Net Radiation Research Articles

Enhancing Winter Wheat Representation in Noah‐MP‐Crop for Improved Dynamic Crop Growth Simulation in the North China Plain

AbstractExplicitly representing the world's most frequently cultivated winter wheat in land surface model (LSM) is important for understanding carbon and energy cycling over cropland and its interactions with climate, which is crucial for global food security. However, in the latest version of Noah‐MP‐Crop LSM, winter wheat is significantly underrepresented. This study improved the winter‐wheat parameterization in Noah‐MP‐Crop model by optimizing the phenological scheme, incorporating vernalization process, and calibrating several key parameters associated with winter wheat photosynthesis and carbon allocations. Focusing on the North China Plain as area representative region, model performance in simulating crop dynamic growth, carbon flux, and energy fluxes was validated at both site and regional scales. Results showed that the simulated phenological development matched well with the real‐world phenological records. A comparison between the simulated results by the default and developed parameterizations revealed the significant improvements in the reproductions of leaf area index (LAI) and gross primary production (GPP). The determination coefficient (R2) value of GPP was increased from 0.15 to 0.46 to 0.39–0.91. Simulations of energy fluxes showed smaller improvements, with R2 values increasing from 0.46 to 0.67 to 0.61–0.84 for latent heat (LE) and 0.18–0.55 to 0.25–0.61 for sensible heat. Additionally, the mean average error of net radiation was reduced. Improvements in spatial and temporal variations of LAI, GPP, and LE in regional simulation were also observed. This work can facilitate incorporating winter wheat cultivation and its interactions with climate system, particularly when coupling the Noah‐MP‐Crop model with the widely used Weather Research and Forecasting model.

Drivers of the mean biases of the tropical atmospheric circulation in a moist static energy framework

In this study, we apply the moist static energy for first baroclinic mode (MSEB) model to examine the drivers of the mean tropical atmospheric circulation biases over oceanic regions. The model diagnoses the vertical motion in an air column of the tropical regions based on net energy heat flux and advection of moisture or heat into the air column in relation to the stability of the air column due to the gradients in moist static energy. Analysis of Coupled Model Intercomparison Project (CMIP) and Atmospheric Model Intercomparison Project (AMIP) simulations helped to identified errors intrinsic to the atmospheric models or errors due to atmosphere–ocean coupling process. Despite some limitations of the MSEB model, our multi-model mean analysis over the entire tropical ocean reveals that the primary drivers of the tropical circulation biases mostly result from intrinsic atmospheric model errors in top of the atmosphere longwave radiation and surface latent heats fluxes, suggesting a link to biases in the hydrological cycle. Oceanic coupling significantly enhanced some of the biases. Biases in the advection of moist static energy also play an important role, while biases in the gross moist stability profiles play only a minor role. Further, we examine the inter-model variations in four main regional large-scale biases (double-ITCZ, Pacific cold tongue, southward shift of ITCZ over the Atlantic, and dipole bias over the Indian Ocean). The analysis suggests that regional bias patterns across general circulation models are primarily driven by coupling errors, except for the bias in the Indian Ocean, which is intrinsic to the atmospheric model but amplified by coupling. Notably, longwave radiation biases at the top of the atmosphere are prevalent among the four bias patterns, as well as biases in moisture advection over the Atlantic. Our results underscore the significant role of net longwave radiation at the top of the atmosphere, an aspect not sufficiently emphasized in previous studies.

The energy-limited water loss of an alpine shrubland on the northeastern Qinghai-Tibetan Plateau, China

