Latent Research Articles

Partitioning Global Surface Energy and Their Controlling Factors Based on Machine Learning

As two competitive pathways of surface energy partitioning, latent (LE) and sensible (H) heat fluxes are expected to be strongly influenced by climate change and wide spread of global greening in recent several decades. Quantifying the surface energy fluxes (i.e., LE and H) variations and controlling factors is still a challenge because of the discrepancy in existing models, parameterizations, as well as driven datasets. In this study, we assessed the ability of random forest (RF, a machine learning method) and further predicted the global surface energy fluxes (i.e., LE and H) by combining FLUXNET observations, climate reanalysis and satellite-based leaf area index (LAI). The results show that the surface energy fluxes variations can be highly explained by the established RF models. The coefficient of determination (R2) ranges from 0.66 to 0.89 for the LE, and from 0.53 to 0.90 for the H across 10 plant functional types (PFTs), respectively. Meanwhile, the root mean square error (RMSE) ranges from 12.20 W/m2 to 21.94 W/m2 for the LE and from 12.05 W/m2 to 22.34 W/m2 for the H at a monthly scale, respectively. The important influencing factors in building RF models are divergent with respect to LE and H, but the solar radiation is common to both LE and H and to all 10 PFTs in this study. We also found a contrasting trend of LE and H: a positive trend in LE and a negative trend in H during 1982–2016 and these contrasting trends are dominated by the elevated CO2 concentration level. Our study suggested an important role of the CO2 concentration in determining surface energy partitioning which is needed to be considered in future studies.

Retrievals of key biophysical parameters at mesoscale from the Ts/VI scatterplot domain

Earth Observation (EO) is often combined with simulated process models to gain insight on key parameters for the physical mechanisms and interactions of the Earth's system. The objective of this study is two-fold: First, it explores the combined use of EO data from the Advanced Along-Track Scanning Radiometer (AATSR) with the SimSphere land biosphere model via the “triangle” to derive latent (LE) and sensible heat (H) fluxes and soil moisture content (SMC) for diverse European ecosystems. Secondly, it investigates the influence of atmospheric correction on the “triangle”-derived retrievals. Both non-atmospherically (1P) and atmospherically corrected (2P) AATSR data products are used. The data cover selected days from 2007 to 2011 at 12 sites of a European ground monitoring network. For all the predicted parameters, the 2P product leads to improved statistical validation measures. The present study for the first time: (1) assesses the triangle technique at 1km mesoscale resolution using AATSR data; (2) investigates the effects of atmospheric correction and surface heterogeneity on prediction accuracy. The findings provide important information regarding potential operational use of the technique.

Geospatial coherence of surface-atmosphere fluxes in the upper Great Lakes region

Surface-atmosphere fluxes are known to vary at multiple time scales, but uncertainty is high as to how fluxes change spatially within regions. With an increase in the number of eddy covariance towers, we are now able to examine the geospatial coherence of ecosystem fluxes, using time-series correlation. Eighteen sites from Michigan and Wisconsin were used in this study, ranging from 100 m to 600 km apart. Surface-atmosphere fluxes from a six-month period were used to quantify spatial coherence on a pair-wise basis. Using geospatial statistics, carbon and sensible heat (H) fluxes were found to be 95% correlated directly outside of their flux footprint and 56% correlated up to a distance of ~35 km. Latent (LE) and momentum (τ) fluxes were less correlated, 83% directly outside of their flux footprint and 40% at a distance of ~130 km albeit, at a much larger spatial distance than for the carbon and sensible heat fluxes. All fluxes showed strong spectral resonance at diel and seasonal timescales, with 1-, 2- and 3-month periods being common modes of variability among H, LE, and τ fluxes. Results based on Empirical Orthogonal Function show distinct transitions of net ecosystem exchange from fall to winter before photosynthesis or respiration while H and τ do not exhibit coherent trends. This work demonstrates the potential of quantifying geospatial coherence of surface-atmosphere fluxes in the Midwestern United States, with the ability to predict fluxes beyond the spatial limit of a single flux tower footprint. Ultimately, expanding the flux measurements to larger scales would allow better spatial scaling of terrestrial surface-atmosphere fluxes between tower footprint and modeling or remote sensing scales.

