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Let me answer your first Q about "The impact of climate change on water resources" - Climate change messing with our water resources is a big worry. it messes up how rain falls, makes crazy weather happen more often, and messes with how water moves around. need to understand how storms affect water supply, floods, and nature. It's all about dealing with climate change and how it affects our precious water!

In Malaysia, how we define a storm event differs depending on where you are and who's studying it. But generally, we do a few things to figure it out:

Step 1: collect rainfall data from various weather stations nationwide. measure how much rain falls and for how long, usually every hour or day.

Step 2: look at all that rainfall data to spot any cool patterns or trends. watch for crazy heavy rain that goes on for a long time – that's when it might be a storm event!

Step 3: Using historical data and climate patterns, set a certain level of rain that makes something a storm event in that specific area. this can vary depending on the local climate and the place's geography.

Step 4: Storm events can be classified in different ways – like how much rain falls in an hour or the total rainfall over a specific time period. It helps to understand what's considered a storm.

Step 5: Check older data to find past storm events. This helps to see how often and intense storms were in the past and if anything changes.

Step 6: with climate change messing things up, we must look at historical data differently and consider how storms might change over time. Use fancy climate models to predict future rainfall trends and how storms could evolve in the future.

Step 7: keep a close watch on rainfall data all the time and update our storm event rules regularly. This helps us adapt to any changes caused by climate change messing with our rain patterns.

Hope this could help! If we stay curious and keep studying our weather, we can better understand how to deal with storms and climate change's impact on our precious water resources.

Progress in understanding Climate Change and its effects needs advances in modeling Climate Phenomena. "IPCC Models" "Climate Models" "General Circulation Models", appellations are of no importance. It is in all cases Physics-Driven Models developed within multi-disciplinary scientific teams worldwide to describe the evolution of weather phenomena (at short time scales) and climate phenomena that involve long time-scale processes, more complex to analyze, as part of these phenomena are not yet well understood.

This is why, despite the enormous progress already achieved, the predictability of Climate Models (The Earth System Models, ESMs), are not yet sufficiently accurate. The standard deviations between the different models remain of the same order of magnitude as the mean values and huge biases on regional levels are noticed and well documented in technical and scientific references of each of the models.

This should lead us to admit that more research is needed to improve our knowledge of the driving forces that control the climate in order to build more accurate predictive climate models, as scientists do well for weather prediction

See also:

https://www.researchgate.net/post/Climate_Change_and_Climate_Models_Progress_and_Limits

On Climate Models: From General Circulation Models (GCMs) and Earth System Models (ESMs). General Circulation Models (GCMs)which are the core of weather forecasting Models appeared in the 1960s with the pioneer's work of Manabe (2021 Nobel Prize in Physics). A fundamental point is that is difficult to speak about GCMs and even less of Climate Models without a minimum review starting from Atmosphere Dynamics Models genesis in the 1960s to the actual Earth System Models (ESMs) that participated in the last "CMIP6". These represent the State-of-art of universal knowledge about Climate and its modeling. The results published in 2021 covers 80 ESMs from as many research teams throughout the world. Nowadays, Climate Science and Modelling have attained an international critic-mass never reached in any other domain.

ESMs include a number of components that try to describe the evolution of intercoupled phenomena that govern Climate Phenomena. To understand how this works, one has to know about the progress achieved and still-opened questions related to Climate Models. Mathematically the resolution of the dynamic and the transport equations of physical quantities on more or less important scales provide accurate predetermination in a relatively short time. This is what meteorologists do to deliver us every day their newsletter. This is what the same meteorologists are trying to do with scientists from all sides to build climate models in the long term, sure inaccurate today, exactly as was the 1960s weather model of Manabe, Nobel Prize in Physics 2021, the pioneer of general circulation modeling. The very first general circulation models were based on atmosphere-only physical models (Manabe et al., 1965, Nobel Prize in Physics, 2021), which were quickly improved to take into account the hydrologic cycle and its role in the general circulation of the atmosphere (Smagorinsky et al. 1965). From there, climate modeling has made considerable progress by gradually integrating the many positive or negative feedback processes that occur at different scales between the different components of the system: ocean circulation (Manabe and Bryan, 1969), land hydrological processes (Sellers et al., 1986), sea ice dynamics (Meehl and Washington, 1995), and aerosols (Takemura et al., 2000), biophysical and biogeochemical processes (Cox et al., 2000). Models with these latter components are often called Earth System Models (ESMs) and more recent such models include land and ocean carbon cycle, atmospheric chemistry, dynamic vegetation, and other biogeochemical cycles (Watanabe et al., 2011, Collins et al., 2011). It should be noted that as a whole and for the same reasons, the horns of ESMs, which are based on physical formulations similar to those employed in general circulation models applied in meteorology, have not evolved much, except for the increase in the resolution of the calculations made possible thanks to the increase in the computing capacity or their capacity to assimilate increasingly abundant and precise data; in particular global satellite data, which complements and connects measurements on the ground or at low altitude.

