Assessing the impact of soil moisture-temperature coupling on temperature extremes over the Indian region

While previous model sensitivity studies have mainly focused on discerning the soil moisture-precipitation feedback processes over the Indian region, the present study investigates the impact of soil moisture-temperature (SM-T) coupling on the temperature extremes (ExT) using the high-resolution (~60 km) model simulations. These simulations include the control and soil moisture (SM) sensitivity experiments (DRY-SM and WET-SM) initialized by perturbing (decreasing/increasing) SM from the historical (HIST: 1951-2010) and future 4K warming (FUT: 2051-2100) control runs. The analysis identifies the transitional regions of north-central India (NCI) as the hotspot of strong SM-T coupling. Over NCI, the HIST experiment shows an occurrence of 4-5 extreme events per year, with an average duration of 5-6 days per event and intensity exceeding 46oC. Whereas, FUT estimates indicate relatively severe, long-lasting, and more frequent extreme events. The SM sensitivity experiments reveal the significant influence of SM-T coupling on the ExT over NCI in both historical and future climates. We find that the DRY-SM results in significant enhancement of frequency, duration and intensity of ExT, in contrast to WET-SM. We note that the difference between DRY-SM and WET-SM 50-year return value of the block maxima GEV fit can reach upto 1.25oC and 3oC for historical and future climate, respectively. The enhanced (reduced) extreme temperature conditions in DRY-SM (WET-SM) simulation are caused by the intensification (abridgement) of sensible heat flux by limiting (intensifying) available total energy for evaporative cooling due to faster (slower) dissipation of positive soil moisture anomalies (also called as soil moisture memory). In addition, the influence of SM on ExT over NCI is found to be larger during the post-monsoon season as compared to the pre-monsoon and monsoon seasons.Comment: 60 pages, 13 figure

The Indian COSMOS Network (ICON): validating L-band remote sensing and modelled soil moisture data products

Availability of global satellite based Soil Moisture (SM) data has promoted the emergence of many applications in climate studies, agricultural water resource management and hydrology. In this context, validation of the global data set is of substance. Remote sensing measurements which are representative of an area covering 100 m2 to tens of km2 rarely match with in situ SM measurements at point scale due to scale difference. In this paper we present the new Indian Cosmic Ray Network (ICON) and compare it’s data with remotely sensed SM at different depths. ICON is the first network in India of the kind. It is operational since 2016 and consist of seven sites equipped with the COSMOS instrument. This instrument is based on the Cosmic Ray Neutron Probe (CRNP) technique which uses non-invasive neutron counts as a measure of soil moisture. It provides in situ measurements over an area with a radius of 150–250 m. This intermediate scale soil moisture is of interest for the validation of satellite SM. We compare the COSMOS derived soil moisture to surface soil moisture (SSM) and root zone soil moisture (RZSM) derived from SMOS, SMAP and GLDAS_Noah. The comparison with surface soil moisture products yield that the SMAP_L4_SSM showed best performance over all the sites with correlation (R) values ranging from 0.76 to 0.90. RZSM on the other hand from all products showed lesser performances. RZSM for GLDAS and SMAP_L4 products show that the results are better for the top layer R = 0.75 to 0.89 and 0.75 to 0.90 respectively than the deeper layers R = 0.26 to 0.92 and 0.6 to 0.8 respectively in all sites in India. The ICON network will be a useful tool for the calibration and validation activities for future SM missions like the NASA-ISRO Synthetic Aperture Radar (NISAR)

Cosmic-ray soil water monitoring: the development, status & potential of the COSMOS-India network