Study regionAlpine shrubland on the northeastern Qinghai-Tibetan Plateau. Study focusWater provision ability is a pivotal ecological service of high-altitude alpine regions and is controlled by precipitation, evapotranspiration (ET), and soil water storage whereas the underlying ecohydrological processes remain highly unquantified. Here, we investigated continuous 19-year flux measurements to quantify the temporal patterns of ET and water budget (precipitation minus ET, P−ET), as well as 0-20 cm soil water storage change (ΔSWS). New hydrological insights for the regionAt a monthly scale, ET peaked in July (96.7 ± 26.4 mm, Mean ± S.D.) and averaged 41.7 ± 31.9 mm, whose variations were determined by the slope of the saturation vapor pressure curve at air temperature, air and soil temperatures, regardless of vegetation growth stage. P−ET averaged 18.3 ± 26.3 mm in August and September while stayed deficit during the other months. The variations in P−ET were controlled by precipitation in the May-October growing season whereas by ET in the non-growing season from November to April. ΔSWS peaked in May (28.8 ± 11.2 mm) and September (3.0 ± 2.7 mm) and almost accumulated to zero over the whole season. At annual scales, none of ET, P−ET, and ΔSWS changed significantly. ET averaged 512.2 ± 68.4 mm and exceeded precipitation (459.1 ± 58.4 mm), likely due to the lateral flow supply of uphill locations. The variations in ET were regulated directly by bulk canopy resistance and indirectly by net radiation. P−ET averaged −53.2 ± 95.4 mm and demonstrated a clear water deficit (−51.6 ± 21.0 mm) during the non-growing season. The variations of P−ET were driven jointly by precipitation and ET, with opposite but equivalent effects. The dominance of thermal conditions and energy availability on ET variability manifested an energy-limited feature of water loss in the alpine shrubland. The temporal patterns in P−ET elucidated that the alpine shrubland plays the water retention rather than water provision function through transforming variable precipitation input into stable ET loss.

Mechanism for compound daytime-nighttime heatwaves in the Barents–Kara Sea during the boreal autumn and their relationship with sea ice variability

The frequency of heatwaves in the Arctic is on the rise under global warming. These occurrences not only profoundly impact the local ecological environment but also exert remote effects on East Asia and even the global climate. Yet, there exists a noticeable dearth of research focus on Arctic compound daytime-nighttime heatwaves, limiting our comprehension of Arctic climate dynamics. We investigated the occurrence and extinction mechanism for compound daytime-nighttime heatwaves in the Barents–Kara Sea (BKS) during the boreal autumn and explored their association with the sea ice variability. Our results show that a significant dipole pattern appears in the geopotential height two days before the occurrence of compound daytime-nighttime heatwaves in the BKS during autumn, characterized by a negative anomaly centered over Greenland and a positive anomaly centered over the BKS. A robust southerly anomaly in the middle of this dipole pattern facilitates the continuous inflow of warm, moist air from the Atlantic Ocean to the BKS. Both the strong intrusion of moisture and the transport of heat (positive temperature advection) driven by the large-scale atmospheric circulation increase downward latent heat flux, sensible heat flux and net longwave radiation. These factors collectively increase the near-surface temperature over the BKS, ultimately leading to the occurrence of compound daytime-nighttime heatwaves in this region of the Arctic. The extinction of compound daytime-nighttime heatwaves in the BKS is a result of the weakening of the transport of heat and intrusion of water vapor caused by changes in the large-scale circulation. The intrusion of water vapor and the transport of heat significantly reduce the sea ice concentration in most of the BKS. This reduction in sea ice persists for an additional day after the termination of compound daytime-nighttime heatwaves in the BKS. A process of positive atmospheric temperature feedback on a sub-monthly scale may potentially influence the maintenance of compound daytime-nighttime heatwaves in the BKS during the boreal autumn.

Temporal patterns of carbon-water coupling of a subalpine peatland in subtropics: Insights from a seven-year eddy covariance monitoring

Study regionA well-preserved subalpine peatland in the subtropics, the Dajiuhu peatland, in Shennongjia, Hubei Province, China. Study focusOver a seven-year period, constant in-situ carbon flux monitoring was conducted using the eddy covariance method. The patterns of CO2 and H2O fluxes were analyzed, encompassing both daytime and nocturnal period observations, spanning both growing and non-growing seasons, and the interconnection between carbon and water within the Dajiuhu peatland. Furthermore, this investigation identified meteorological parameters shaping these flux dynamics. New hydrological insights for the regionThe water source function was more resilient to the effects of extreme weather events and showed higher stability when compared to the carbon sink function. Daytime carbon-water coupling presented a pronounced negative correlation during the growing season, contrasting with a more complex trinomial relationship evident during the non-growing season; however, nocturnal periods did not reveal any apparent correlation. Relative humidity (RH), water table depth (WTD), and evapotranspiration (ET) emerged as key variables impacting jointly on both CO2 and H2O fluxes. Furthermore, net radiation (Rn) magnifies the hysteresis loops associated with net ecosystem exchanges of CO2 (NEE) during the growing season, with WTD being the prime determinant influencing seasonal fluctuations in hysteresis related to H2O fluxes. These findings exemplify the complexities inherent in the management of carbon and water resources within subalpine peatlands, underscored by their intricately intertwined and inseparable relationship.

