Soil moisture revamps the temperature extremes in a warming climate over India

Major land regions of the world have been exhibiting severe rise in temperature extremes (ExT) during the recent few decades. The Indian subcontinent has been highlighted as one of the hotspots for increased characteristics of ExT. Recent studies have projected that outbreak of high-intensity ExT is likely to become more common over India at the end of the 21st century. The Indian region generally experienced the extreme heat conditions during the pre-monsoon months of April-May-June, which may elongate into the summer monsoon season as well, due to prolonged deficiency of the monsoon rainfall. Furthermore, increase in ExT exerts serious impact on the ecosystem, human health, agriculture and economy. Understanding long-term changes in ExT over India in past and future climate has been an important topic of research. Observations indicate that occurrence of ExT over India is linked to large-scale atmospheric circulation anomalies and regional-scale land-atmosphere feedback processes arising from soil moisture (SM) variations. In particular, SM revamps the ExT by modulating the surface energy partitioning and evapotranspiration (ET). As a crucial component of land-atmosphere coupling processes, SM also acts as temporal storage of atmospheric anomalies. Additionally, the long-term persisting nature (memory) of SM has potential to induce a pronounce impact on near-surface temperature and precipitation (PR) variability. Therefore, it is very important to understand the regional-scale SM variability using observational datasets and model simulations to get better insight into land-atmosphere feedback processes associated with extreme temperature conditions. The influence of SM on ExT can be determined using the observational data products as well as state-of-the-art climate model sensitivity experiments initialized by perturbing SM. In review of the SM sensitivity experiments over the Indian landmass, researchers mostly explored SM-PR feedback mechanism using the model simulations. However, impact of SM perturbations on ExT over India is still unclear. Therefore, this study aims to investigate the impact of SM perturbations on ExT by using the Meteorological Research Institute (MRI) high-resolution (~60 km) atmospheric general circulation model (i.e. MRI-AGCM3.2) simulations for the historical period (1951–2010) and future projection (2051–2100).

Model: The study uses the Meteorological Research Institute atmospheric general circulation model MRI-AGCM3.2 (~60 km horizontal resolution, 64 vertical levels, 3 active soil layers) with the Simple Biosphere (SiB) land surface model. Lower boundary conditions include observed monthly SST and sea ice concentration from COBE-SST2 and prescribed climatological sea ice thickness. External forcings include observed greenhouse gases, ozone fields from MRI-CCM, and MRI-CGCM3 outputs. Experiments: Six long-term simulations were analyzed: (1) HIST (historical, 1951–2010), (2) HIST-20 (historical with −20% SM perturbation), (3) HIST+20 (historical with +20% SM perturbation), (4) FUT (future, 2051–2100, global mean +4 K relative to pre-industrial, consistent with RCP8.5 end-century), (5) FUT-20 (future with −20% SM perturbation), and (6) FUT+20 (future with +20% SM perturbation). For sensitivity runs, initial soil moisture in the top three layers (up to ~1–2 m depending on vegetation) was perturbed by ±20% at the start of each month, and the model integrated for one month repeatedly, using the same lateral boundary conditions as the corresponding control run. Bias correction and evaluation: Model hydro-meteorological outputs (precipitation, Tmax, SM, ET) were bias-corrected following Soriano et al. Taylor statistics against observations show improved performance for corrected variables over India: correlations 0.75–0.91, standard deviations 0.94–1.1 (relative to observed), and RMSD 0.45–0.65. Observational/data-assimilation products used include IMD gridded temperature and precipitation, GLDAS (ET, SHF, LHF), and high-resolution LDAS (~4 km) for SM. SM–temperature coupling: Coupling strength was quantified using Dirmeyer’s linear sensitivity metric: Ω = −Rc × σSM, where Rc is the regression slope of temperature anomalies on SM anomalies and σSM is SM standard deviation at each grid. This metric was computed for HIST and FUT and cross-validated with an alternative metric following Miralles et al. Extreme temperature indices: ExT events are defined when daily Tmax exceeds the 90th percentile (threshold computed from HIST) for at least 3 consecutive days. For FUT, the HIST 90th percentile threshold is used. Indices: ExTF (number of ExT events per year), ExTD (duration in days per event), and ExTI (yearly maximum Tmax). GEV analysis: Yearly block maxima (ExTI) were fit using stationary GEV and non-stationary GEV with SM as a covariate for the location parameter μ(y) = A0 + A1 y, where y is standardized annual mean SM. Return levels (e.g., 50-year) were estimated; significance and goodness-of-fit were assessed via likelihood-ratio tests. Negative shape parameters indicate Weibull behavior of ExTI. Soil moisture memory (SMM): SMM was quantified as the e-folding timescale λ at which the autocorrelation of SM anomalies decays to 1/e, using a 30-day lag autocorrelation and assuming exponential decay r(t) = exp(−t/λ). SMM diagnostics were computed for control and SM-perturbed experiments. Land–atmosphere process diagnostics: Changes in SM, Tmax, sensible heat flux (SHF), latent heat flux (LHF), ET, and SMM were analyzed to elucidate mechanisms by which SM perturbations alter ExT, focusing on the north-central India (NCI) strong coupling hotspot.

