Soil Heat Flux Research Articles

Balanço de Radiação e Partição de Fluxos de Calor Sensível e Latente Sobre Um Pomar de Lima ácida na Amazônia Oriental

Abstract We investigate the balance of radiation and energy over a lime orchard in Eastern Amazon and how it relates to environmental conditions. We found that lime trees aged between 6 and 7 years old reflect 11.0% to 14.5% of incoming shortwave radiation, and the latent heat flux corresponds to 57.6% and 66.6% of the daily net radiation in the dry season (August - November) of 2020, and 2021, respectively. The soil heat flux represents 1% to 2% of the daily net radiation. Evapotranspiration was much lower than the reference evapotranspiration from August to November in 2019 and 2020. Evapotranspiration increased proportionally to the reference evapotranspiration from August to November 2021. This increase may be explained by weather conditions, such as the frequent rainfall during the dry season of 2021, in the same period when the energy for evapotranspiration is higher. Also, the high relative humidity between August and November 2021 may have favored the opening of stomata, increasing the orchard's evapotranspiration. The crop coefficient ranges between 0.74 and 0.84.

A coupled WRF-PV mesoscale model simulating the near-surface climate of utility-scale photovoltaic plants

To simulate the local or regional climate of utility-scale photovoltaic (PV) plants, a new PV-associated energy balance model was developed for the Weather Research and Forecasting Model (WRF). The resultant tool can be used to improve our understanding of the interaction between utility-scale PV plants and land-surface processes. The effects of PV panels were represented by transferring the solar radiation into electricity and heat flux and imposing an extra drag force on the mean flow in the model domain. The proposed PV model is more advanced than previous models in the following ways: (1) The model is universal based on its analytical expression of the sensible heat of PV panels and the influence of the physical shielding of the panels on the upward longwave radiation. (2) The photoelectric conversion efficiency (ε) in the model is temperature dependent and restrained between seasons. (3) The model includes the soil and latent heat flux parameterizations under observation constraints in a novel way. (4) The model bases the dynamic roughness length (Z0) on the eddy covariance flux observation. This new PV model was then incorporated with the WRF mesoscale meteorological model, and the model evaluation in two utility-scale PV plants demonstrated acceptable performance of the new WRF-PV mesoscale model in simulating the max/mean daily surface temperature, downward shortwave radiation, and wind speed with correlation coefficients of 0.61–0.99, and the hourly sensible/latent heat fluxes, with correlation coefficients of 0.59–0.93 during different seasons. The consistency of the performance of the model across these near-surface meteorological variables confirms the versatility and reliability of the new WRF-PV model as a suitable tool for simulating the climate of utility-scale PV plants.

Estimation of Sensible and Latent Heat Fluxes Using Flux Variance Method under Unstable Conditions: A Case Study of Tea Plants

Evapotranspiration is essential for precise irrigation and water resource management. Previous literature suggested that eddy covariance (EC) systems could directly measure evapotranspiration in agricultural fields. However, the eddy covariance method remains difficult for routine use, due to its high cost, operational complexity, and relatively multifaceted raw data processing. An alternative method is the flux variance (FV) method, which can estimate the sensible heat flux using high-frequency air temperature measurements by fine-wire thermocouples, at relatively low-cost and with less complexity. Additional measurements of the net radiation and soil heat flux permit the extraction of latent heat flux through the energy balance closure equation. This study examined the performance of the FV method and the results were compared against direct eddy covariance measurements. Data were collected from November 2018 to July 2019, covering seasonal variations. Due to the method’s limitation, only the data under unstable conditions were used for the analysis and days with rainfall were omitted. The results showed that the FV-estimated sensible heat flux was in good agreement with that of eddy covariance in the seasons of winter 2018 and summer 2019. The best agreement between the estimated and measured sensible heat fluxes was observed in the summer, with R2 = 0.83, RMSE = 34.97 Wm−2 and RE = 8.20%. The FV extracted latent heat flux was in good agreement with that measured by EC for both seasons. The best result was obtained in the summer, with R2 = 0.92, RMSE = 23.12 Wm−2, and RE = 6.37%. Overall estimations of sensible and latent heat fluxes by the FV method were in close relation with the eddy covariance data.