Observations of Turbulent Heat Fluxes Variability in a Semiarid Coastal Lagoon (Gulf of California)

Despite the critical role latent (LE) and sensible (H) heat play in turbulent processes and heat exchange in the water–air interface, there is a lack of studies of turbulent fluxes over the surface in semiarid regions. We collected continuous measurements of net radiation (Rn), LE, H, and micrometeorological data at a coastal lagoon in the Gulf of California during 2019 with an eddy covariance (EC) system. We analyzed the time series, considering the North American Monsoon System, the pre-monsoon, and post-monsoon season. Results show that Rn (276 ± 118 W m−2) and turbulent fluxes were higher during the monsoon season (July–September) LE (129 ± 18 W m−2), and H (29 ± 9 W m−2). The monthly average of Rn, LE, and H was highest in June (493.9 W m−2), August (142 W m−2), and May (50 W m−2), respectively. Furthermore, during the monsoon season, the (H + LE)/Rn ratio (0.74) suggests that more than half of the Rn reaching the coastal lagoon is used for the turbulent exchange of LE and H. During the pre-monsoon, LE (r2 = 0.36) increases with a higher vapor pressure deficit (VPD), while H (r2 = 0.66) increases with a higher friction velocity (u*) during the monsoon season. Quantitative observations are essential for further research.

Feasibility of Estimating Turbulent Heat Fluxes via Variational Assimilation of Reference-Level Air Temperature and Specific Humidity Observations

This study investigated the feasibility of partitioning the available energy between sensible (H) and latent (LE) heat fluxes via variational assimilation of reference-level air temperature and specific humidity. For this purpose, sequences of reference-level air temperature and specific humidity were assimilated into an atmospheric boundary layer model (ABL) within a variational data assimilation (VDA) framework to estimate H and LE. The VDA approach was tested at six sites (namely, Arou, Audubon, Bondville, Brookings, Desert, and Willow Creek) with contrasting climatic and vegetative conditions. The unknowns of the VDA system were the neutral bulk heat transfer coefficient (CHN) and evaporative fraction (EF). EF estimates were found to agree well with observations in terms of magnitude and day-to-day fluctuations in wet/densely vegetated sites but degraded in dry/sparsely vegetated sites. Similarly, in wet/densely vegetated sites, the variations in the CHN estimates were found to be consistent with those of the leaf area index (LAI) while this consistency deteriorated in dry/sparely vegetated sites. The root mean square errors (RMSEs) of daily H and LE estimates at the Arou site (wet) were 25.43 (Wm−2) and 55.81 (Wm−2), which are respectively 57.6% and 45.4% smaller than those of 60.00 (Wm−2) and 102.21 (Wm−2) at the Desert site (dry). Overall, the results show that the VDA system performs well at wet/densely vegetated sites (e.g., Arou and Willow Creek), but its performance degrades at dry/slightly vegetated sites (e.g., Desert and Audubon). These outcomes show that the sequences of reference-level air temperature and specific humidity have more information on the partitioning of available energy between the sensible and latent heat fluxes in wet/densely vegetated sites than dry/slightly vegetated sites.

Increased control of vegetation on global terrestrial energy fluxes

Changes in vegetation structure are expected to influence the redistribution of heat and moisture; however, how variations in the leaf area index (LAI) affect this global energy partitioning is not yet quantified. Here, we estimate that a unit change in LAI leads to 3.66 ± 0.45 and −3.26 ± 0.41 W m−2 in latent (LE) and sensible (H) fluxes, respectively, over the 1982–2016 period. Analysis of an ensemble of data-driven products shows that these sensitivities increase by about 20% over the observational period, prominently in regions with a limited water supply, probably because of an increased transpiration/evaporation ratio. Global greening has caused a decrease in the Bowen ratio (B = H/LE) of −0.010 ± 0.002 per decade, which is attributable to the increased evaporative surface. Such a direct LAI effect on energy fluxes is largely modulated by plant functional types (PFTs) and background climate conditions. Land surface models (LSMs) misrepresent this vegetation control, possibly due to underestimation of the biophysical responses to changes in the water availability and poor representation of LAI dynamics. Changes in the leaf area index alter the distribution of heat and moisture. The change in energy partitioning related to leaf area, increasing latent and decreasing sensible fluxes over the observational period 1982–2016, is moderated by plant functional type and background climate.

