| 03 Sep 2026
A Post-1998 Transition from Water-Vapor to Joint Greenhouse Gas Forcing regime over Nigeria
Abstract. Anthro-forced climatic oscillations across the West African sub-region present severe challenges to regional ecological resilience, yet the fine-scale causal interactions governing localized thermal feedback loops remain elusive. This study bypasses traditional linear constraints by deploying a novel multivariate causality block network tracking architecture to evaluate multi-decadal surface air temperature (SAT) fluctuations across Nigeria. Utilizing a spatially continuous 44-year atmospheric profile from the NASA MERRA-2 reanalysis platform (1981–2024), this paper maps the evolving coupling between thermodynamic states and localized trace gas mixtures. The causality tracking identifies a profound, systemic regime shift structurally anchored to the historic 1998 climate tipping point. This transition is marked by a sharp SAT anomaly step-change, climbing from a pre-1998 baseline of −0.64 °C to a post-1998 mean of 0.16 °C, coupled with a 66 % expansion in internal thermal variance. While individual trace gas metrics yield weak standalone diagnostic correlations, masking their true impact, non-parametric distributional tracking confirms deep structural divergence across the two temporal eras (p < 0.001). Crucially, the multivariate network analysis uncovers a fundamental atmospheric paradigm shift: Nigeria's historical thermal baseline, once regulated by natural water-vapor feedbacks, has transitioned into a highly sensitive, multi-driver configuration. Forecast error variance decomposition demonstrates that contemporary Nigerian SAT shifts are now explicitly driven by a synergistic combination of internal chaotic atmospheric dynamics and joint greenhouse gas forcing. These findings uncover a localized thermodynamic vulnerability, providing an empirical basis for further investigation into the underlying climate mechanisms, spatial heterogeneity, and subcontinental patterns of climate sensitivity and adaptation.
MS No. egusphere-2026-4657: “A Post-1998 Transition from Water-Vapor to Joint Greenhouse Gas Forcing regime over Nigeria”
The authors have investigated long term surface air temperature (SAT) fluctuations across tropical regions of Nigeria, Africa using NASA MERRA-2 reanalysis data on atmospheric profile. They claim to have identified, in terms of sharp SAT anomaly, a prominent shift of radiative forcing regime from natural water-vapor feedback to multi-driver configuration of greenhouse gases (GHG) around the year 1998.
The work is based solely on open-source reanalysis data, and has no experimental resource, field work or satellite image analysis of its own. It lacks any robust theoretical framework or efficient analytic technique for compensating the limitation. It has several shortcomings in methodology and results. I do not recommend this manuscript for publication. In my opinion, at least the following issues must have been addressed before submitting anywhere.
(1) The theme of atmospheric paradigm shift just after a specific year (1998) is doubtful and illogical from a physical standpoint. In an actual atmosphere, such a sharp transition from water vapour feedback to joint GHG forcing cannot occur within a single year. It is possible that the abrupt change noted by the authors is only a data artifact. Although a severe El Nino took place during 1997-1998, that might have caused just a transient change, and not any perpetuating shift like that observed by the authors. Most probably they have misinterpreted the baseline shift of reanalysis model (due to the inclusion of new satellite sensors in 1998) as a new climate forcing regime. The authors must first confirm that the reported transition is truly a geophysical phenomenon by comparing it with independent ground truth (not another reanalysis), such as radiosonde or GNSS time series over decades.
(2) The methodology has procured separate time series data for various atmospheric parameters, namely water vapour (H2O), carbon dioxide (CO2), methane (CH4) and others, and has assumed simple linear summation in estimating anomaly [Eq. (1)], averaging [Eq. (2)], and regression [Eq. (5)] for all. This is not only oversimplification but incorrect. CO2, CH4 etc. are non-condensable, well-mixed trace gases whereas H2O is a condensable, temperature dependent entity that causes a rapid thermodynamic feedback mechanism thereby amplifying the initial forcing imposed by CO2 or CH4. The radiative forcing of CO2 has logarithmic scaling while that of CH4 has square root law. The total precipitable water vapour scales nonlinearly with localized surface temperature. Attempting to capture so many diversities in a linear sum of the same format is a fundamental flaw.
(3) The results section does not offer anything new. The violin-boxplots (Fig. 3) are nothing but the replication of whatever the reanalysis data yielded. There are, of course, some distribution shifts around the year 1998 but no strong causative factor is found there to correlate that shift to local GHG emissions.
Figs. 4, 5 and 6 are mere elementary presentations. When the x-variable spans 10-40 or 200-400, the y-variable spans only up to 1.5 or 2.5, and the plotted points get scattered throughout the whole graph, a linear fitting is meaningless. Please look for more efficient statistical techniques. Some faint separating trends of orange and blue points are sometimes noted visually. Nevertheless, proper evidence of a bias needs mathematical justification.
(4) The manuscript has used the word “thermodynamic” in a number of occasions but no physical thermodynamic transformation process, such as heat transfer, entropy change, or related radiative terms are adopted. Instead of getting confined to the statistics of gas concentration data alone, please translate each contribution to its radiative forcing and feedback factor component. Plotting the radiative forcing for water vapour alone and that for the joint anthropogenic forcing against time in the same graph would be more informative.
(5) The literature review should cite Raychaudhuri et al. [“Combined effects of … carbon dioxide and water vapour”, Remote Sensing Letters, 16, 1376-1387, 2025], which is quite relevant to the objective of the present work.