Variation characteristics of soil temperature, moisture, and heat flux in the understorey of evergreen broadleaf forest in South China

Based on observation data from the observation tower station in Zhuhai in South China from October 2015 to May 2018, the variations in soil temperature, moisture, and heat flux in the understorey of evergreen broadleaf forest are analyzed. The ground surface temperature is slightly greater than the canopy surface temperature; the soil temperature is the smallest. The seasonal variation in the soil moisture fluctuates around a relative equilibrium as the rain increases or decreases. Both ground and canopy surface temperatures have valley values before sunrise and peak values in the afternoon. The diurnal variations in soil temperature are characterized by a cosine function. With the deepening of the soil layer, the time of valley and peak lag and the amplitude of the variation in the soil temperature decrease. There is almost no diurnal variation in soil temperature at 40 cm depth or the soil heat flux at 30 cm depth. The heat fluxes at depths of 7.5 cm and 15 cm show an “S” pattern variation, with a peak at 17:30. The net radiation of the canopy surface shows a bell-shaped variation, with a peak at 12:30. The averaged soil thermal conductivities are 2.18 W·m−1·K−1, 1.22 W·m−1·K−1, and 1.26 W·m−1·K−1 for 5 ~ 10 cm, 10 ~ 20 cm, and 20 ~ 40 cm depths, respectively.

Global land surface evapotranspiration monitoring by ETMonitor model driven by multi-source satellite earth observations

Evapotranspiration (ET) is an essential ecohydrological process linking the land surface energy, water and carbon cycles, and plays a critical role in the earth system. ET remains one of the most problematic components of the water cycle to be determined due to the heterogeneity of the landscape and the complexity of driving factors. The satellite-based earth observation is expected to provide ET information at large-scales. However, accurate global ET information, with spatially and temporally continuous coverage at moderate-to-high resolution, is still scarce. In this paper, a combined model, called ETMonitor, with multi-process parameterizations, was improved and applied to estimate the global ET, mainly using the biophysical and hydrological parameters/variables retrieved from satellite observations. The ETMonitor model was improved in several aspects in this study to generate the global ET datasets during 2000–2019 at daily/1-km resolution, including: 1) adopting high temporal resolution surface water cover and snow/ice cover as input, to simulate the impact of their seasonal change on ET variation; 2) parameterizing the impact of soil moisture on plant transpiration and soil evaporation using high resolution soil moisture, which was downscaled to 1-km resolution from the coarse resolution data retrieved from microwave remote sensing observation; 3) involving a better soil heat flux estimation to reduce its impact on the uncertainty of estimated ET; 4) being calibrated based on global ground flux observations to achieve better accuracy. The estimated daily ET was validated based on the global in situ observations at site scale across various ecosystems, with overall high correlation (0.75), low bias (0.08 mm d-1), and low root mean square error (0.93 mm d-1). It had good ability to partition total ET to plant transpiration and soil evaporation indicated by the good agreement with the ground isotope measurements in a growing season at one site in the northwest China. The estimated global ET was cross-validated by comparing with other existing ET products, and it showed the global ET estimated by ETMonitor could capture the expected global ET patterns both in space and in time. It also indicated the superiority of the ET product by ETMonitor in the following aspects: capability in capturing the seasonal dynamics of waterbody evaporation and sublimation; better performance in capturing the spatial variation of ET in the irrigated cropland regions and mountain regions with complex terrain than other global ET products, e.g., the GLEAM and MOD16 ET products; capability of ET component partitioning at high spatial (1-km) and high temporal (daily) resolutions with good accuracy. The estimated plant transpiration, soil evaporation, canopy rainfall interception loss, and water body evaporation and snow sublimation accounted for 61.54 % (±0.44 %), 19.08 % (±0.54 %), 13.54 % (±0.49 %), and 5.84 % (±0.24 %), respectively, of the total ET on global average. The ETMonitor global ET dataset could provide important information on studies of global terrestrial water and energy cycles and climate change studies, and water resources management at global and regional scales.

