Observations of daytime surface energy balance in cloudy tropical conditions at Ile-Ife, Nigeria

Daytime energy balance at the surface in cloudy tropical conditions for Ile-Ife; Nigeria (7°33'N, 4°34'E) is investigated based on a series of micrometeorological measurements performed in October/November of 1998. For the humid environment that it is (mixing ratio, 17 -25 g / kg), magnitudes of the latent heat flux were much larger than the values for the sensible heat. Of the morning hours the average value for the Bowen ratio obtained was 0.36, while for the afternoons it was 0.74. As the soil surface became dried up in the afternoons, magnitudes of both sensible heat and ground heat fluxes were found to be comparable. Fluctuations in the magnitudes of the terms of the surface energy balance correlated well to the cloud amount, degree of soil wetness, air temperature and humidity. But of all these factors, the variation in the amount of cloudiness appeared most dominant.

Czasowa zmienność i przestrzenne zróżnicowanie ewapotranspiracji w zlewni nizinnej rzeki Łasicy

Accurate quantification of evapotranspiration is necessary for understanding the water cycle at a local scale. At catchment scale, evapotranspiration might be approximated using remote sensing data useful in spatialtemporal analyses. In this study, the long-term and seasonal variability of evapotranspiration in the Łasica River catchment in the years 2003–2020 was assessed on the basis of data acquired from the SSEBop project (Operational Simplified Surface Energy Balance). Additionally, using the index of precipitation utilization (WWO), the degree of precipitation consumption for the water demands of plants was determined. The highest evapotranspiration occurs in forest areas, slightly lower in marshy belts covered with meadow vegetation, and the lowest in agricultural areas and anthropogenically transformed areas. The spatial differentiation of evapotranspiration is particularly marked during the growing season, from April to October. Mean annual evapotranspiration sum is 403 mm, of which 96% falls on the growing season. Extremely low annual ET sums occurred in 2015 (329 mm), 2019 (342 mm) and 2003 (384 mm), while particularly high – in 2010 (455 mm) and 2013 (447 mm). In dry years, WWO is even 71–77%, while in particularly wet years, WWO is much lower and amounts to 54–58%.

Comparative Evaluation of Simplified Surface Energy Balance Index-Based Actual ET against Lysimeter Data in a Tropical River Basin

In the past decades, multispectral and multitemporal remote sensing has been popularly used for estimating actual evapotranspiration (ETc) across the globe. It has been proven to be a cost-effective tool for understanding agricultural practices in a region. Today, because of the availability of different onboard sensors on an increasing number of different satellites, land surface activity can be captured at fine spatial and time scales. In the present study, three multi-date satellite imageries were used for the evaluation of remote sensing-based estimation of actual evapotranspiration in paddy in the command area of the tropical Kangsabati river basin. A surface energy balance model, the Simplified-Surface Energy Balance Index (S-SEBI), was applied for all three dates of the Rabi season (2014–2015) for the estimation of actual evapotranspiration. The crop coefficient was calculated using the exhaustive survey data collected from the command area and adjusted to local conditions. The ETc estimated using the S-SEBI-based model was compared with the Food and Agriculture Organization Penman–Monteith (FAO-56 PM) method multiplied by the adjusted local crop coefficient and lysimeter data in the command area. The coefficient of determination (r2) was applied to examine the accuracy of the S-SEBI model with respect to lysimeter data and the FAO-56 PM-based ETc. The results showed that the S-SEBI model performed well with the lysimeter (r2 = 0.90) in comparison with FAO-56 PM, with an r2 of 0.65. In addition to this, the S-SEBI-based ET estimates correlated well with the FAO-56 PM, with r and RMSE values of 0.06 and 1.13 mm/day (initial stage), 0.85 and 0.48 mm/day (development stage), and 0.77 and 0.52 (maturity stage) for paddy, respectively. The S-SEBI-based ETc estimate varied with different stages of crop growth and successfully captured the spatial heterogeneity within the command area. In general, this study showed that the S-SEBI method has the potential to calculate spatial evapotranspiration and provide useful information for efficient water management. The results revealed the applicability and accuracy of remote sensing-based ET for managing water resources in a command area with scarce data.

Characteristic Decrease in the Value of Rapeseed Evapotranspiration after Its Ripening

This paper presents the methodology of taking measurements of active surface energy balance components using the Bowen method. It discusses the applied measurement system, an important part of which are HMD 50U/50Y measurement sensors from Vaisala, adapted to work in the field. Their operation is a source of data for determining vertical profiles of temperature and water vapour pressure. These data are used to determine the turbulence components of the energy balance, i.e., sensible and latent heat. Measurements taken during the vegetative season on rape field showed that intensive evaporation occurred in the period until the end of June and that its decrease coincided with the decrease in the value of the degree of plant development determined on the basis of LAI records. In spring, during the period of intensive plant development, the decade sums of evaporation reached 30 mm, after which their quantities fell to the range of 10–15 mm. They became higher only in the periods of precipitation, when the water from the interception was available.

The surface energy balance of Austre Lovénbreen, Svalbard, during the ablation period in 2014

The ability to simulate the surface energy balance is key to studying land–atmosphere interactions; however, it remains a weakness in Arctic polar sciences. Based on the analysis of meteorological data from 1 June to 30 September 2014 from an automatic weather station on the glacier Austre Lovénbreen, near Ny–Ålesund, Svalbard, we established a surface energy balance model to simulate surface melt. The results reveal that the net shortwave radiation accounts for 87% (39 W m–2) of the energy sources, and is controlled by cloud cover and surface albedo. The sensible heat equals 6 W m–2 and is a continuous energy source at the glacier surface. Net longwave radiation and latent heat account for 31% and 5% of heat sinks, respectively. The simulated summer mass balance equals –793 mm w.e., agreeing well with the observation by an ultrasonic ranger.

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.