Effects of Surface Heterogeneity Due to Drip Irrigation on Scintillometer Estimates of Sensible, Latent Heat Fluxes and Evapotranspiration over Vineyards

Accurate estimates of sensible (H) and latent (LE) heat fluxes and actual evapotranspiration (ET) are required for monitoring vegetation growth and improved agricultural water management. A large aperture scintillometer (LAS) was used to provide these estimates with the objective of quantifying the effects of surface heterogeneity due to soil moisture and vegetation growth variability. The study was conducted over drip-irrigated vineyards located in a semi-arid region in Albacete, Spain during summer 2007. Surface heterogeneity was characterized by integrating eddy covariance (EC) observations of H, LE and ET; land surface temperature (LST) and normalized difference vegetation index (NDVI) data from Landsat and MODIS sensors; LST from an infrared thermometer (IRT); a data fusion model; and a two-source surface energy balance model. The EC observations showed 16% lack of closure during unstable atmospheric conditions and was corrected using the residual method. The comparison between the LAS and EC measurements of H, LE, and ET showed root mean square difference (RMSD) of 25 W m−2, 19 W m−2, and 0.41 mm day−1, respectively. LAS overestimated H and underestimated both LE and ET by 24 W m−2, 34 W m−2, and 0.36 mm day−1, respectively. The effects of soil moisture on LAS measurement of H was evaluated using the Bowen ratio, β. Discrepancies between HLAS and HEC were higher at β ≤ 0.5 but improved at 1 ≥ β > 0.5 and β > 1.0 with R2 of 0.76, 0.78, and 0.82, respectively. Variable vineyard growth affected LAS performance as its footprints saw lower NDVILAS compared to that of the EC (NDVIEC) by ~0.022. Surface heterogeneity increased during wetter periods, as characterized by the LST–NDVI space and temperature vegetation dryness index (TVDI). As TVDI increased (decreased) during drier (wetter) conditions, the discrepancies between HLAS and HEC, as well as LELAS and LEEC Re decreased (increased). Thresholds of TVDI of 0.3, 0.25, and 0.5 were identified, above which better agreements between LAS and EC estimates of H, LE, and ET, respectively, were obtained. These findings highlight the effectiveness and ability of LAS in monitoring vegetation growth over heterogonous areas with variable soil moisture, its potential use in supporting irrigation scheduling and agricultural water management over large regions.

Using Large-Aperture Scintillometer to Estimate Lake-Water Evaporation and Heat Fluxes in the Badain Jaran Desert, China

Accurate estimation of evaporation (E0) over open water bodies in arid regions (e.g., lakes in the desert) is of great importance for local water resource management. Due to the ability to accurately determine sensible (H) and latent (LE) heat fluxes over scales of hundreds to thousands of meters, scintillometers are more and more appreciated. In this study, a scintillometer was installed on both sides of the shore over the Sumu Barun Jaran Lake in the Badain Jaran Desert and was applied to estimate the sensible and latent heat fluxes and evaporation to be compared with the data of an evaporation pan and an aerodynamic model. Based on the field data, we further analyzed the seasonal differences in the flux evaluation using water temperature at different depths at half-hour and daily time scales, respectively. The results showed that in cold seasons, values of H were barely affected by the changes of shallow water temperature, whereas in hot seasons, the values were changed by 20%–30% at the half-hour time scale and 6.2%–18.3% at the daily time scale. In different seasons, shallow water temperature at different depths caused changes in the range of 0%–20% of LE (E0). This study contributes to a better understanding of uncertainties in measurements by large-aperture scintillometers in open-water environments.

Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework

AbstractEstimation of turbulent heat fluxes via variational data assimilation (VDA) approaches has been the subject of several studies. The VDA approaches need an adjoint model that is difficult to derive. In this study, remotely sensed land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are assimilated into the heat diffusion equation within an ensemble Kalman smoother (EnKS) approach to estimate turbulent heat fluxes. The EnKS approach is tested in the Heihe River Basin (HRB) in northwest China. The results show that the EnKS approach can estimate turbulent heat fluxes by assimilating low temporal resolution LST data from MODIS. The findings indicate that the EnKS approach performs fairly well in various hydrological and vegetative conditions. The estimated sensible (H) and latent (LE) heat fluxes are compared with the corresponding observations from large aperture scintillometer systems at three sites (namely, Arou, Daman, and Sidaoqiao) in the HRB. The turbulent heat flux estimates from EnKS agree reasonably well with the observations, and are comparable to those of the VDA approach. The EnKS approach also provides statistical information on the H and LE estimates. It is found that the uncertainties of H and LE estimates are higher over wet and/or densely vegetated areas (grassland and forest) compared to the dry and/or slightly vegetated areas (cropland, shrubland, and barren land).