A benchmark dataset of diurnal- and seasonal-scale radiation, heat, and CO2 fluxes in a typical East Asian monsoon region

Abstract. A benchmark dataset of radiation, heat, and CO2 fluxes is crucial to land–atmosphere interaction research. Due to rapid urbanization and the development of agriculture, the land–atmosphere interaction processes over the Yangtze River Delta (YRD) of China, which is a typical East Asian monsoon region, are becoming various and complex. To understand the effects of various land cover changes on land–atmosphere interactions in this region, a comprehensive long-term (2011–2019) in situ observation campaign, including 30 min resolution meteorological variables (air temperature, humidity, pressure, wind speed, and wind direction), surface radiative flux, turbulent heat flux, and CO2 flux, was conducted at four sites with two typical surface types (i.e., croplands and suburbs) in the YRD. Analysis of the dataset showed that all four radiation components, latent heat flux, sensible heat flux, soil heat flux, and CO2 flux varied seasonally and diurnally at the four sites. Surface energy fluxes exhibited great differences among the four sites. On an annual basis, for the two cropland sites, the dominant consumer of net radiation was latent heat flux. For the two suburban sites, in contrast, latent heating dominated from April to November, whereas sensible heating dominated during the other months. Our present work provides convincing evidence that the dataset has potential for multiple research fields, including studying land–atmosphere interactions, improving boundary layer parameterization schemes, evaluating remote sensing algorithms, validating carbon flux modeling and inversion, and developing climate models for typical East Asian monsoon regions. The dataset is publicly available at https://doi.org/10.5281/zenodo.6552301 (Duan et al., 2022).

Dynamics and environmental controls of evapotranspiration for typical alpine meadow in the northeastern Tibetan Plateau

To understand the water, energy, and carbon cycles in the Tibetan Plateau (TP), it is essential to estimate seasonal and inter-annual variations in energy fluxes and evapotranspiration (ET) for alpine meadow ecosystems. The multiyear (2014–2019) energy fluxes and ET, for a typical alpine meadow at Arou station (northeastern TP), and their environmental and biophysical controls were evaluated using the eddy covariance method in this study. Latent heat flux (LE) was the dominant component of energy consumption during the growing season, whereas sensible heat flux (H) dominated energy partitioning during the non-growing season. H showed the opposite trend to LE, while the seasonal variation of soil heat flux (G) was small. The daily ET was primarily controlled by the available energy on the seasonal scale. Soil water content (SWC) and normalized difference vegetation index (NDVI) displayed secondary effects on ET during the non-growing and growing seasons, respectively. The inter-annual ET was relatively stable, ranging from 562.6 to 661.9 mm (coefficient of variation; CV = 7.4 %); this was slightly higher than the annual precipitation despite large variations in inter-annual precipitation (CV = 19.9 %) and was most likely due to snow and frozen ground melting. The cumulative ET in the growing season was about 77 % of the annual ET. There was a nonlinear increase in the daily Priestley–Taylor coefficient (α = ET/ETeq, where ETeq is the equilibrium evaporation) with an increase in bulk surface conductance (gc), which was insensitive to increases in gc that exceeded 15 mm s−1. There was a good relationship between gc and NDVI. This study provides insights into the driving mechanisms of long-term variations in the energy partitioning and biophysical controls on ET in alpine meadow ecosystems.

Environmental factors contributing to variations in CO2 flux over a barley-rice double-cropping paddy field in the Korean Peninsula.

Understanding the CO2 flux over agricultural crop fields is critical because the temporal cycle is driven by both ecological environment and anthropogenic change. We analyzed the net ecosystem exchange of CO2 measured over a barley-rice double-cropping field using the eddy covariance method for 5years. We conducted gap-filling based on u*-threshold criteria and partitioned the net ecosystem exchange into gross primary production and respiration. The relative importance analysis of solar radiation, temperature, soil heat flux, soil water content, and vapor deficit revealed that solar radiation and temperature were the dominant contributors to net ecosystem exchange. The annual variation in the net ecosystem exchange followed a bimodal pattern driven by CO2 uptake by both barley and rice, displaying two negative peaks in late April and mid-August. The elongation stages of the crops exhibited the highest flux. Gross primary production and respiration were closely related to solar radiation and nighttime temperature, respectively. The relative importance of the other environmental variables was affected by the cultivation season and irrigation water. In the period of rice cultivation, respiration was approximately 3µmolm-2s-1 higher during rice drainage than during the flooded period. The accumulated net ecosystem production was estimated to be 315 gC m-2 and 349 gC m-2 for the barley and rice growing periods, respectively, and 649 gC m-2 for the annual total. These values are comparable with the results of other studies on barley-rice double-cropping fields.

