What is he best known for?
The fields of study he is best known for:
- Statistics
- Machine learning
- Drainage basin
His scientific interests lie mostly in Precipitation, Global warming, Kharif crop, Spatial distribution and Western Disturbance.
His Precipitation research is multidisciplinary, incorporating elements of Monsoon and Seasonality.
Kamal Ahmed combines subjects such as Physical geography and Precipitation index with his study of Seasonality.
The Global warming study combines topics in areas such as Percentile, Common spatial pattern, Heat wave and Forcing.
His Spatial distribution study incorporates themes from General Circulation Model, Coupled model intercomparison project, GCM transcription factors, Climatic variables and Entropy.
Kamal Ahmed has researched Western Disturbance in several fields, including Cropping and Evapotranspiration.
His most cited work include:
- Weighting Methods and their Effects on Multi-Criteria Decision Making Model Outcomes in Water Resources Management (112 citations)
- Impacts of climate variability and change on seasonal drought characteristics of Pakistan (58 citations)
- Impacts of climate variability and change on seasonal drought characteristics of Pakistan (58 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Precipitation, Coupled model intercomparison project, Downscaling, Trend analysis and Random forest.
His studies in Precipitation integrate themes in fields like Cropping, Monsoon and Kharif crop.
As a part of the same scientific family, Kamal Ahmed mostly works in the field of Kharif crop, focusing on Evapotranspiration and, on occasion, Global warming and Physical geography.
His Coupled model intercomparison project study combines topics in areas such as Forecast skill and Feature selection.
His Downscaling research includes themes of Quantile, Projection and Representative Concentration Pathways.
His research integrates issues of Quantile regression and Range in his study of Random forest.
He most often published in these fields:
- Precipitation (57.35%)
- Coupled model intercomparison project (42.65%)
- Downscaling (30.88%)
What were the highlights of his more recent work (between 2019-2021)?
- Trend analysis (26.47%)
- Coupled model intercomparison project (42.65%)
- Kharif crop (20.59%)
In recent papers he was focusing on the following fields of study:
Trend analysis, Coupled model intercomparison project, Kharif crop, General Circulation Model and Projection are his primary areas of study.
His study in Trend analysis is interdisciplinary in nature, drawing from both Physical geography, Crop water stress and Food security.
His Replicate research extends to the thematically linked field of Coupled model intercomparison project.
His Kharif crop research integrates issues from Wind speed, Predictive modelling, Machine learning and Artificial intelligence.
His GCM transcription factors study, which is part of a larger body of work in General Circulation Model, is frequently linked to Impact assessment, Greenhouse gas, Southeast asia and Mainland, bridging the gap between disciplines.
His biological study spans a wide range of topics, including Selection, Forecast skill, Forcing, Spatial distribution and Heat wave.
Between 2019 and 2021, his most popular works were:
- Prediction of droughts over Pakistan using machine learning algorithms (22 citations)
- Prediction of droughts over Pakistan using machine learning algorithms (22 citations)
- Selection of GCMs for the projection of spatial distribution of heat waves in Pakistan (15 citations)
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