region based on assessed precipitation products and machine learning - Ahmed El-Azhari; Ismail Karaoui; Yassine Ait Brahim; Mohamed Azhar; Abdelghani Chehbouni; Lhoussaine Bouchaou (Groundwater for Sustainable Development, 2024)

Hematological, immuno-antioxidant disruptions, and genes down-regulation induced by Aeromonas veronii challenge in Clarias gariepinus: The ameliorative role of silica nanoparticles - Afaf N. Abdel Rahman; Hassnaa Mahmoud Elsheshtawy; Engy Mohamed Mohamed Yassin; Ahmed Omran; Marwa Abo Hashem; Azhar Eltanahy; Tarek Khamis; Sameh H. Ismail; Morteza Yousefi; Heba H. Mahboub (Fish & Shellfish Immunology, 2023)

Seasonal predictability of Ethiopian Kiremt rainfall and forecast skill of ECMWF's SEAS5 model - Muhammad Azhar Ehsan; Michael K. Tippett; Andrew W. Robertson; Mansour Almazroui; Muhammad Ismail; Tufa Dinku; Nachiketa Acharya; Asher Siebert; Jemal Seid Ahmed; Asaminew Teshome (Climate Dynamics, 2021)

Predicting peak summer monsoon precipitation over Pakistan in ECMWF SEAS5 and North American Multimodel Ensemble - Muhammad Azhar Ehsan; Michael K. Tippett; Fred Kucharski; Mansour Almazroui; Muhammad Ismail (International Journal of Climatology, 2020)
The potential and actual forecast skill of peak summer monsoon precipitation (July–August [JA]) over the core summer monsoon region of Pakistan (CSMRP: 68°–76°E, 30°–36°N) is investigated. The predictions from the latest version of the European Centre for Medium‐Range Weather Forecast System5 (SEAS5) and the North American Multimodel Ensemble (NMME) initialized in the beginning of June, May, and April are utilized. The potential skill is estimated by signal‐to‐noise ratio and perfect model correlation. The forecast skill is evaluated using the temporal anomaly correlation as well as the ranked probability skill score for probabilistic forecasts. The SEAS5 generally captures the observed climatological mean and variability patterns of peak summer monsoon precipitation over the region, with some biases mainly located over the complex topography zones. Observed SST anomalies in the El Niño–Southern Oscillation (ENSO) region are negatively correlated with observed peak summer monsoon precipitation over the region. The ENSO–precipitation connection is weakly reproduced in SEAS5 at Lead‐1 and fades gradually with increasing lead time. The potentially predictable component (signal) is small compared to the unpredictable part (noise). Nonetheless, statistically significant potential skill is found over the CSMRP. However, the forecast skill of peak summer monsoon precipitation over the region is lower than the potential skill in SEAS5. A multimodel ensemble average of five models shows little benefit in predicting peak monsoon precipitation over Pakistan. Extended spatial averaging has some impact on the skill; however, temporal averaging has no effect on the skill of the summer monsoon precipitation in SEAS5. Together these results show limitations of the current seasonal prediction models and demonstrate their inadequate performance in predicting peak summer monsoon precipitation over Pakistan.

Potential predictability of Arabian peninsula summer surface air temperature in the North American multimodel ensemble - Muhammad Azhar Ehsan; Fred Kucharski; Mansour Almazroui; Muhammad Ismail; Michael K. Tippett (Climate Dynamics, 2019)

Skill and predictability in multimodel ensemble forecasts for Northern Hemisphere regions with dominant winter precipitation - Muhammad Azhar Ehsan; Michael K. Tippett; Mansour Almazroui; Muhammad Ismail; Ahmed Yousef; Fred Kucharski; Mohamed Omar; Mahmoud Hussein; Abdulrahman A. Alkhalaf (Climate Dynamics, 2017)

Analysis of heavy metal concentrations in sediments of selected estuaries of Malaysia—a statistical assessment - Abbas F. M. Alkarkhi; Norli Ismail; Aness Ahmed; Azhar mat Easa (Environmental Monitoring and Assessment, 2009)

Multivariate analysis of heavy metals concentrations in river estuary - Abbas F. M. Alkarkhi; Anees Ahmad; Norli Ismail; Azhar Mat Easa (Environmental Monitoring and Assessment, 2008)