Surface Turbulent Fluxes during Persistent Cold-Air Pool Events in the Salt Lake Valley, Utah. Part I: Observations

AbstractThe land surface is coupled to the atmospheric boundary layer through surface turbulent fluxes. Persistent cold-air pools (PCAPs) form in topographic depressions where cold, dense air fills the valley basin and in the presence of air pollution is accompanied by poor air quality. For the first time, the surface turbulence dataset from seven monitors during the Persistent Cold-Air Pool Study conducted in Salt Lake Valley, Utah (December 2010–February 2011), are analyzed. We found that the surface sensible (H) and latent (LE) heat fluxes were lower during strong PCAP events compared with non-PCAPs. The higher ratio of heat flux to net radiation (H/Rn and LE/Rn) for strong PCAPs compared with weak PCAPs is suspected to be related to the presence of boundary layer clouds, which could enhance the turbulent mixing through cloud top–down mixing. The daily average ground heat flux (G) was a similar order of magnitude toHand LE during wintertime. The highest surface turbulent fluxes and energy balance closure occurred in the stability range of −0.05 <ξ≤ −0.02, or under slightly unstable conditions, near the neutral stability range. The median surface exchange coefficient (Ch), a crucial parameter to determine surface turbulent fluxes in land surface models, was slightly higher at the bare land site (BL) than the short vegetation sites (PH and CR) in wintertime, suggesting the importance of dynamic land-use information in numerical models.

Robust observations of land-to-atmosphere feedbacks using the information flows of FLUXNET

Feedbacks between atmospheric processes like precipitation and land surface fluxes including evapotranspiration are difficult to observe, but critical for understanding the role of the land surface in the Earth System. To quantify global surface-atmosphere feedbacks we use results of a process network (PN) applied to 251 eddy covariance sites from the LaThuile database to train a neural network across the global terrestrial surface. There is a strong land–atmosphere coupling between latent (LE) and sensible heat flux (H) and precipitation (P) during summer months in temperate regions, and between H and P during winter, whereas tropical rainforests show little coupling seasonality. Savanna, shrubland, and other semi-arid ecosystems exhibit strong responses in their coupling behavior based on water availability. Feedback couplings from surface fluxes to P peaks at aridity (P/potential evapotranspiration ETp) values near unity, whereas coupling with respect to clouds, inferred from reduced global radiation, increases as P/ETp approaches zero. Spatial patterns in feedback coupling strength are related to climatic zone and biome type. Information flow statistics highlight hotspots of (1) persistent land–atmosphere coupling in sub-Saharan Africa, (2) boreal summer coupling in the central and southwestern US, Brazil, and the Congo basin and (3) in the southern Andes, South Africa and Australia during austral summer. Our data-driven approach to quantifying land atmosphere coupling strength that leverages the global FLUXNET database and information flow statistics provides a basis for verification of feedback interactions in general circulation models and for predicting locations where land cover change will feedback to climate or weather.

PATTERNS OF ENERGY EXCHANGE FOR TROPICAL URBAN AND RURAL ECOSYSTEMS LOCATED IN BRAZIL CENTRAL

Seasonality and inter-annual variation of the energy balance of natural surfaces as the effect of conversion from natural to agricultural areas has been the object of much in-depth research in South America. However, none has assessed the effect of conversion from a native to an urbanized area. Current research was performed in the city of Cuiabá, in the Cerrado-Pantanal ecotone, state of Mato Grosso, central Brazil, featuring a tropical sub-humid climate (Aw). The paper investigates the pattern of energy fluxes exchanges in the rural and urban sites located in Brazilian savannah ecosystem. The heat stored inside the urban canopy (ΔQS) and within the rural area was obtained by the Objective Hysteresis Model (OHM) and by soil flux meter, respectively. Sensible (H) and latent (LE) heat fluxes were estimated by the Bowen Ratio Energy Balance (BREB). The rural and urban sites had different patterns in the micrometeorology variables Wind speed decreased and air temperature and vapor pressure deficit increased from rural to urban site. The urbanization also modified the energy fluxes partition of urban canopy by increasing ΔQs (12%) and H (60%) and by decreasing LE (29%), with β = 2.0 in contrast of rural canopy, where the partition was ΔQs (1.5%), H (29%), LE (64%) and β = 0.45. The ΔQS, H and LE were in phase with Rn, differing from what has been reported for sites in North America and Europe.

