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	<title>climate change effects in South India &#8211; Science</title>
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	<title>climate change effects in South India &#8211; Science</title>
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		<title>Atmospheric Thirst in Tamil Nadu Shifts in Abrupt Regimes, Not Slow Trends</title>
		<link>https://scienmag.com/atmospheric-thirst-in-tamil-nadu-shifts-in-abrupt-regimes-not-slow-trends/</link>
		
		<dc:creator><![CDATA[Russell Cooper]]></dc:creator>
		<pubDate>Wed, 23 Sep 2026 21:16:30 +0000</pubDate>
				<category><![CDATA[Earth Science]]></category>
		<category><![CDATA[abrupt regime shifts in climate]]></category>
		<category><![CDATA[Atmospheric evapotranspiration in Tamil Nadu]]></category>
		<category><![CDATA[climate change effects in South India]]></category>
		<category><![CDATA[climate variability and drought onset]]></category>
		<category><![CDATA[climatic water balance]]></category>
		<category><![CDATA[drought]]></category>
		<category><![CDATA[ET0]]></category>
		<category><![CDATA[evaporative demand]]></category>
		<category><![CDATA[hydro-meteorological record analysis]]></category>
		<category><![CDATA[impacts of evapotranspiration on land-atmosphere moisture exchange]]></category>
		<category><![CDATA[influence of atmospheric demand on water resources]]></category>
		<category><![CDATA[Mann–Kendall trend analysis]]></category>
		<category><![CDATA[NASA POWER]]></category>
		<category><![CDATA[Pettitt test]]></category>
		<category><![CDATA[reference evapotranspiration]]></category>
		<category><![CDATA[regime shift]]></category>
		<category><![CDATA[SARIMA forecasting]]></category>
		<category><![CDATA[semi-arid climate]]></category>
		<category><![CDATA[semi-arid region water management]]></category>
		<category><![CDATA[spatial heterogeneity of ET0]]></category>
		<category><![CDATA[Tamil Nadu]]></category>
		<category><![CDATA[temporal non-stationarity in climate data]]></category>
		<category><![CDATA[water budget and drought prediction]]></category>
		<category><![CDATA[water stress and drought risk assessment]]></category>
		<guid isPermaLink="false">https://scienmag.com/?p=210381</guid>

					<description><![CDATA[A four-decade analysis of Tamil Nadu's hydro-meteorological records reveals that atmospheric evaporative demand shifts abruptly between regimes rather than following smooth trends, reshaping how drought risk and water balance should be predicted in semi-arid India.]]></description>
										<content:encoded><![CDATA[<p>In the semi-arid expanses of Tamil Nadu, southern India, the single most consequential number in the water budget may not be rainfall at all. It is reference evapotranspiration, or ET0, the amount of water the atmosphere tries to pull out of the land surface when supply is unlimited. A new study published in Theoretical and Applied Climatology argues that this atmospheric demand, often treated as a slowly drifting background quantity, actually behaves in a far more restless and structured way. Researchers Mohanaashri V, Ramyachitra D and Geetha K of the Department of Computer Science at Bharathiar University in Coimbatore analysed nearly four decades of hydro-meteorological records and found that ET0 across Tamil Nadu is marked by spatial heterogeneity, temporal non-stationarity and abrupt regime shifts, properties that carry direct consequences for drought prediction and water management in one of India&#8217;s most water-stressed states.</p>
<p>Atmospheric evaporative demand sits at the hinge of the terrestrial water balance. It governs the moisture exchange between land and air, determines how much of a given rainfall episode is lost back to the sky, and in water-limited regions it is tightly coupled to the onset and intensification of drought. When demand rises faster than supply, soils dry, reservoirs shrink and vegetation stress compounds even if precipitation itself does not collapse. Yet despite this central role, the multi-decadal behaviour of ET0 and its structural changes have remained poorly characterised, particularly in semi-arid regions where the question of whether atmospheric conditions are statistically associated with their impact on water balance variability has not been systematically answered. The Tamil Nadu study set out to close that gap by examining long-term hydroclimatological behaviour through four lenses: spatial heterogeneity, temporal non-stationarity, atmospheric control and impacts on the climatic water balance across contrasting hydro-climatic regimes.</p>
<p>The evidence base was drawn from the NASA POWER database, a publicly accessible satellite-derived and modelled meteorological record that provided temperature, relative humidity, solar radiation, wind speed and precipitation for the period 1985 to 2024. Rather than relying on a single station, the researchers selected representative stations spanning the diverse hydro-climatic regimes of Tamil Nadu, from the wetter coastal and western zones to the drier interior plains. This design matters because a state-level average can easily mask the fact that neighbouring districts may be drifting in opposite directions. By treating each regime on its own terms, the analysis could reveal whether the drivers of evaporative demand behave uniformly or whether their dominance changes with the local climate setting.</p>
<p>Methodologically, the study leaned on a battery of robust non-parametric techniques chosen for their resilience to outliers and to the non-normal distributions typical of hydro-climatic data. Trend detection used the Mann–Kendall test paired with Sen&#8217;s slope estimator, a combination that has become a standard for identifying monotonic change in environmental series. The pivotal innovation, however, was the Pettitt test for regime shift analysis, which searches for a single abrupt change point in a time series rather than assuming gradual change. Extreme event analysis characterised the behaviour of ET0 at the tails of the distribution, where agricultural stress concentrates, and a SARIMA model, a seasonal autoregressive integrated moving average framework, was used to forecast short-term ET0 dynamics. Finally, a driver dominance analysis quantified the relative contribution of individual atmospheric factors to ET0 variability, allowing the team to rank the controls rather than merely list correlations.</p>
