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)

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