Manabe, S., Smagorinsky, J., & Strickler, R. F. (1965). Simulated climatology of a general circulation model with a hydrologic cycle. Monthly Weather Review, 93(12), 769-798.

Smagorinsky, S. Manabe, and J. L. Holloway, “Numericd Results From a Nine-Level General Circulation Model of the Atmosphere,” Monthly Weather Review, vol. 93, No. 12, Dec. 1965, pp. 727-768.

Manabe, S., & Bryan, K. (1969). Climate calculations with a combined ocean-atmosphere model. J. Atmos. Sci, 26(4), 786-789.

Sellers, P. J., Mintz, Y. C. S. Y., Sud, Y. E. A., & Dalcher, A. (1986). A simple biosphere model (SiB) for use within general circulation models. Journal of the atmospheric sciences, 43(6), 505-531.

Meehl, G. A., & Washington, W. M. (1995). Cloud albedo feedback and the super greenhouse effect in a global coupled GCM. Climate dynamics, 11(7), 399-411.

Takemura, T., Okamoto, H., Maruyama, Y., Numaguti, A., Higurashi, A., & Nakajima, T. (2000). Global three‐dimensional simulation of aerosol optical thickness distribution of various origins. Journal of Geophysical Research: Atmospheres, 105(D14), 17853-17873.

Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A., & Totterdell, I. J. (2000). Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature, 408(6809), 184-187.

Watanabe, S., Hajima, T., Sudo, K., Nagashima, T., Takemura, T., Okajima, H., ... & Kawamiya, M. (2011). MIROC-ESM 2010: Model description and basic results of CMIP5-20c3m experiments. Geoscientific Model Development, 4(4), 845-872.

Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran, P., Hinton, T., ... & Woodward, S. (2011). Development and evaluation of an Earth-System model–HadGEM2. Geoscientific Model Development, 4(4), 1051-1075.

See Also:

Besbes, M., & Chahed, J. (2023). Predictability of water resources with global climate models. Case of Northern Tunisia. Comptes Rendus. Géoscience, 355(S1), 1-22. Available on:Article Predictability of water resources with global climate models...

Findings of his research [1] "Three Gorges Dam: friend or foe of riverine greenhouse gases?" put into question some prejudices and should imply further deepening of the scientific community knowledge. "These findings suggest that ‘large-dam effects’ are far beyond our previous understanding spatiotemporally, which highlights the fundamental importance of whole-system budgeting of GHGs under the profound impacts of huge dams". The question remains what comprehensive environmental impacts of such huge changes of hydrologic systems on all the components of the earth system as well as on associated modification of population activities (agriculture, industries, production...)? Then what would be the impacts of these changes on the different budgets of GHE, water cycle, and other exchanges at the interfaces of the earth system?

[1] Ni, J., Wang, H., Ma, T., Huang, R., Ciais, P., Li, Z., ... & Borthwick, A. G. (2022). Three Gorges Dam: friend or foe of riverine greenhouse gases?. National Science Review, 9(6), nwac013: Available on:

https://academic.oup.com/nsr/article-pdf/9/6/nwac013/45053354/nwac013.pdf

See also:

https://www.researchgate.net/post/Climate_Change_Water_Resources/18

The paper [1] by Besbes et al.,2023, "Predictability of water resources with global climate models. Case of Northern Tunisia" analyzes the long-term effects of climate change using the predictions from CMIP6 on Northern Tunisia’s water resources, including blue and green water. The region represents the essential source of surface water, which gives it the qualifier “water tower” of Tunisia. It is also the cereal region of the country, mainly cultivated in rain-fed: it is its “attic”. Based on hydrological modeling, the analysis aims at determining the foreseeable climate-change effect on the overall water resources of the northern region of Tunisia.

[1] Besbes, M., & Chahed, J. (2023). Predictability of water resources with global climate models. Case of Northern Tunisia. Comptes Rendus. Géoscience, 355(S1), 1-22. Available on:

Article Predictability of water resources with global climate models...

See Also:

https://www.researchgate.net/post/Climate_Change_Water_Resources

https://www.researchgate.net/post/Climate_Change_and_Climate_Models_Progress_and_Limits

In these festive days, I would like to mention this 30 year old Paper, "Joy A. Palmer (1993) From Santa Claus to sustainability: emerging understanding of concepts and issues in environmental science, International Journal of Science Education, 15:5 , 487-495", in which the author discusses the nature and development of children's early knowledge and awareness of environmental issues. as strange as it may seem, we learn that "pre‐school children may well have a strong base of accurate scientific knowledge upon which early years environmental teaching may build." Happy Holidays For All

See Also:

https://www.researchgate.net/post/Adaptation_and_Resilience_to_Climate_Change_Temporal_Paradox_versus_Chronology_Protection_Conjecture