Observed, Simulated and Projected Extreme Climate Indices over Pakistan
(Sprache: Englisch)
This research explores observed, simulated, and projected extreme climate indices from a selection of different GCMs from CMIP5 ensemble for Pakistan at province level. The extreme indices for observed, simulated and projected climate are found and analysed...
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This research explores observed, simulated, and projected extreme climate indices from a selection of different GCMs from CMIP5 ensemble for Pakistan at province level. The extreme indices for observed, simulated and projected climate are found and analysed on provincial basis over the country.Pakistan has been facing shortages in both the power and water sector which are the lifelines of the country. Significant increases in the maximum and minimum temperatures over the country may affect such sectors drastically. Considerable increase in the frequency and intensity of extreme weather events, coupled with erratic monsoon rains may cause frequent and intense floods and droughts in the region. Rising temperatures resulting in enhanced heat and water-stressed conditions, particularly in arid and semi-arid regions, may lead to reduced agricultural productivity. This report shall bring added value to all stakeholders and policy makers in determining the hazards that extreme climate has brought in the past and may bring in the near future.
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Text Sample:Chapter 3: VERIFICATION OF GCMS AND RCMS:
GCMs are known to have coarse horizontal resolutions with feedback and simulation biases. RCMs, on the other hand, are more sophisticated and have high horizontal resolutions, yet are not free from biases since both regional downscaling simulation and the parent driving GCM induce spatial and temporal biases (see e.g., Burhan et al., 2014). For the purpose of projecting robust climate change extremes and to have high confidence in the results, model selection is made by gauging ist ability to emulate observed climatology both for temperature and precipitation. Moreover, Taylor diagrams for GCMs and RCMs are made to obtain a concise statistical summary of how well the simulated climatology match the observed climatology in terms of their correlation, their root-mean-square difference and the ratio of their variances (Taylor, 2001).
3.1 GCMS EMULATING OBSERVED CLIMATOLOGY:
Area averaged mean annual maximum and minimum temperatures, and area averaged total annual rainfall is extracted from the 7 GCMs and put to comparison with the observed climatology of maximum and minimum temperature, and rainfall. Province based climatologies are constructed [...]. It is seen that in all provinces, maximum and minimum temperature climatologies are well represented by all GCMs except for Had-GEM2-AO (which is not in fact the actual Hadley center simulated model, but ist modeling center is NIMR, South Korea). In terms of precipitation, generally models tend to have high scatter, so the precipitation results for GCMs thereafter tend to remain in low confidence.
3.1.1 GCMs emulating observed climatology over Baluchistan:
In terms of rainfall in Baluchistan, quite haphazard climatological patterns displayed by different GCMs suggests that the coarse resolution of the GCMs are unable to resolve rugged terrain and barren climate of the province. However, CCSM4 to some extent is able to capture the peaks of annual rainfall cycle,
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yet with considerable wet biases yielding over-estimated results for the past climate of the province. In Baluchistan province, GCMs correlate well (95-99%), root-mean-square difference is small (less than 0.5 units), and the models lie within }0.5 standard deviation of the observed maximum and minimum temperatures. Nevertheless, no good correlation is seen to be established between any of the models representing precipitation statistics of the Baluchistan province [...].
3.1.2 GCMs emulating observed climatology over GB-AJK:
Both maximum and minimum temperatures in GB-AJK are well represented by simulated GCMs climatologies, however, with considerable cold biases. Moreover, GCMs tend to pick up the winter (DJFM) precipitation climatological cycle comparatively better than that in the summer (JJAS), yet, once again, with huge biases in the province. CCSM4 is seen as better representing the annual precipitation cycle, as compared to the rest of the models. In GB-AJK, all the models except HadGEM2-AO are giving 95-99% correlation with the observed in terms of maximum temperature. All the models except HadGEM2-AO are within the half root mean square difference, as well as within the +0.5 standard deviation of the observed maximum temperature. Same results hold for the minimum temperature in GB-AJK. In terms of precipitation, there is both large variability and error, along with weak correlations (some models even giving negative correlations) in the GB-AJK Province. CCSM4 gives a comparatively better estimation with 60% correlation, however, both the root-mean-square difference and the ratio of the variances tends to remain on the higher side.
3.1.3 GCMs emulating observed climatology over KPK:
Summer (JJAS) maximum and minimum temperature in KPK is better resolved as compared to that in the winter (DJFM) by GCMs. Precipitation climatologies represented by GCMs are poorly resolved for summer (JJAS) and partially better resolved in winters (DJFM), however, with both
3.1.2 GCMs emulating observed climatology over GB-AJK:
Both maximum and minimum temperatures in GB-AJK are well represented by simulated GCMs climatologies, however, with considerable cold biases. Moreover, GCMs tend to pick up the winter (DJFM) precipitation climatological cycle comparatively better than that in the summer (JJAS), yet, once again, with huge biases in the province. CCSM4 is seen as better representing the annual precipitation cycle, as compared to the rest of the models. In GB-AJK, all the models except HadGEM2-AO are giving 95-99% correlation with the observed in terms of maximum temperature. All the models except HadGEM2-AO are within the half root mean square difference, as well as within the +0.5 standard deviation of the observed maximum temperature. Same results hold for the minimum temperature in GB-AJK. In terms of precipitation, there is both large variability and error, along with weak correlations (some models even giving negative correlations) in the GB-AJK Province. CCSM4 gives a comparatively better estimation with 60% correlation, however, both the root-mean-square difference and the ratio of the variances tends to remain on the higher side.
3.1.3 GCMs emulating observed climatology over KPK:
Summer (JJAS) maximum and minimum temperature in KPK is better resolved as compared to that in the winter (DJFM) by GCMs. Precipitation climatologies represented by GCMs are poorly resolved for summer (JJAS) and partially better resolved in winters (DJFM), however, with both
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Bibliographische Angaben
- Autoren: Burhan Ahmad , Shahid Mahmood
- 2017, 102 Seiten, 35 Abbildungen, Masse: 19 x 27 cm, Kartoniert (TB), Englisch
- Verlag: Anchor Academic Publishing
- ISBN-10: 3960671725
- ISBN-13: 9783960671725
- Erscheinungsdatum: 01.09.2017
Sprache:
Englisch
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