Can changes in land use in a semi-arid region of Brazil cause seasonal variation in energy partitioning and evapotranspiration?

Changes to forests due to deforestation, or their replacement by agricultural areas, alter evapotranspiration and the partitioning of available energy. This study investigated seasonal variations in the energy balance and evapotranspiration in landscapes under different levels of anthropogenic intervention in the semi-arid region of Brazil. Micrometeorological data was obtained from September 2020 to October 2022 for three areas of the semi-arid region: preserved Caatinga (CAA, native vegetation), Caatinga under regeneration (REGE) and a deforested area (DEFA). Here, we use the Bowen ratio energy balance method. Measurements were taken of global solar radiation, air temperature, relative humidity, vapour pressure deficit, rainfall, net radiation, latent heat flux, sensible heat flux, soil heat flux, evapotranspiration, volumetric soil water content and Normalised Difference Vegetation Index. Sensible heat flux was the dominant flux in both areas with 66% for preserved Caatinga vegetation, 63% for Caatinga under regeneration and 62% deforested area. The latent heat flux was equivalent to 28% of the net radiation for preserved Caatinga vegetation, Caatinga under regeneration and deforested area. The evapotranspiration in turn responded as a function of water availability, being higher during the rainy seasons, with average values of 1.82 mm day−1 for preserved Caatinga vegetation, 2.26 mm day−1 for Caatinga under regeneration and 1.25 mm day−1 for deforested area. The Bowen ratio presented values > 1 in deforested area, preserved Caatinga vegetation and Caatinga under regeneration. Thus, it can be concluded that the change in land use alters the energy balance components, promoting reductions in available energy and latent and sensible heat fluxes during the rainy-dry transition in the deforested area. In addition, the seasonality of energy fluxes depends on water availability in the environment.

Significance of anthropogenic black carbon in modulating atmospheric and cloud properties through aerosol-radiation interaction during a winter-time fog-haze

The present study investigated the aerosol-radiation-cloud interaction of anthropogenic black carbon (BC) during a severe fog-haze event by utilizing WRF-Chem, multi-satellite and in-situ observations, reanalyses datasets, and HYSPLIT model. The WRF-Chem model adequately captured the regional distribution of aerosol, cloud, and meteorological variables over the study domain. The maximum BC surface concentration (≥7 μg m−3) was predominantly evident over densely populated central and lower Indo-Gangetic Plain (IGP) regions. Although smoke aerosols usually persisted within 4 km above the surface at daylight hours, they reached as high as 6 km during nighttime, specifically over the central IGP regions. The heavily influenced areas by BC aerosols expanded to almost the entire landmass and the continental outflow region upon doubling the anthropogenic emission. The geographical distribution of maximum perturbations in net shortwave radiation flux at the surface closely matched the spatial patterns of the highest BC concentration, indicating a crucial role of BC in directly preventing the incoming sunlight from reaching the surface. Consequently, the reduced solar radiation at the ground might result in substantial surface cooling (between −0.3 and −0.5 °C), eventually prohibiting surface evapotranspiration and diminishing the outgoing sensible and latent heat fluxes. Also, more amplified cooling in the polluted atmosphere can prevent further development of the planetary boundary layer (PBL), increasing particle entrapment near the surface via an ‘aerosol-radiation-PBL’ feedback loop. However, the most striking contrast between the two scenarios (typical and polluted) was the prolonged and intensified warming (0.5–0.8 °C) in the mid-troposphere, causing a remarkable drop in moisture (more than two to three times) and hence burn-off of liquid cloud droplets due to the semi-direct effect of increased BC aerosols. The intense mid-tropospheric heating could remarkably enhance the updraft velocity, supporting the vertical transport of the additional moisture to higher altitudes, forming more ice clouds at night. Therefore, the current study highlighted the urgency of mitigating anthropogenic BC emissions in highly polluted regions since increased emissions could considerably worsen severe fog-haze conditions and influence both liquid water and ice clouds, depending on the atmospheric conditions.