Ground warming and permafrost degradation in various terrestrial ecosystems in northcentral Mongolia

AbstractTo detect the response of permafrost to climate change in various terrestrial ecosystems, we established a permafrost monitoring network in 2007, which includes eight boreholes to monitor ground temperatures in forest, meadow, steppe, moderately dry steppe, and wetland ecosystems and three Automatic Weather Stations (AWS) to monitor climatic factors, such as wind speed (Ws), air temperature (Ta), relative humidity (RH), precipitation (P), solar radiation (Rs), net radiation (Rn), soil heat flux (SHF), soil temperature (Ts), and soil water content (SWC), in forest, meadow, and steppe ecosystems in north‐central Mongolia. Major indicators, including mean annual ground temperature (MAGT), active layer thickness (ALT), and depth of zero annual amplitude (DZAA), were estimated to detect permafrost degradation. The results show that MAGT has increased by 0.00–0.02°C per year (almost no change) in the ice‐poor permafrost areas and by 0.03–0.06°C per year in the ice‐rich permafrost on pingos and wetlands. ALT showed an annual increase of −0.78 to 0.36 cm (almost no change) in the forest and meadow ecosystems and 2.3–7.2 cm in wetland ecosystems, whereas it increased by 23.0–28.9 cm per year in the steppe ecosystems over the last decade. This implies that the permafrost has degraded more rapidly in the steppe ecosystems than in other ecosystems. Based on correlation analysis, ALT is correlated to P in the meadow ecosystems and to SWC in the forest ecosystem, and MAGT is correlated to RH. However, both ALT and MAGT show a close correlation with major climatic factors, such as Ta, RH, SHF, and SWC in the steppe ecosystem. DZAA shows a close negative correlation with Ta in all ecosystems. These results provide evidence for permafrost degradation and its different responses to climate change in various terrestrial ecosystems.

Characteristics of Energy Distribution in a Desert Ecosystem in Inner Mongolia, Northern China

Desert ecosystems are vulnerable to climate change because of their fragile environment and poor self-regulation ability. Exploring the land–surface energy balance and the water/heat transfer processes of such regions for water resource management purposes is critical. The processes of surface water and heat transfer throughout the desert ecosystems and the effects of environmental factors on the energy distribution remain poorly studied. In this study, we used an eddy covariance system and surface meteorological data (2019–2021) to investigate the characteristics of the energy balance of Dengkou Desert ecosystem located in Inner Mongolia, northern China. Also, we evaluated the effects of different environmental factors on the energy distribution in this desert ecosystem. We found that the temporal patterns of both sensible heat flux (H) and latent heat flux (LE) with time are consistent with that of net radiation (Rn), and Rn is dominated by H. The sum of the daily average soil heat flux during the observation period was positive, indicating that soil was a heat sink and that the atmosphere transfers heat to the soil. During the observation period, the energy distribution of H/Rn fluctuated greatly, presenting a general U-shaped trend, while LE/Rn presented an inverted V-shaped trend. The main factor affecting H was Rn, followed by saturated vapor pressure, air temperature (Ta), and relative humidity. For LE, the main influencing factors were Ta, and Rn. The energy closure of the half-hour flux in the Inner Mongolian desert ecosystem during the observation period was 48%–68%, and the energy balance ratio was 0.54–0.74. The energy closure at the daily scale was higher than that at the half-hour scale, and the energy closure during daytime was higher than that at night.

