Ramdas layer and thermal wave during winter period

Earlier works on Ramdas Layer were about its certainty, its existence, energy balance on the layer and a matching mathematical model. We, first identified it in Thiruvananthapuram, Kerala, for eight days during a fortnight study on soil heat flux. A lifted minimum in temperature could have implications in agriculture and horticulture and so with a view to finding out a range of height through which Ramdas layer occurs, Ramdas-max, Ramdas-min are identified. On 24 January 1994, Ramdas layer occurred at a maximum height of 0.8m from the surface and the day is labeled as Ramdas-max. On 1 February 1994, it occurred at a lower height of 0.4m from the surface and the day is labeled as Ramdas-min. The thermal wave at the ground and at 0.05m depth, the range of thermal wave, its relationship with Ramdas layer, the temperature profile, the rate of change of heat in that layer with that at the surface and the subsoil heat flux at the sub-soil surface stratum(surface-0.05m) during R~mdas-max and Ramdas-min are duly compared and discussed.

Characteristics of radiative and non-radiative energy fluxes over monsoon trough zone

In order to describe behaviour of radiative and non-radiative erergy fluxes in the surface layer, computation of net radiation, sensible, latent and heat soil flux has been done using hourly global radiation, slow response data of MONTBLEX-90 and surface observation of Varanasi and Jodhpur during rainy and non-rainy days in July 1990. Daily and hourly ground temperature is calculated solving one dimensional heat conduction equation and soil heat flux is computed using force restored method .Outgoing Longwave Radiation (OLR) is calculated by Stefan-Boltzrnann law of radiation and the largest diurnal variability was found over dry convective zone. Results show that OLR from the ground lies in the range 473.0-537.6 Wm-2 at Jodhpur and 497.4 -548.4 Wm-2 at Varanasi during generally cloudy day. The dip in OLR is increascd by 10% with increase of relative humidity and cloudiness. Daily mean of the largest downward soil heat flux are found as 206.4 and 269.4 Wm-2 at Varanasi and Jodhpur respectively during cloudy day. About 40-50% of net radiation is imparted to soil heat flux at Varanasi and Jodhpur. Sum of the hourly non- radiative energy fluxes has not been balanced by net radiation while daily cumulative value of the fluxes balances the net radiation during non-rainy day.

A six level automatic soil temperature measuring system

An automatic soil temperature measuring equipment is developed using four terminal thermistors. The output voltages from the six levels, i.e., 10 cm above soil surface, soil surface and 10 cm, 20 cm, 30 cm and 60 cm below the soil surface, are amplified and their multiplexed output is recorded on a chart recorder. The equipment is tested in the field and continuous observations are taken during May 1991. Temperature profiles for different hours of the day are plotted and diurnal variations of all levels are also discussed. An attempt is made to evaluate the damping depth and thence the thermal conductivity and soil heat flux.

Sub-soil temperature variation and estimation of soil heat flux at Pune

Utilising experimental data from 23 November to 8.December 1989. temperature and heat storage variations at Pune have been studied, based on 3 hourly observations.. pattern of penetration of .thermal wave within the soil has been examined and time of occurrence of maximum/minimum temperatures discussed for various depths. Temperature ranges in different layers have been theoretically computed and compared with those based on actual observations. Heat balance at various depths has also been presented and discussed.

Energy balance at the land-surface interface

A small scale field experiment was conducted at the Indian Institute of Tropical Meteorology (IITM). Pashan Pune and the energy budget at the land surface interface was studied for clear and cloudy days over bare soil. Using instrumented towers, a net radiometer and soil temperature probe all the components of the energy budget. i.e. the sensible heat flux, latent heat flux, soil heat flux and net radiation were measured directly and the energy balance was computed. It is observed that when considered over the whole day, the energy budget is fairly balanced. As a part of energy budget, the Bowen's ratio is also discussed.

The Soil heat flow sensor functioning checks, imbalances’ origins and forgotten energies

Soil heat flux is an important component of the Surface Energy Balance (SEB) equation. Measuring it require an indirect measurement. Every used technique may present some possible errors tied with each specific technique, soil inhomogeneities or physicals phenomenon such as latent heat conversion beneath the plates especially in a desiccation cracking soil or vertisol. The installation place may also induce imbalances. Finally, some errors resulting from the physical sensor presence, vegetation presence or soil inhomogeneities may occur and are not avoidable. For all these reasons it is important to check the validity of the measurements. One quick and easy way is to integrate results during one year. The corresponding integration should be close to zero after a necessary geothermal heat efflux subtraction which should be included into the SEB equation for long term integrations. However, below plate evaporation and vegetation absorbed water or rainfall water the infiltration may also contribute to the observed short scale or/and long scale imbalance. Another energy source is usually not included in the SEB equation: the rainfall or irrigation. Yet its importance for a short- and long-term integration is notable. As an example, the most used sensors: Soil Heat Flux Plates (SHFP), is given.