The Varied Role of Atmospheric Rivers in Arctic Snow Depth Variations

AbstractThe state and fate of snow on sea ice are crucial in the mass and energy balance of sea ice. The function of atmospheric rivers (ARs) on snow depth over sea ice has not been measured thus far, limiting the understanding of the mechanism of snow depth changes. Here, the effect of ARs on snow depth changes was explored. We found that increased AR frequency is responsible for winter‐autumn snow accumulation and spring‐summer snow melting. The 2 m air temperature (T2m), rainfall, snowfall, mean net longwave radiation (NLR), mean net shortwave radiation (NSR) and cloud radiative effect (CRE) during ARs explain the changes in snow depth triggered by AR occurrence. This work helps us understand how ARs affect snow depth changes through related physical processes, promotes an understanding of climate systems and provides a theoretical basis for snow treatment in sea ice models.

Interdecadal variability of winter and spring Eurasian snow depth and its impact on Eastern China precipitation

Empirical orthogonal function (EOF) and correlation analyses were employed to investigate the winter and spring snow depth in Eurasia and its relationship with Eastern China precipitation based on the observed and reanalyzed data from 1980 to 2016. The results show that the winter and spring snow cover in Eurasia not only highlights a decreasing trend due to global warming (the first EOF mode, its variance accounted for 24.4% and 22.6% of the total variance) but also exhibits notable interdecadal variation (the second EOF mode, its variance accounted for 10.2% and 11.5% of the total variance). The second EOF mode of winter snow depth in Eurasia is characterized by a west-east dipole pattern. It was observed that the spatial correlation pattern between the EOF2 of Eurasian snow depth and summer precipitation in China closely resembles the meridional quadrupole structure of the third EOF mode of summer precipitation in China. This pattern is characterized by excessive rainfall in Northeast China and the lower-middle reaches of the Yangtze River, and less rainfall over the Yellow River basin and southern China. The EOF mode of spring snow depth not only reflects the declining trend but also regulates precipitation in Eastern China. The possible mechanisms by which snow depth causes changes in soil moisture and subsequently affects atmospheric circulation are then explored from the perspective of the hydrological effects of snow cover. Decreased (Increased) snow depth in Eurasia during the winter and spring directly leads to diminished (increased) soil moisture while increasing (decreasing) net radiation and sensible heat flux at the surface. The meridional distribution of surface temperature also exhibits a dipole pattern, leading to enhanced subtropical westerly jet in the upper troposphere. The Eurasian snow cover anomalies pattern triggered an anomalous mid-latitude Eurasian wave train, which strengthened significantly in the Western Siberian Plain. It then splits into two branches, one continuing to propagate eastward at high latitudes and the other shifting towards East Asia, thereby impacting precipitation in Eastern China. This work indicates that the second EOF mode of Eurasian snow cover can impact the precipitation variability in Eastern China during the same period and in summer on an interdecadal scale.

Effect of wind speed and net radiation on the oasis effect in temperate rice paddy fields

Effect of wind speed and net radiation on the oasis effect in temperate rice paddy fields

Distribution, relationship, and environmental driving factors of chlorophyll-a and algal cell density: A national view of China

Chlorophyll-a (Chl-a) and algal cell density (ACD) are vital for assessing algal proliferation and eutrophication in aquatic ecosystems. Although Chl-a is often used as a proxy for ACD, its accuracy requires validation, and studies on their linear correlation are scarce. Additionally, Chl-a and ACD are influenced by various factors, including nutritional, economic, biochemical, physicochemical, and meteorological factors. However, the relative importance of these factors on Chl-a and ACD remains insufficiently studied. This study analyzed data from 57 lakes and reservoirs across China from March 2021 to February 2023, investigating the distribution patterns of Chl-a and ACD across different regions and seasons. The study employed a linear regression model to explore the correlation between Chl-a and ACD in various regions and seasons throughout China. Furthermore, Mantel test and generalized linear model were used to evaluated the relative importance of nutritional factors (total nitrogen (TN), total phosphorus (TP), TN/TP ratio (TN/TP), and ammonia nitrogen (NH3-N)), economic factors (gross domestic product), meteorological factors (surface pressure, net solar radiation, air temperature, wind speed (WS), and rainfall (RF)), as well as biochemical and physicochemical factors (turbidity (TUR), pH value, water temperature (WT), permanganate index, and dissolved oxygen) on Chl-a and ACD. Results showed that the average concentrations of Chl-a and ACD in South China were highest, at 12 μg/L and 19.5 × 106 cells/L, respectively. Seasonally, Chl-a peaked in spring and was lowest in winter, while ACD peaked in summer and was lowest in winter. Significant seasonal and regional variations in the Chl-a and ACD correlation were observed, with spring showing the strongest relationship. In Central China, Chl-a and ACD were significantly correlated throughout the four seasons, whereas correlations were less distinct in Eastern and Western regions. Therefore, Chl-a as a proxy for ACD requires caution. Nutrient factors (TN, TP, TN/TP, NH3-N) were identified as the primary drivers of Chl-a and ACD. Meteorological factors (WS, RF), along with biochemical and physicochemical factors (WT, TUR) also emerged as critical predictors of Chl-a and ACD, with spatial variations. This study validates Chl-a as a proxy for ACD, analyzes their spatiotemporal distribution, and assesses the influence of various factors on Chl-a and ACD, enhancing our understanding of algal dynamics in Chinese lakes and reservoirs.