Response of Seasonally Frozen Ground to Climate Changes in the Northeastern Qinghai-Tibet Plateau

The effects of climate change on permafrost have been well documented in many studies, whereas the effect of climate change on seasonally frozen ground (SFG) is still poorly understood. We used the observed daily freeze depth of SFG and environmental factors data from the period 2007–2016 to examine the seasonal and inter-annual variation of SFG. We quantitatively evaluated the effects of environmental factors on SFG using a boosted regression tree analysis. The results show that, on a seasonal scale, the lower layer soil frost starts freezing in mid-November, with the maximum freeze depth occurring in late March (209 cm), and then begins to thaw in both the lower and upper layers. We identified four stages of the freeze-thaw cycle: the non-frozen phase, initial freezing, deep freezing, and thawing. Furthermore, the thawing process of SFG mainly took place in the upper layer, but the freezing rate of the lower layer from mid-November to early February was similar to the thawing rate of late April to late June. On the inter-annual scale, the maximum freeze depth showed a significant increasing trend (p < 0.05). However, the freeze-thaw duration declined significantly (p < 0.05), which was correlated with the decrease in the period when surface soil temperature is below 0°C. The mean soil temperature and soil heat flux were the most important environmental indicators affecting seasonal variation of SFG depth, and the cumulative negative air and soil temperatures were the dominant factors affecting inter-annual variation of maximum freeze depth. Our results might provide insight into predicting hydrological and ecological responses to future climate change in frozen-ground regions.

The soil heat flux sensor functioning checks, imbalances' origins, and forgotten energies

Abstract. Soil heat flux is an important component of the surface energy balance (SEB) equation. Measuring it requires an indirect measurement. Every used technique may present some possible errors tied with the utilized specific technique, soil inhomogeneities, or physical phenomena such as latent heat conversion beneath the plates, especially in 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. A quick and easy way is to integrate results over 1 year. By consideration of the inert core internal energy conservation law, it is shown that the corresponding integration should be close to zero after a necessary geothermal heat efflux subtraction. However, below-plate evaporation and vegetation-absorbed water or rainwater infiltration may also contribute to the observed short-scale and/or long-scale imbalance generating convective heat fluxes not sensed by the heat flux sensors. Another energy source is usually not included in the SEB equation: rainfall or irrigation. Yet its importance for short- and long-term integration is notable. As an example, the most used sensor, soil heat flux plates (SHFPs), is given.

CLM5-FruitTree: a new sub-model for deciduous fruit trees in the Community Land Model (CLM5)

Abstract. The inclusion of perennial, woody crops in land surface models (LSMs) is crucial for addressing their role in carbon (C) sequestration, food production, and water requirements under climate change. To help quantify the biogeochemical and biogeophysical processes associated with these agroecosystems, we developed and tested a new sub-model, CLM5-FruitTree, for deciduous fruit orchards within the framework of the Community Land Model version 5 (CLM5). The model development included (1) a new perennial crop phenology description, (2) an adapted C and nitrogen allocation scheme, considering both storage and photosynthetic growth of annual and perennial plant organs, (3) typical management practices associated with fruit orchards, and (4) the parameterization of an apple plant functional type. CLM5-FruitTree was tested using extensive field measurements from an apple orchard in South Tyrol, Italy. Growth and partitioning of biomass to the individual plant components were well represented by CLM5-FruitTree, and average yield was predicted within 2.3 % of the observed values despite low simulated inter-annual variability compared to observations. The simulated seasonal course of C, energy, and water fluxes was in good agreement with the eddy covariance (EC) measurements owing to the accurate representation of the prolonged growing season and typical leaf area development of the orchard. We found that gross primary production, net radiation, and latent heat flux were highly correlated (r>0.94) with EC measurements and showed little bias (<±5 %). Simulated respiration components, sensible heat, and soil heat flux were less consistent with observations. This was attributed to simplifications in the orchard structure and to the presence of additional management practices that are not yet represented in CLM5-FruitTree. Finally, the results suggested that the representation of microbial and autotrophic respiration and energy partitioning in complex, discontinuous canopies in CLM5 requires further attention. The new CLM5-FruitTree sub-model improved the representation of agricultural systems in CLM5 and can be used to study land surface processes in fruit orchards at the local, regional, or larger scale.

