Enhancing Meteorological Variables Accuracy through Bias Correction | Quantile Mapping Approach
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- เผยแพร่เมื่อ 14 ธ.ค. 2024
- Discover the cutting-edge techniques in meteorological data analysis with our in-depth exploration of bias correction and quantile mapping approaches. This video delves into the intricate world of enhancing the accuracy of meteorological variables, a crucial aspect of understanding and predicting climate change. We'll guide you through the process of improving climate model outputs, discussing the importance of bias correction in climate science, and demonstrating how quantile mapping can significantly refine our understanding of weather patterns and long-term climate trends. Whether you're a climate scientist, meteorologist, or simply passionate about environmental studies, this video offers valuable insights into the methods that are shaping our ability to forecast and adapt to our changing climate. Join us as we unravel the complexities of data correction techniques and their pivotal role in climate change research and policy-making.
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This is a great program and easy to use. I hope in the future there will be a feature to show the correlation value between observations and climate models (rsquare, pbias, NSE, etc.)
1. What value represents no data value in the input data?
2. Is this program limited to using 2 observation stations? I have tried using >3 observation stations, but the process always stops at the third station.
Thank you.
Good day! I am interested with your tutorial. Can this engine be used to bias-correct satellite rainfall data? Thank you.
Please how can we get historical GCM and future GCM for specific station as GCM is coarse resolution?
Please keep the good work going up
Thanks for your feedback Rajesh
great video
Glad you enjoyed it
Great work! I practiced bias correction but encountered a challenge: after entering the required data and clicking run, the status showed "bias correcting," yet the process does not complete, particularly for future bias correction and rainfall history. Please advise on the underlying problem. Thank you!
Hi, Please check the format of your time column and I think this is the most reason for this problem.
Please can this be applied to monthly data and how long should the series be at least? Thank you.
Hi, Yes you can it for every time spans, at least you need 5 years datasets for this
@@HydroAI2024 I used these two files (observed and sumilated) but I don't get any results. Please Help.
@@JalelBenSalemDallel It's really hard to answer without looking at your datasets.
@@HydroAI2024 Please give me your mail.
from where we can get this software its quite useful in bias correction.
Hi
please search this paper and then you can download the software:
Development of Climate Data Bias Corrector (CDBC)
Tool and Its Application over the Agro-Ecological
Zones of India
@@HydroAI2024 I have found the paper, but unfortunately, no link is given to download this software. Please guide me.
@@biluchemist Hi, Please download it from the below link:
www.mediafire.com/file/082acw7cstiz20m/CDBC-master.zip/file
Please make a video on downscaling of climate data in any region
Hi Rajesh, Yes of course.
Hi, thank you for your response. I have checked the data format according to your video, but it still cannot run the process. Every variable (temperature and precipitation) only runs when the variable/distribution part of solar radiation is selected instead of temperature and precipitation on the bias corrector tool. Could I communicate with you via email and send a sample of my climate data for you to check? Thank you.
Ok no problem, Please send your data to my gmail accuont: azizianhydroai@gmail.com