Interruption characteristic of 3%C5F10O/97%CO2 gas mixture in a 40.5 kV circuit breaker

The C5F10O/CO2 gas mixture is one of the most promising SF6 alternative gases at the present stage, which was initially applied in high-voltage electrical equipment. This paper mainly studies the interruption performance of 3%C5F10O/97%CO2 gas mixture (k = 3%) with a charging pressure of 0.6 MPa in high-voltage circuit breakers. First, the thermodynamic parameters, transport coefficient, and net radiation coefficient were calculated for k = 3%. On this basis, a 40.5 kV circuit breaker was used as a prototype to establish the magnetohydrody-namic model for breaking 20 kA short-circuit current, and the arc temperature and pressure distribution in the arc extinguishing chamber of the circuit breaker were calculated. The LC oscillation circuit was used to build an arc-extinguishing characteristic test platform to verify the accuracy of the numerical calculation. Finally, based on the Mayr arc model and the critical electric field strength, the post-arc thermal breakdown and electrical breakdown characteristics of SF6, CO2, and k = 3% were quantitatively analyzed. The results show that under 0.6 MPa, the thermal breakdown performance of k = 3% is about 89.7% of SF6, which is nearly twice higher than that of CO2 and has better thermal breaking ability. The electrical breakdown performance of k = 3% is about 20.4% of SF6, and the probability of electrical breakdown in the front end of the fixed contact is high. This problem should be paid attention to in the design of high-voltage circuit breakers. This study can provide a reference for the development and optimization of environmentally friendly high-voltage circuit breakers.

Heat the road again! Twenty years of surface urban heat island intensity (SUHII) evolution and forcings in 21 tropical metropolitan regions in Brazil from remote sensing analyses

This study analysed the influence of urbanisation on the expansion of surface urban heat island intensities (SUHIIs) and the variability of biophysical parameters in twenty one major Brazilian Metropolitan Regions (MRs), from 2003 to 2022. We use land surface temperature (LST) data from MODIS sensors to continuously quantify the daytime and night-time SUHIIs. Spectral reflectance and re-analysis data were used to access the variability of Enhanced Vegetation Index-2 (EVI2), surface albedo (α), urban area (UA) growth, net surface radiation (Rn), and actual evapotranspiration (ET). The Mann-Kendall trend test was applied to all variables and their relationships with LST were investigated using statistical metrics. The results show that the SUHIIs were 60 % (1.64 °C) higher during the daytime than during the night, with significant growth trends throughout the studied period and more pronounced monthly seasonal variations in higher latitude MRs. The UAs are shown to be more influential on LST during the daytime, with the association of LST with EVI2 and α playing a fundamental role in regulating the urban climate. The results also demonstrate that increasing ET potentially mitigates LST, especially during the daytime. For the night-time, Rn is a stronger factor influencing LST, leading to the higher availability of sensible heat.