Artificial Neural Network Model of Soil Heat Flux over Multiple Land Covers in South America

Soil heat flux (G) is an important component for the closure of the surface energy balance (SEB) and the estimation of evapotranspiration (ET) by remote sensing algorithms. Over the last decades, efforts have been focused on parameterizing empirical models for G prediction, based on biophysical parameters estimated by remote sensing. However, due to the existing models’ empirical nature and the restricted conditions in which they were developed, using these models in large-scale applications may lead to significant errors. Thus, the objective of this study was to assess the ability of the artificial neural network (ANN) to predict mid-morning G using extensive remote sensing and meteorological reanalysis data over a broad range of climates and land covers in South America. Surface temperature (Ts), albedo (α), and enhanced vegetation index (EVI), obtained from a moderate resolution imaging spectroradiometer (MODIS), and net radiation (Rn) from the global land data assimilation system 2.1 (GLDAS 2.1) product, were used as inputs. The ANN’s predictions were validated against measurements obtained by 23 flux towers over multiple land cover types in South America, and their performance was compared to that of existing and commonly used models. The Jackson et al. (1987) and Bastiaanssen (1995) G prediction models were calibrated using the flux tower data for quadratic errors minimization. The ANN outperformed existing models, with mean absolute error (MAE) reductions of 43% and 36%, respectively. Additionally, the inclusion of land cover information as an input in the ANN reduced MAE by 22%. This study indicates that the ANN’s structure is more suited for large-scale G prediction than existing models, which can potentially refine SEB fluxes and ET estimates in South America.

Hydrometeorological dataset of West Siberian boreal peatland: a 10-year record from the Mukhrino field station

Northern peatlands represent one of the largest carbon pools in the biosphere, but the carbon they store is increasingly vulnerable to perturbations from climate and land-use change. Meteorological observations taken directly at peatland areas in Siberia are unique and rare, while peatlands are characterized by a specific local climate. This paper presents a hydrological and meteorological dataset collected at the Mukhrino peatland, Khanty-Mansi Autonomous Okrug – Yugra, Russia, over the period of 8 May 2010 to 31 December 2019. Hydrometeorological data were collected from stations located at a small pine–shrub–Sphagnum ridge and Scheuchzeria–Sphagnum hollow at ridge–hollow complexes of ombrotrophic peatland. The monitored meteorological variables include air temperature, air humidity, atmospheric pressure, wind speed and direction, incoming and reflected photosynthetically active radiation, net radiation, soil heat flux, precipitation (rain), and snow depth. A gap-filling procedure based on the Gaussian process regression model with an exponential kernel was developed to obtain continuous time series. For the record from 2010 to 2019, the average mean annual air temperature at the site was −1.0 ∘C, with the mean monthly temperature of the warmest month (July) recorded as 17.4 ∘C and for the coldest month (January) −21.5 ∘C. The average net radiation was about 35.0 W m−2, and the soil heat flux was 2.4 and 1.2 W m−2 for the hollow and the ridge sites, respectively. The presented data are freely available through Zenodo (https://doi.org/10.5281/zenodo.4323024, Dyukarev et al., 2020), last access: 15 December 2020) and can be used in coordination with other hydrological and meteorological datasets to examine the spatiotemporal effects of meteorological conditions on local hydrological responses across cold regions.

Patterns of surface energy exchange and evapotranspiration in relation to water availability in an oasis-desert ecotone

A knowledge of the exchanges of energy and water over the terrestrial surface is the first step to understand the ecohydrological mechanisms, particularly in water-limited ecosystems in the dryland environments. However, patterns of energy exchange and evapotranspiration (ET) are not well understood in the oasis-desert ecotone, which plays an important role in protecting oasis against the threat of desertification in northwestern China’s arid regions. Here the continuous measurements of surface energy fluxes were made using eddy covariance in conjunction with auxiliary measurements for two years (2014-2015) at a shrubland within an oasis-desert ecotone in the arid regions, northwestern China. Statistical analysis on 30-min time scale indicates that about 50% of daytime net radiation (Rn) over the shrubland is dissipated as H on average, which peaks in spring; one third Rn is consumed by soil heat flux (G). Only 9% of Rn was consumed for latent heat flux (λE), which peaks in summer (21% in 2014 and 16% in 2015), corresponding to the season with highest rainfall among all seasons. Daily mean ET is about 1 mm·d−1 during growing season of the shrub species. The rapid and transient increase in ET occurs following a rainfall event. A switch in surface soil moisture from 0.04 to 0.11 m3·m−3 causes an increase in Rn by about 11% and λE by 151% at the shrubland, respectively. Accumulated annual ET were 195 and 181 mm in 2014 and 2015, respectively, exceeding the corresponding P by about 87 and 77 mm, indicating that groundwater may be another important source of water for ET over the shrubland aside from P. These results provide valuable insight into the mechanisms of sustaining energy and water balance at the ecotone, and then produce some management guidelines for allocating water resources and protecting vegetation.