PATTERNS OF ENERGY EXCHANGE FOR TROPICAL URBAN AND RURAL ECOSYSTEMS LOCATED IN BRAZIL CENTRAL

Seasonality and inter-annual variation of the energy balance of natural surfaces as the effect of conversion from natural to agricultural areas has been the object of much in-depth research in South America. However, none has assessed the effect of conversion from a native to an urbanized area. Current research was performed in the city of Cuiabá, in the Cerrado-Pantanal ecotone, state of Mato Grosso, central Brazil, featuring a tropical sub-humid climate (Aw). The paper investigates the pattern of energy fluxes exchanges in the rural and urban sites located in Brazilian savannah ecosystem. The heat stored inside the urban canopy (ΔQS) and within the rural area was obtained by the Objective Hysteresis Model (OHM) and by soil flux meter, respectively. Sensible (H) and latent (LE) heat fluxes were estimated by the Bowen Ratio Energy Balance (BREB). The rural and urban sites had different patterns in the micrometeorology variables Wind speed decreased and air temperature and vapor pressure deficit increased from rural to urban site. The urbanization also modified the energy fluxes partition of urban canopy by increasing ΔQs (12%) and H (60%) and by decreasing LE (29%), with β = 2.0 in contrast of rural canopy, where the partition was ΔQs (1.5%), H (29%), LE (64%) and β = 0.45. The ΔQS, H and LE were in phase with Rn, differing from what has been reported for sites in North America and Europe.

Long-term variations in energy partitioning and evapotranspiration in a semiarid grassland in the Loess Plateau of China

Estimating seasonal and interannual variations in energy partitioning and actual evapotranspiration (ET) distributions in semiarid grasslands is essential for improving the understanding of interactions between the land and atmosphere, and is useful for land surface parameterization in grasslands of the Loess Plateau. In this study, energy fluxes and ET values over a semiarid grassland site and their environmental and biological controls were investigated over multiple years (2007–2012) using the eddy covariance method. The seasonal and interannual variations in the partitioning of the net radiation (Rn) into sensible (H) and latent (LE) heat fluxes were primarily controlled by precipitation through changes in the soil water content (SWC) and vegetation growth. During relatively wet and warm periods, LE was the dominant component of the energy balance, whereas H was the dominant component of energy partitioning in dry periods. Annual ET was higher than annual P (except in 2007), with a better closure of surface energy balance during the drier years. The total annual ET and its daily maximum varied from 278.2 to 460.3 mm and from 3.45 to 4.95 mm day−1, respectively. The daily Priestley-Taylor coefficient (ET/ETeq, where ETeq is the equilibrium evaporation) decreased sharply when the SWC in the 5-cm soil layer decreased below 0.15 m3 m-3 during the growing seasons. The average ET for sixteen days was linearly correlated with the normalized difference vegetation index (NDVI). ET/ETeq increased nonlinearly with an increase in Gs but was insensitive to the increases in Gs greater than 6.52 mm s−1 in the driest year (2011) and 9.17 mm s−1 in the wettest year (2007). Additionally, there is good correlation between the threshold of Gs and the annual mean NDVI. On an annual scale, the low Gs (3.07-6.77 mm s−1), ET/ETeq (0.28-0.42), and higher Bowen ratio (β) (2.07–4.19) collectively represented the overall water-limited conditions for ET in the semiarid grassland of the Loess Plateau. Our data indicate that ET and its biophysical controls vary in response to interannual changes in annual P. These results contribute to an understanding of the driving mechanisms for long-term variations in energy partitioning and biophysical controls on ET in the Loess Plateau of China.

