dc.contributor.author |
Jayaminda, C |
|
dc.contributor.author |
Gunawardhana, L |
|
dc.contributor.author |
Rajapakse, L |
|
dc.contributor.editor |
Abeysooriya, R |
|
dc.contributor.editor |
Adikariwattage, V |
|
dc.contributor.editor |
Hemachandra, K |
|
dc.date.accessioned |
2024-03-18T03:12:33Z |
|
dc.date.available |
2024-03-18T03:12:33Z |
|
dc.date.issued |
2023-12-09 |
|
dc.identifier.citation |
C. Jayaminda, L. Gunawardhana and L. Rajapakse, "Rating Performances of Global Climate Models in Capturing Monsoon Rainfall Patterns in Sri Lanka," 2023 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, 2023, pp. 264-269, doi: 10.1109/MERCon60487.2023.10355390. |
en_US |
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/22329 |
|
dc.description.abstract |
Climate change plays a significant role in decision
making regarding water management. Understanding and
projecting the future climate of Sri Lanka is crucial for the
development of appropriate adaptation and mitigation strategies.
This research paper focuses on evaluating the performance of the
Multiple Imputation by Chained Equations (MICE) imputation
package for filling in missing data and the latest Coupled Model
Intercomparison Project phase 6 (CMIP6) models for simulating
the monsoon climate in Sri Lanka. The research utilizes observed
daily precipitation data from 27 meteorological stations and
employs the predictive mean matching (PMM) and normal
imputation (Norm) methods for MICE algorithm to impute
missing data. The performance of 15 CMIP6 models is evaluated
using statistical techniques. The evaluation methodology includes
assessing the models based on distance from the average solution
using the Evaluation Based on Distance from Average Solution
(EDAS) method. The results and analysis of the study provide
insights into the performance of the CMIP6 models in simulating
the monsoon climate of Sri Lanka in different climatic zones. The
findings contribute to the selection of a suitable climate model
for future climate change studies in Sri Lanka and support the
development of effective adaptation and mitigation strategies in
response to a changing climate. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IEEE |
en_US |
dc.relation.uri |
https://ieeexplore.ieee.org/document/10355390 |
en_US |
dc.subject |
Climate change |
en_US |
dc.subject |
Data imputation |
en_US |
dc.subject |
EDAS |
en_US |
dc.subject |
MICE |
en_US |
dc.subject |
Performance metrics |
en_US |
dc.title |
Rating performances of global climate models in capturing monsoon rainfall patterns in Sri Lanka |
en_US |
dc.type |
Conference-Full-text |
en_US |
dc.identifier.faculty |
Engineering |
en_US |
dc.identifier.department |
Engineering Research Unit, University of Moratuwa |
en_US |
dc.identifier.year |
2023 |
en_US |
dc.identifier.conference |
Moratuwa Engineering Research Conference 2023 |
en_US |
dc.identifier.place |
Katubedda |
en_US |
dc.identifier.pgnos |
pp. 264-269 |
en_US |
dc.identifier.proceeding |
Proceedings of Moratuwa Engineering Research Conference 2023 |
en_US |
dc.identifier.email |
jayamindakac.22@uom.lk |
en_US |
dc.identifier.email |
lumindang@uom.lk |
en_US |
dc.identifier.email |
lalith@uom.lk |
en_US |