Time scale and influencing factor variations of water and heat fluxes in sandy land

Abstract The transfer process and variation characteristics of water and heat fluxes play an important role in both the ecosystem function and the climatic patterns of arid and semi-arid areas. However, both water (latent heat flux, Fe) and heat (sensible heat flux, Fh) fluxes, and the factors impacting each, operate on different time scales. Therefore, the wavelet transformation was used to reconstruct water and heat flux data measured by an eddy covariance system installed in Horqin sandy land, China. The distribution and response regularity of water and heat fluxes in response to control factors were then analysed across different time scales. The results indicated that the responses of Fe and Fh to controlling factors were similar on 30 min and daily scales, to which the energy terms of net radiation (Fn) and available energy (Fa) showed an extremely significant positive contribution. Removing the interference of the energy terms, Fe and Fh are strongly correlated with the vapour pressure deficit (VPD) and air temperature (Ta) at the daily scale. The water conditions of VPD and relative humidity (RH) were the main influencing factors at the monthly scale. At the seasonal scale, Fe was positively correlated with Fa and Fn but negatively correlated with soil heat flux (Fg), RH and wind speed (WS). On the contrary, Fh was positively correlated with RH but negatively correlated with Fn. At the annual scale, Fe and Fh showed a significant positive correlation with all factors. By the increasing time scale, the cross-correlations between various hydroclimatic processes become better. Generally, at the daily and annual scales, there is a high correlation between Fe, Fh and the control factors, and a pronounced periodicity is exhibited. Another factor that is known to cause such effects is the so-called long-term persistence (or else long-range dependence or the Hurst phenomenon). These results suggest that the time scales of flux and impacting factors should be considered when undertaking water and heat flux analyses of sandy land and other ecosystems.

Energy Balance, Microclimate, and Crop Evapotranspiration of Winter Wheat (Triticum aestivum L.) under Sprinkler Irrigation

Understanding the impact of sprinkler irrigation on field energy balance, microclimate, and crop evapotranspiration is of great importance for optimizing irrigation scheduling and enhancing crop growth. In this study, the microclimate variables, energy, and water flux were measured using an eddy covariance system during four wheat (Triticum aestivum L.) growing seasons in a sprinkler-irrigated field of North China Plain. The variation patterns of microclimate, energy balance (net solar radiation Rn, soil heat flux G, latent heat LE, and sensible heat H) and crop evapotranspiration (ET) were analyzed during and after sprinkler irrigation events. A novel quantitative model using a stepwise regression method was developed to predict the change in microclimate after sprinkler irrigation by considering irrigation, weather, meteorology, and crop traits. The results showed that the reflectance rate of the wheat canopy decreased by 0.01, and the daily LE/Rn increased by 0.19–0.23 in the 1–3 days after sprinkler irrigation with 40–50 mm water, which finally resulted in crop ET increased by 1.8–4.7 mm during irrigation interval, and seasonal total ET could increase by 9–24 mm when five normal sprinkler irrigations were implemented in a wheat season. The mean daily H/Rn decreased by 0.06–0.17, indicating weak energy exchange between canopy and environment. The measured daily minimum (Tmin), maximum temperatures (Tmax) and daily mean vapor pressure deficit (VPD) decreased by approximately 0.8 °C, 0.9 °C, and 0.25 kPa, respectively, and daily mean relative humidity increased by approximately 7.5% on the first 3 days after sprinkler irrigation; and these changes decreased and were negligible on the 5th–7th days. The decreases in daily Tmin, Tmax, and mean VPD after sprinkler irrigation could change more under higher irrigation amounts and sunny days with a larger crop leaf area index based on the fitted models.

Comparison of the Forecast Performance of WRF Using Noah and Noah-MP Land Surface Schemes in Central Asia Arid Region