Dynamics of the superficial fluxes over a flooded rice paddy in southern Brazil

In Southern Brazil, rice paddies are an important agribusiness occurring in lowlands, where the growing season occurs in the summer and the area remains without use in the rest of the year. We estimated the surface fluxes (carbon dioxide (CO2), Latent (LE) and Sensible (H) heat fluxes) over a flooded rice paddy in Southern Brazil for a five-year period using the eddy covariance methodology. LE was higher than H, with mean values of the Bowen ratio (H LE−1) of 0.14 during the growing season and 0.35 during the fallow season. The mean evapotranspiration (ET) was of 4.3 ± 0.3 mm d−1 during the growing season and 1.8 ± 0.3 mm d−1 during the fallow season. We related the gross primary production with the water use efficiency to obtain the partitioning of ET between evaporation (E) and transpiration (T). Annually, E and T represent approximately 50% of the ET. However, there is a marked seasonal variability in these components, mainly related to the variation of the leaf area index. Over the full five-year study period, the flooded rice paddy was a net carbon sink of 198 ± 221 gC m-2 y−1. The CO2 flux presented high variability between the fallow and growing seasons. The fallow periods represent a source of 268 ± 123 gC m-2 y−1, and the growing seasons are a sink of 448 ± 105 gC m-2 y−1. During the annual period, the flooded rice paddy presents a low water use efficiency, 1.05 gC kgH2O−1.

The exchange of water and energy between a tropical peat forest and the atmosphere: Seasonal trends and comparison against other tropical rainforests

Tropical rainforests control the exchange of water and energy between the land surface and the atmosphere near the equator and thus play an important role in the global climate system. Measurements of latent (LE) and sensible heat exchange (H) have not been synthesized across global tropical rainforests to date, which can help place observations from individual tropical forests in a global context. We measured LE and H for four years in a tropical peat forest ecosystem in Sarawak, Malaysian Borneo using eddy covariance, and hypothesize that the study ecosystem will exhibit less seasonal variability in turbulent fluxes than other tropical ecosystems as soil water is not expected to be limiting in a tropical forested wetland. LE and H show little variability across seasons in the study ecosystem, with LE values on the order of 11 MJ m−2 day and H on the order of 3 MJ m−2 day−1. Annual evapotranspiration (ET) did not differ among years and averaged 1579 ± 47 mm year−1. LE exceeded characteristic values from other tropical rainforest ecosystems in the FLUXNET2015 database with the exception of GF-Guy near coastal French Guyana, which averaged 8–11 MJ m−2 day−1. The Bowen ratio (Bo) in tropical rainforests in the FLUXNET2015 database either exhibited little seasonal trend, one seasonal peak, or two peaks. Volumetric water content (VWC) and VPD explained a trivial amount of the variability of LE and Bo in some of the tropical rainforests including the study ecosystem, but were strong controls in others, suggesting differences in stomatal regulation and/or the partitioning between evaporation and transpiration. Results demonstrate important differences in the seasonal patterns in water and energy exchange across different tropical rainforest ecosystems that need to be understood to quantify how ongoing changes in tropical rainforest extent will impact the global climate system.

Monsoonal and annual energy fluxes variations in the atmospheric surface layer over a coastal region of the tropical ocean

The tropical coastal ocean is a vital jigsaw-piece to understanding exchanges of energy, moisture, and carbon between the atmosphere and the ocean biospheres. Latent and sensible heat fluxes, micro-climate variables, and surface water temperature data in the atmospheric surface layer were collected using an instrumented tower at a tropical coastal ocean (5 ∘28’6”N, 100∘12’1”E). The instrumented tower was installed on a stainless-steel platform extending a pre-existing pier. Data were collected for two years, i.e., November 2015 to October 2017, which encompassed two annual cycles of the Monsoons. The first objective of this work is to describe the Monsoonal and annual patterns of latent (LE) and sensible (H) heats while the second objective is to link the micro-climate variables to the energy fluxes on the seasonal and annual time scales. The inter-annual variation of energy input into the study is minimal (3% and 4% in the values recorded for the RG and Rn). The average albedo was 0.29 and the Bowen ratio was 0.11. Annual changes in LE and H between the two years were apparent both at 14% increased and decreased, respectively. LE is largely modulated by the Monsoons, where it is higher in the Northeast Monsoon (dry and hot) than the Southwest Monsoon (wet and cold). Conversely, H did not exhibit appreciably changes with the Monsoon and mostly followed the downward Rn trend. Variations between Monsoons are ten times larger than between years, thus highlighting its significance in controlling the regional conditions. Between the Northeast and Southwest Monsoons, the change in LE, i.e., ΔLE recorded was −30% while that of H, i.e., ΔH was ＋18%. These results have important applications in improving numerical weather models and closing the energy budget.

