Despite the intense research on the tropical climate and its features, primarily the Intertropical Convergence Zone (ITCZ), fewer studies investigated the state of the ITCZ through an objective and automated algorithm, particularly the double ITCZ. The study combines the European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) variables, Global Precipitation ClimatologyProject (GPCP), and TRMM (TMPA 3B42 Daily) datasets to objectively and automatically identify the zonally elongated convergence regions (i.e. ITCZs) in the Pacific and provide 42 years climatologies. The algorithm utilises layer- and time-averaged winds in the lower troposphere (pressure levels between 1000 and 850 hPa) to obtain characteristics of ITCZs that include centre latitude, boundaries, widths, and additionally precipitation intensities using GPCP and TRMM datasets. The Northern Hemisphere (NH) ITCZs are found near 8° N, while the Southern Hemisphere (SH) ITCZs are near5° S. On the one hand, these results suggest that the NH ITCZs reach their northernmost centre latitude and the highest centre precipitation intensity in September and their southernmost in March; the full width peaks in August. On the other hand, the SH ITCZs start near the equator and migrate to reach the southernmost latitude in May. During their seasonal migration, the widths fluctuate with decreasing intensities. Generally, as found by previous studies, the NH ITCZs shift equatorward, narrow and intensify. The SH ITZCs shift poleward, narrow, and intensify under global warming.
<p>The Intertropical Convergence Zone (ITCZ) is recognised as the most crucial feature of the tropical climate producing more than 30% of the global precipitation. Its variability dramatically affects the people living in tropical areas. In the eastern Pacific, a pair of ITCZ, one at each side of the equator, during the boreal spring is evident. It is known as the Double Intertropical Convergence Zone (DITCZ). Generally, the ITCZ in the Pacific is located in the Northern Hemisphere (NH); however, during extreme El Ni&#241;o events, it can cross the equator, or a wide band of deep convection extending over both hemispheres is to be observed. The DITCZ exists more frequently and with much more strength in General Circulation Models (GCMs), resulting in a spurious bias. The DITCZ bias has been a long-standing tropical bias in climate model simulations since the early beginning. Despite the intense research on the tropical climate and its features, fewer studies investigated the state of the ITCZs through an objective and automated algorithm. Also, much fewer studies have applied such an algorithm to the GCMs output. Unfortunately, far too little attention has been paid to examining how DITCZ bias is transmitted to Regional Climate Models (RCMs). Furthermore, the input variables to the RCM from GCM are prognostic such as wind, temperature and humidity. Since precipitation is not an input, it would be interesting to examine how the representation of ITCZs in the GCMs is unfolded in the RCMs. The method adopted in this study depends on an objective and automated algorithm developed and modified by earlier studies. The algorithm uses layer- and time-averaged winds in the lower troposphere (seven layers between 1000 and 850 hPa), in addition to wet-blub potential temperature, to automatically detect the centre latitude of the ITCZs. Furthermore, it uses GPCP or CMIP5 model precipitation to obtain the extents (i.e. boundaries) of the ITCZs and the precipitation intensities. From reanalysis datasets, the NH ITCZs are found near 8&#176;N, while the Southern Hemisphere (SH) ITCZs are near 5&#176;S. In CMIP5 models, the DITCZ is much stronger and more frequent, and it occurs year-round. Generally, the NH ITCZs are located between 8&#176;N and 10&#176;N while the SH ITCZs are located between 5&#176;S and 10&#176;S. Moreover, models overestimate the tropical precipitation mainly, the centre and full ITCZ intensities. Furthermore, it indicates more vigorous convection in the NH ITCZs than in the SH ITCZs. The study also found that the state of ITCZ in GCMs directly influences the bias in RCM monthly precipitation. However, it depends mainly on the RCM employed. The most affected nations by DITCZ bias are Ecuador and Peru. Quantitative in-depth analysis of precipitation of GCMs and RCMs is still <span>on</span>going.</p>
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