The land surface scheme (LSS) plays a very important role in the forecast of surface meteorological elements in the Central Asia arid region. Therefore, two LSSs viz. Noah and Noah-MP were evaluated over the Central Asia arid region in January and July 2017 using the Weather Research and Forecasting (WRF) model at a 3-km horizontal grid resolution. The objective was to assess the performance of WRF LSSs by calculated the mean error (ME) and the root mean squared error (RMSE) of simulated hourly meteorological elements, such as 2-m air temperature, 10-m wind speed, soil temperature, soil moisture at 5 and 25 cm thickness, and surface soil heat flux at 5 cm thickness. The results showed that, compared to Noah, Noah-MP modeled less surface sensible heat flux in the northern Xinjiang (15~20 W∙m−2) and surface latent heat flux in most areas of Xinjiang (<10 W∙m−2) in January, and mainly generated less sensible heat flux in most areas of north Xinjiang and the mountainous regions of southern Xinjiang (≤20 W·m−2) which on the contrary, generated more surface latent heat flux in most parts of Xinjiang (15~20 W·m−2) in July. Meanwhile, the surface soil heat flux generated from Noah-MP was closer to the observations at Hongliuhe and Kelameili stations in January, the ME increased by 17.5% and reduced by 80.7%, respectively, the RMSE decreased by 44.4% and 61.7%, respectively, and closer to the observations at Xiaotang station in July, the ME and RMSE reduced by 19.1% and 20.5%, respectively. Compared to Noah, Noah-MP improved the overall simulation of soil temperature and soil moisture over the northern and eastern Xinjiang (at 10 cm thickness), the ME and RMSE of simulated soil temperature reduced by 85.0% and 13.4% in January, decreased by 78.6% and increased by 6.2% in July, respectively, and the ME and RMSE of simulated soil moisture reduced by 67.2% and 14.9% in January, reduced by 33.3% and 2.8% in July, respectively. Compared to Noah, Noah-MP’s results were lowered for the simulated 10-m wind speed and 2-m air temperature, especially the simulated 2-m air temperature over the cold climate regions of northern Xinjiang, was improved significantly, the ME and RMSE of simulated 10-m wind speed reduced by 0.8% and 4.9% in January, decreased by 6.7% and 2.8% in July, respectively, the ME and RMSE of simulated 2-m air temperature reduced by 2.8% and 1.0% in July, respectively. This study demonstrated the advantage of coupled Noah-MP over the Central Asia arid region, providing the basis for WRF/Noah-MP in future operational applications in the Central Asia arid region.

Research on the Characteristics of Surface Flux and Surface Parameters of Meadow Underlying Surface in the Source Region of Yellow River

Based on observation data from January 1st to December 31st in 2014 at Maduo Site, which is located near the Yellow River source area in the Qinghai-Tibet Plateau, this research examined how the surface flow of alpine meadow underlying surface varies. The applicability of the land-surface process models CLM5.0 and CLM4.5 in alpine grassland was also tested. The findings revealed that total radiation in the Yellow River source area was lower in the winter but quickly increased after mid-March, peaked in June or July, and then gradually decreased. The surface reflected radiation was affected by both the total radiation and surface albedo. Its seasonal variation showed different characteristics than the total radiation. Due to the snow on the surface, the short-wave radiation reflected by the surface was larger in winter, while the surface reflected radiation in summer was relatively small, especially after the rainy season. Long-wave surface radiation followed the same seasonal pattern as air counter radiation, with a low point in winter and a high point in summer. Due to cloud cover and other variables, however, long-wave surface radiation was larger than atmospheric counter radiation. The sensible heat flux and net radiation varied similarly until July (rainy season), but after July, the latent heat flux and net radiation followed the same pattern until the soil was frozen in early November. For the whole year, the study of regional surface flux was mainly focused on latent heat flux. Corresponding to sensible heat and latent heat, the daily average of soil heat flux was above 0 from mid-March to late August, which meant that the soil heat flux was transmitted from the surface soil to the deep layer, while the rest of the time showed a negative, with soil heat flux transmitted from the deep layer to the surface soil. In late March, the daily average heat flux of soil was abnormally large, which was related to the melting of frozen soil. Generally, for the whole year, soil heat flux was transmitted from the deep layer to the surface soil. The simulation results of CLM5.0 and CLM4.5 for radiation flux and surface heat flux are very close to the observed values, especially CLM5.0. This indicates that the simulation effect of the model in Alpine Grassland in the source region of the Yellow River has been significantly improved after improving many parameterization schemes and dynamic processes in CLM5.0. However, the soil freezing and thawing process and snow parameterization scheme in CLM need to be further improved. Generally, the daily average CO2 flux during the frozen period of soil was 0. In May, September, and October, the respiration of alpine meadows dominated, surface releasing CO2, while in early and middle June, photosynthesis played the leading role, surface absorbing CO2. During the period from late June to mid-August, when both the moisture and temperature of soil were higher, and the surface vegetation experienced rapid growth, the daily average CO2 flux increased sharply. On the contrary, when the frozen soil melted, the CO2 flux released by the surface increased significantly.