A new method for estimating of evapotranspiration and surface soil moisture from optical and thermal infrared measurements: the simplified triangle

ABSTRACT Earth Observation (EO) provides a promising approach towards deriving accurate spatiotemporal estimates of key parameters characterizing land surface interactions, such as latent (LE) and sensible (H) heat fluxes as well as soil moisture content. This paper proposes a very simple method to implement, yet reliable to calculate evapotranspiration fraction (EF) and surface moisture availability (Mo) from remotely sensed imagery of Normalized Difference Vegetation Index (NDVI) and surface radiometric temperature (Tir). The method is unique in that it derives all of its information solely from these two images. As such, it does not depend on knowing ancillary surface or atmospheric parameters, nor does it require the use of a land surface model. The procedure for computing spatiotemporal estimates of these important land surface parameters is outlined herein stepwise for practical application by the user. Moreover, as the newly developed scheme is not tied to any particular sensor, it can also be implemented with technologically advanced EO sensors launched recently or planned to be launched such as Landsat 8 and Sentinel 3. The latter offers a number of key advantages in terms of future implementation of the method and wider use for research and practical applications alike.

Northern Hemisphere Extratropical Turbulent Heat Fluxes in ASRv2 and Global Reanalyses

Abstract Large-scale objectively analyzed gridded products and satellite estimates of sensible (H) and latent (LE) heat fluxes over the extratropical Northern Hemisphere are compared to those derived from the regional Arctic System Reanalysis version 2 (ASRv2) and a selection of current-generation global reanalyses. Differences in H and LE among the reanalyses are strongly linked to the wind speed magnitudes and vegetation cover. Specifically, ASRv2 wind speeds match closely with observations over the northern oceans, leading to an improved representation of H compared to the global reanalyses. Comparison of evaporative fraction shows that the global reanalyses are characterized by a similar H and LE partitioning from April through September, and therefore exhibit weak intraseasonal variability. However, the higher horizontal resolution and weekly modification of the vegetation cover based on satellite data in ASRv2 provides an improved snow–albedo feedback related to changes in the leaf area index. Hence, ASRv2 better captures the small-scale processes associated with day-to-day vegetation feedbacks with particular improvements to the H over land. All of the reanalyses provide realistic dominant hemispheric patterns of H and LE and the locations of maximum and minimum fluxes, but they differ greatly with respect to magnitude. This is especially true for LE over oceanic regions. Therefore, uncertainties in heat fluxes remain that may be alleviated in reanalyses through improved representation of physical processes and enhanced assimilation of observations.

Energy partitioning of greenhouse cucumber based on the application of Penman-Monteith and Bulk Transfer models

Partitioning between latent (LET) and sensible (H) heat fluxes is critical in improving the greenhouse crops irrigation scheduling and microclimate. By applying the Bulk Transfer (BT) and Penman-Monteith (PM) models, the energy fluxes in different growing stages of the cucumber crop were determined in a Venlo-type greenhouse. The application of the BT and PM models is constrained by accurate parameterizations of canopy resistance (rc) and aerodynamic resistance (ra). In this paper, we measured micrometeorological data, crop growth index and LET during cucumber growing seasons in spring and autumn of 2016. The rc was modelled with stomatal conductance of cucumber leaves and validated with actual measurement of LET by lysimeters. The results showed that rc varied from 35 s m−1 during the day to 500 s m−1 at night in spring season, whilst it ranged from 40 s m−1 during the day to 1000 s m−1 at night in autumn season. Comparison of rc estimated by the PM and the BT models demonstrated that the rc estimated by the two methods were similar and highly correlated for both seasons. During the spring season, the PM and the BT models gave the determination coefficients (R2) of predicted hourly LET equal to 0.94 and 0.83, whereas during the autumn season, the values were 0.94 and 0.76, respectively. The average root mean square errors (RMSE) of measured and predicted hourly LET were 96.97 and 74.74 W m-2 for the spring and autumn seasons for PM model, respectively. In contrast, the BT model gave RMSE of measured and predicted hourly LET of 82.47 and 69.14 W m-2, for spring and autumn, respectively. The results also depicted that the simplified energy balance approach was a feasible alternative to partition the energy fluxes in the greenhouse. The predictions made in this study would be an easy and relatively accurate way to partition greenhouse cucumber energy fluxes and thus, scientifically plan the irrigation schedule. In conclusion, this study provides scientific basis for optimizing efficient water-saving irrigation, development of a suitable irrigation scheduling and improving crop water use efficiency in the greenhouse, and consequently, more energy savings by avoiding excessive water application and thereby the objective of having improved and satisfactory yield and higher economic returns can be achieved.