I have seen in some discussion forums that climate projection models do not reliably reproduce twister phenomena. How can climate modeling overcome this challenge ?
Some recent papers indicating that we understand little how climate change affects tornadoes:
1. Article Future Global Convective Environments in CMIP6 Models
2. Article Anthropogenic Influences on Tornadic Storms
Even where tornado trends are demonstrable, attribution to climate change has not been definitely possible:
3. Article Explaining the trends and variability in the United States t...
4. Article Increasingly Powerful Tornadoes in the United States
By closely examining the outputs of the IPCC models, we find that the proposed scenarios do not lead to "one immutable conclusion" but to "several possible conclusions" which are sometimes so different that they can lead to amalgamation and confusion, especially when they fall between the hands of sorcerer's apprentices. In this respect,one may invoke Decartes's passage from the first meditation "but what! they are" ..... "models"! Do we have, for all that, the "truth" today? or at least "immutable conclusions"? Because:
1. if we have the "truth" we would not speak about "models"
2. if the "truth" is unique, we would not use several models and make a compilation.
3. if the "truth" is immutable, we would not have had recourse to hypotheses that result in several scenarios predicting different futures
Hi,
Global climate models are way too much coarse in resolution to capture such local phenomenon and the regional climate models which are reasonably high-resolution in nature, are not scientifically correct as the input is inter(extra)polated. If the input is dubious, how do we think that the output is correct? On top of it, you are in the discussion on local phenomenon.
As long as the research community steer away from ineffective data (obtained from different sources (e.g., satellites, station, etc.)) assimilation techniques and put effort in making the numerical models more scientific, nothing is going to happen and I don't see that the research community has that flexibility in thinking.
Data assimilation is ineffective because the data obtained is not at the exact location you are calculating in the numerical model so you are essentially inter(extra)polating, it's again red-flag, and even it is at the exact grid-point, it's extremely small part compared to the number of grid-points we consider in the numerical simulations.
Thanks for your contribution on my question Kishore Ragi Jamel Chahed Ilan Kelman
I believe that climate models have limitations like many models from other scintific areas (geomorphology for example). Twister are phenomena that have a very limited location and occurrence in space and time. Thus, the climate models may have difficulty reproducing these phenomena.
However, we must continue methodologically advancing to overcome this challenge.
You have outlined an alarming new phenomenon that everyone hopes it does not happen near them, thus avoiding any discussion about it.
However, you have noticed that it is happening everywhere on the planet today, while previously it mostly occurred along the "twister corridor" in Central USA.
It has spread far and wide, also increasing its intensity and killing many more people than it did before.
Meteorologists in the USA have been able to predict successfully and give warnings, but sometimes hurricanes take place at night and you can't see it coming.
Lots of research can be done on this subject: When can we expect one, how is it generated and what conditions lead to the formation of one. All these are incompletely known today.
Looking at the outputs of the IPCC models, one may invoke Decartes's passage from the first meditation "but what! they are" ..... "models"!
Graph: Synthesis of near-term projections of global mean surface air temperature (GMST). (a) Simulations and projections of annual mean GMST 1986–2050 (anomalies relative to 1986–2005). Projections under all RCPs from CMIP5 models (grey and coloured lines, one ensemble member per model), with four observational estimates (Hadley Centre/Climate Research Unit gridded surface temperature data set 4 (HadCRUT4): Morice et al., 2012); European Centre for Medium-range Weather Forecast (ECMWF) interim reanalysis of the global atmosphere and surface conditions (ERA-Interim): Simmons et al., 2010); Goddard Institute of Space Studies Surface Temperature Analysis (GISTEMP): Hansen et al., 2010); National Oceanic and Atmospheric Administration (NOAA): Smith et al., 2008)) for the period 1986–2012 (black lines).
Source: Kirtman, B., S.B. Power, J.A. Adedoyin, G.J. Boer, R. Bojariu, I. Camilloni, F.J. Doblas-Reyes, A.M. Fiore, M. Kimoto, G.A. Meehl, M. Prather, A. Sarr, C. Schär, R. Sutton, G.J. van Oldenborgh, G. Vecchi and H.J. Wang, 2013: Near-term Climate Change: Projections and Predictability. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
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