Soil moisture (SM) plays a central role in the hydrological cycle and surface energy balance and represents an important control on a range of land surface processes. Knowledge of the spatial and temporal dynamics of SM is important for applications ranging from numerical weather and climate predictions, the calibration and validation of remotely sensed data products, as well as water resources, flood and drought forecasting, agronomy and predictions of greenhouse gas fluxes. Since 2015, the Centre for Ecology and Ecology has been working in partnership with several Indian Research Institutes to develop COSMOS-India, a new network of SM monitoring stations that employ cosmic-ray soil moisture sensors (CRS) to deliver high temporal frequency, near-real time observations of SM at field scale. CRS provide continuous observations of near-surface (top 0.1 to 0.2 m) soil volumetric water content (VWC; m3 m-3) that are representative of a large footprint area (approximately 200 m in radius). To date, seven COSMOS-India sites have been installed and are operational at a range of locations that are characterised by differences in climate, soil type and land management. In this presentation, the development, current status and future potential of the COSMOS-India network will be discussed. Key results from the COSMOS-India network will be presented and analysed

A study of field-scale soil moisture variability using the COsmic-ray Soil Moisture Observing System (COSMOS) at IITM Pune site

This study presents an analysis of daily field-scale soil-moisture (SM) variations, measured using the COsmic-ray Soil Moisture Observing System (COSMOS), over a tropical monsoon site (IITM, Pune) in India, for the period 2017–2020. Being located in the core zone of the Indian summer monsoon, the daily field-scale SM observations at COSMOS-IITM provide an unique opportunity to understand the SM response to monsoon precipitation variations on sub-seasonal, seasonal and interannual time-scales. In addition to the COSMOS-IITM observations, we also evaluated SM variations over this location using satellite, reanalysis and model products for the same period. An important result from our analysis reveals the presence of biweekly (time-scale ~ 10–20 days) and low-frequency intra-seasonal (time-scale ~ 30–60 days) variations in the field-scale SM, which are linked to the dominant modes of Indian summer monsoon subseasonal variability. In particular, we find a pronounced enhancement of the low-frequency signal of SM variations during the 2019 monsoon which was characterized by abnormally excess precipitation and prolongation of rains well beyond the summer monsoon season, in contrast to 2018 monsoon. Moreover, this study highlights a longer persistence of SM memory time-scale (about 60 days) during 2019 as compared to 2017, 2018 and 2020. The validation of coarser resolution data sets revealed that GLDAS and ERA5 reasonably capture a range of observed field-scale SM variabilities over COSMOS-IITM site

Understanding the soil water dynamics during excess and deficit rainfall conditions over the core monsoon zone of India

Observations of soil moisture (SM) during excess and deficit monsoon seasons between 2000 to 2021 present a unique opportunity to understand the soil water dynamics (SWD) over core monsoon zone (CMZ) of India. This study aims to analyse SWD by investigating the SM variability, SM memory (SMM), and the coupling between surface and subsurface SM levels. Particularly intriguing are instances of concurrent monsoonal extremes, which give rise to complex SWD patterns. Usually, it is noted that a depleted convective activity and persistence of higher temperatures during the pre-monsoon season leads to lower SM, while monsoon rains and post-monsoon showers support the prevalence of higher SM conditions. The long persistent dry spells during deficit monsoon years enhances the Bowen ratio (BR) due to the high sensible heat fluxes. On the other hand, the availability of large latent heat flux during excess monsoon and post-monsoon seasons tend to decrease the BR. This enhancement or reduction in BR is due to evapotranspiration (ET), which influences the SWD by modulating the surface—subsurface SM coupling. The surface and subsurface SM coupling analysis for CMZ exhibits significant distinction in the evolution of wet and dry extremes. SM variations and persistence time scale is used as an indicator of SMM, and analysed for both surface and subsurface SM observation levels. Evidently, subsurface SM exhibits remarkably prolonged memory timescales, approximately twice that of surface SM. Furthermore, we dissect SWD linked to wet and dry extremes by analysing annual soil water balance at a local site in Pune, India. Our findings reveal that ET and deep drainage on annual scale are modulated largely by number of break events during the monsoon season. In essence, our study underscores the significance of surface–subsurface SM observations in unravelling the intricate tapestry of SWD