An atmospheric and soil thermal-based wheat crop coefficient method using additive crop growth models

Accurate crop evapotranspiration simulation is vital for reasonable irrigation planning. The two-step method for crop evapotranspiration estimation has been widely used for irrigation water demand management. However, in the two-step method, the crop coefficient (Kc) is typically taken as a constant in crop growth stages, which may result in a certain error in evapotranspiration estimation. It is of significance to estimate Kc accurately for effective water resources management. Based on three-year lysimeter experimental data collected from the Wudaogou Station for Hydrology and Water Resources, this study proposes a thermal-based Kc method for actual crop evapotranspiration estimation. The proposed thermal-based Kc method uses air temperature and soil heat flux as input variables, which could mainly characterise the thermal effect on crop growth from the atmosphere and soil. Results showed that the proposed method is effective in estimating Kc. The estimated Kc highly correlates with actual Kc values, which are derived from lysimeter observation, with correlation coefficient above 0.87 and Nash-Sutcliffe efficiency above 0.70. The proposed method could estimate Kc daily, which can be used to estimate crop evapotranspiration accurately.

Transpirational cooling and physiological responses of trees to heat

Heatwaves cause severe adverse effects on urban human life. Green spaces that cool the urban environment through shading and transpiration can improve the urban thermal environment. However, there is currently a lack of quantitative evaluation of the transpirational cooling effect and physiological response of trees to heat. Therefore, this exploratory study investigated two pairs of trees (Cinnamomum camphora and Cedrus deodara), which are commonly used for urban greening in Nanjing, China. Transpirational cooling was estimated using the heat diffusion method for xylem sap flow in four trees. The morphological characteristics and environmental factors of each forest land were measured, and the transpirational cooling of the four trees was analyzed statistically. The results indicated that the canopy transpriation of C. deodara samples decreased substantially during extreme heat days. At the unit leaf area scale, the transpirational cooling effect of C. camphora samples was more pronounced than that of C. deodara samples during extreme heat days. Water vapor pressure and soil heat flux at 20 cm underground were the main drivers affecting the canopy transpiration of C. camphora samples, whereas air temperature and soil temperature at 5 cm underground were the main drivers affecting the canopy transpiration of C. deodara samples. To analyze the physiological cooling effects of trees, a new index (Transpirational Cooling Efficiency, TCE) is proposed to quantitatively evaluate the relationship between tree transpirational cooling and sap flow. The findings of this study may enrich the response patterns of trees to transpiration under extreme heat and provide guidance for the planning and designing of green spaces to improve thermal environments.

A Hybrid Bulk Algorithm to Predict Turbulent Fluxes over Dry and Wet Bare Soils

Abstract Measurements made in the Columbia River basin (Oregon) in an area of irregular terrain during the second Wind Forecast Improvement Project (WFIP2) field campaign are used to develop an optimized hybrid bulk algorithm to predict the surface turbulent fluxes from readily measured or modeled quantities over dry and wet bare or lightly vegetated soil surfaces. The hybrid (synthetic) algorithm combines (i) an aerodynamic method for turbulent flow, which is based on the transfer coefficients (drag coefficient and Stanton number), roughness lengths, and Monin–Obukhov similarity; and (ii) a modified Priestley–Taylor (P-T) algorithm with physically based ecophysiological constraints, which is essentially based on the surface energy budget (SEB) equation. Soil heat flux in the latter case was estimated from measurements of soil temperature and soil moisture. In the framework of the hybrid algorithm, bulk estimates of the momentum flux and the sensible heat flux are derived from a traditional aerodynamic approach, whereas the latent heat flux (or moisture flux) is evaluated from a modified P-T model. Direct measurements of the surface fluxes (turbulent and radiative) and other ancillary atmospheric/soil parameters made during WFIP2 for different soil conditions (dry and wet) are used to optimize and tune the hybrid bulk algorithm. The bulk flux estimates are validated against the measured eddy-covariance fluxes. We also discuss the SEB closure over dry and wet surfaces at various time scales based on the modeled and measured fluxes. Although this bulk flux algorithm is optimized for the data collected during the WFIP2, a hybrid approach can be used for similar flux-tower sites and field campaigns.