<p>The headline finding is that ET0 in Tamil Nadu does not follow a simple, monotonic trajectory. Instead, the records show statistically significant regime changes, meaning that the series jumps between quasi-stable states with different mean levels and different atmospheric controls. The interaction between temperature, radiation and humidity emerges as the governing mechanism, and the balance of power among these three variables shifts from one hydro-climatic regime to another. In practical terms, this means that a warming trend does not translate into a uniform increase in atmospheric thirst everywhere. Where humidity is high, rising temperatures may be partially offset by the suppression of evaporation; where the air is already dry, the same warming can push demand sharply upward. The study&#8217;s driver dominance analysis makes this regime dependence explicit, showing that the atmospheric control on ET0 varies systematically under different hydro-climatic conditions.</p>
<p>Extreme ET0 behaviour and the response of the climatic water balance also diverged across regimes, a pattern the authors interpret as the spatial fingerprint of climatic water stress. In the drier interior, where rainfall is marginal and evaporative demand is chronically high, shifts in ET0 translate almost directly into deeper water deficits, because there is little buffer between supply and demand. In wetter zones, the same shifts may be absorbed by soil moisture and surface storage, at least temporarily. This asymmetry has a sobering implication: identical large-scale climate signals can produce radically different drought outcomes depending on where they land. Water planners who rely on state-wide or basin-wide averages risk misjudging both the severity and the geography of emerging stress.</p>
<p>Perhaps the most consequential conclusion of the paper is a methodological warning. Atmospheric evaporative demand, the authors argue, cannot be understood on the basis of monotonic trends alone, because its spatial heterogeneity, temporal non-stationarity and regime dependence violate the assumptions underlying simple trend analysis. A Mann–Kendall test applied to a series that has jumped between two regimes may report a significant trend that is really an artefact of a step change, or conversely may miss genuine change that is concentrated in a short transition. For predictability, this reframing is critical. Forecast systems and drought early-warning schemes that extrapolate a linear trend will systematically misjudge the future if the underlying process is one of regime dynamics. Recognising the regime structure, by contrast, opens the door to forecasts conditioned on the current state, which is precisely what the SARIMA component of the study begins to explore for short-term ET0 dynamics.</p>
<p>The findings arrive amid a broader scientific reassessment of global evaporative demand. Recent work has documented that climate change has increased evaporative demand across most of the planet, with South Asia standing out as a notable exception in some global assessments, and researchers have begun naming prolonged episodes of extreme atmospheric demand, such as so-called thirstwaves, as a distinct class of agricultural hazard. The Tamil Nadu results add regional texture to this global picture, showing that even within a single Indian state the trajectory of atmospheric thirst is not uniform. They also echo a long-standing puzzle in hydrology, the so-called evaporation paradox, in which observed pan evaporation can decline even as temperatures rise, a reminder that humidity, radiation and wind interact with temperature in ways that defy single-variable intuition.</p>
<p>For a state where agriculture consumes the bulk of freshwater and where monsoon failures routinely trigger drinking-water emergencies, the practical stakes are considerable. Knowing which atmospheric variable dominates ET0 in each regime tells irrigation authorities what to watch: humidity and radiation in some zones, temperature in others. Knowing that regimes shift abruptly rather than drift smoothly suggests that water budgets should be revised at detected change points rather than on fixed assumptions. The availability of the underlying NASA POWER data, covering 1985 to 2024, and of the processed analytical outputs on reasonable request from the corresponding author, means the framework can be replicated and extended to other semi-arid regions facing similar questions. The research was supported by the Tamil Nadu Chief Minister&#8217;s Research Grant, reflecting state-level interest in the predictability problem.</p>
<p>Ultimately, the study reframes atmospheric evaporative demand from a passive consequence of warming into an active, regime-governed component of the climate system with its own predictability structure. In semi-arid Tamil Nadu, the atmosphere&#8217;s thirst arrives in steps, not slopes, and each step rewrites the local water balance in a different way. Capturing that step-like behaviour, the authors contend, is the key to anticipating drought before it takes hold, and to managing a water future in which the demand side of the equation may change faster than the supply side ever will.</p>
<p><strong>Subject of Research:</strong> Multi-decadal variability and regime shifts in atmospheric evaporative demand and climatic water balance in Tamil Nadu, India</p>
<p><strong>Article Title:</strong> Multi-decadal variability and regime dynamics of atmosphere evaporative demand and climatic water balance in Tamil Nadu, India: implications for predictability</p>
<p><strong>Article References:</strong> Multi-decadal variability and regime dynamics of atmosphere evaporative demand and climatic water balance in Tamil Nadu, India: implications for predictability. (n.d.). <a href="https://doi.org/10.1007/s00704-026-06592-2" rel="noopener noreferrer">https://doi.org/10.1007/s00704-026-06592-2</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.1007/s00704-026-06592-2" rel="noopener noreferrer">10.1007/s00704-026-06592-2</a></p>
<p><strong>Keywords:</strong> evaporative demand, reference evapotranspiration, ET0, Tamil Nadu, drought, regime shift, Pettitt test, Mann-Kendall trend analysis, SARIMA forecasting, climatic water balance, semi-arid climate, NASA POWER</p>
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