- Model evaluation: After bias correction, annual-mean PR, SM, ET, and Tmax over India show strong agreement with observations (correlations 0.75–0.91; normalized SD 0.94–1.1; RMSD 0.45–0.65). - SM–T coupling hotspot: Strong SM–temperature coupling is located over north-central India (NCI), with area of strong coupling likely expanding under +4 K future conditions. - Climatology and future change of ExT (MRI-AGCM3.2, bias-corrected): HIST shows ≥4 ExT events/year over much of India, average duration ~5–6 days/event, and maximum intensities up to ~47 °C over central India. Under FUT (+4 K), nearly 100% of Indian land shows increases: on average +~9 ExT events/year, +~5–6 days/event, and +~3 °C in ExTI relative to HIST. Over NCI, FUT projects ExTI > 50 °C occurring roughly every 25–30 days and persisting 10–12 days. - Impact of ±20% SM perturbations (India-wide): • HIST-20 (drier): ExTF increases by 4–5 events/year; ExTD by 1–2 days/event; long-term mean ExTI by at least ~0.6 °C. • HIST+20 (wetter): ExTF decreases by 1–2 events/year; ExTD by 2–3 days/event; long-term mean ExTI by ~0.5 °C. • FUT-20 (drier): ExTF increases by 1–2 events/year; ExTD by 0–1 days/event; long-term mean ExTI by ~1 °C. • FUT+20 (wetter): ExTF decreases by 3–4 events/year; ExTD by 3–4 days/event; long-term mean ExTI by ~2 °C. About 70% or more of India experiences significant changes in ExT characteristics in sensitivity runs. - NCI hotspot sensitivity (area-averaged): • HIST-20: ExTF +~5 events/year; ExTD +~1.8 days/event; ExTI +~0.71 °C relative to HIST. • HIST+20: ExTF −~3 events/year; ExTD −~1 day/event; ExTI −~1.88 °C relative to HIST. • FUT-20: ExTF +~2.2 events/year; ExTD +~1.55 days/event; ExTI +~0.93 °C relative to FUT. • FUT+20: ExTF −~3.3 events/year; ExTD −~2 days/event; ExTI −~2.02 °C relative to FUT. - GEV return levels over NCI: For HIST, the 50-year return level under dry SM is ~1.25 °C higher than under wet SM; dry SM raises 50-year ExTI up to ~48.75 °C versus wet below ~47.63 °C. For FUT, dry SM raises 50-year ExTI up to ~53.52 °C, wet SM keeps it below ~50.94 °C. - Mechanisms: In transitional/moderate SM regimes (not very wet or dry), SM changes strongly modulate ET and surface energy partitioning. A 20% SM decrease over NCI reduces ET by ~10% and increases SHF and Tmax; a 20% SM increase enhances ET by ~15%, lowers SHF, favors more clouds and atmospheric moisture, reduces incoming solar radiation, and cools near-surface air. SMM over NCI is ~3–4 weeks; −20% SM reduces SMM by ~1 week, while +20% SM increases SMM by <1 week. Drier SM reduces SMM, enhancing SHF and warming, thereby intensifying ExT. - Warming effect on SM impact: The modulation of ExT frequency and duration by SM perturbations becomes less prominent in FUT relative to HIST, linked to increases in precipitation and SM, reduced surface–air temperature gradients, lower Bowen ratio, and reduced SHF.

The study demonstrates that soil moisture substantially modulates temperature extremes over India, particularly over the north-central India (NCI) hotspot of strong SM–temperature coupling. SM perturbations alter ExT by reshaping surface energy partitioning (between sensible and latent heat), evapotranspiration, and soil moisture memory. Over moderate SM regimes such as NCI, a ±20% SM change yields large shifts in ExT frequency, duration, and intensity. While similar mechanisms operate in future +4 K climates, the relative impact of SM perturbations on ExT frequency and duration diminishes as background warming increases precipitation and SM, lowering the Bowen ratio and sensible heat flux. Extreme-value analysis confirms that drier SM states elevate rare-event intensities (higher return levels), whereas wetter SM states suppress them. Overall, the results highlight the critical role of land-surface hydrology in shaping heat extremes and how this role may evolve under climate change.

This work quantifies how soil moisture perturbations revamp temperature extremes across India using high-resolution AGCM experiments for historical and +4 K future climates. More than 70% of India shows significant sensitivity, with the strongest effects over the NCI coupling hotspot where ±20% SM changes alter ExT frequency by up to several events per year, duration by up to a few days per event, and intensity by up to a few degrees Celsius. Land–atmosphere feedbacks involving ET, surface energy partitioning, and soil moisture memory underpin these changes. Under future warming, SM’s modulation of ExT frequency and duration weakens relative to historical conditions due to a moister background state and reduced sensible heating. Potential future directions include multi-model assessments of SM–T coupling strength and ExT sensitivity, improved representation and observational constraints on soil moisture memory and land–atmosphere feedbacks, and deeper investigation of non-linear SMM behavior under wet perturbations and across weak-coupling regions.

- The results are based on a single climate model (MRI-AGCM3.2) and specific experimental design; impacts of soil moisture on extremes may vary across models depending on land–atmosphere coupling representation. - Despite bias correction and evaluation, notable model–observation differences exist regionally (e.g., Indo-Gangetic plains biases in PR/ET/SM and Tmax underestimation). - Non-linear behavior between SMM and wet SM perturbations over weak coupling zones requires further investigation. - Sensitivity experiments apply uniform ±20% SM perturbations and monthly re-initialization, which may not capture all real-world heterogeneity and memory pathways.