A Cross-Resolution Surface Net Radiative Inversion Based on Transfer Learning Methods

Net radiation (Rn) is a key component of the Earth’s energy balance. With the rise of deep learning technology, remote sensing technology has made significant progress in the acquisition of large-scale surface parameters. However, the generally low spatial resolution of net radiation data and the relative scarcity of surface flux site data at home and abroad limit the potential of deep learning methods in constructing high spatial resolution net radiation models. To address this challenge, this study proposes an innovative approach of a multi-scale transfer learning framework, which assumes that composite models at different spatial scales are similar in structure and parameters, thus enabling the training of accurate high-resolution models using fewer samples. In this study, the Heihe River Basin was taken as the study area and the Rn products of the Global Land Surface Satellite (GLASS) were selected as the target for coarse model training. Based on the dense convolutional network (DenseNet) architecture, 25 deep learning models were constructed to learn the spatial and temporal distribution patterns of GLASS Rn products by combining multi-source data, and a 5 km coarse resolution net radiation model was trained. Subsequently, the parameters of the pre-trained coarse-resolution model were fine-tuned with a small amount of measured ground station data to achieve the transfer from the 5 km coarse-resolution model to the 1 km high-resolution model, and a daily high-resolution net radiation model with 1 km resolution for the Heihe River Basin was finally constructed. The results showed that the bias, R2, and RMSE of the high-resolution net radiation model obtained by transfer learning were 0.184 W/m2, 0.924, and 24.29 W/m2, respectively, which was better than those of the GLASS Rn products. The predicted values were highly correlated with the measured values at the stations and the fitted curves were closer to the measured values at the stations than those of the GLASS Rn products, which further demonstrated that the transfer learning method could capture the soil moisture and temporal variation of net radiation. Finally, the model was used to generate 1 km daily net radiation products for the Heihe River Basin in 2020. This study provides new perspectives and methods for future large-scale and long-time-series estimations of surface net radiation.

Analysis of Carbon Flux Characteristics in Saline–Alkali Soil Under Global Warming

ABSTRACTThe carbon cycle of saline–alkali ecosystems will be affected to some extent in the context of future global warming. Therefore, we investigated the net ecosystem exchange (NEE) of three typical crops (wheat, maize and soybean) in the saline–alkaline land of the Yellow River Delta. To further investigate CO2 fluxes, NEE was decomposed into gross primary productivity (GPP) and ecosystem respiration (Re). In terms of seasonal variation, wheat and soybean were carbon sources in the early and late growth periods, and carbon sinks in the rest of the period, whereas maize was a carbon sink in the majority of the period, and maize had good carbon sink potential. The cumulative NEE during the growth periods for wheat, maize, and soybean were 414.86, 258.24 and 228.92 g cm−2, respectively, and the daily variation showed that the peak NEE values for the three crops preceded the peak values of both GPP and ecosystem respiration, occurring approximately at 12:00 a.m. In the correlation analysis, NEE and GPP of the three crops were well correlated with photosynthetic photon flux density and net radiation, whereas Re was significantly correlated with air temperature. Through a comparative analysis of CO2 fluxes within various agricultural ecosystems, our findings indicated that wheat demonstrated moderate carbon sequestration capabilities, whereas maize and soybean exhibited strong carbon sink characteristics. Notably, saline–alkali crops exhibited lower Re, whereas GPP levels remained at a moderate range. Therefore, under the global warming trend, the respiration of saline crops and soils will be affected and may change the original carbon sink into a carbon source. Hence, implementing suitable measures targeting saline–alkali areas, such as the establishment of an effective crop rotation system and the enhance saline–alkali land conditions, can reduce emissions of greenhouse gases, thus reducing the pressure of global warming and maintaining a stable carbon cycle in saline–alkali land.

An initial assessment of winter microclimatic conditions in response to seismic line disturbance in a forested peatland

AbstractLinear disturbances are widespread in the boreal region of Alberta, Canada. Despite their ubiquitous nature, little is known about their influence on over‐winter meteorological conditions and if and how they alter the snowpack and soil temperature profiles through altered energy and water balances in the wintertime. The presence of seismic lines could affect hydrological processes in both the wintertime and warm months. This will then affect plant communities and carbon cycling on these disturbances. Thus, understanding the effect of seismic lines on meteorological conditions during cold weather conditions will be important to better understand how they alter ecosystem function. Accordingly, this study aims to assess the effect of two seismic lines with different orientations created for petroleum resource exploration on energy and meteorological variables by comparing them with the near surface conditions in the adjacent wooded peatland area from October 2022 to April 2023. We observed 1.8 times higher photon flux density of photosynthetically active radiation on the linear disturbances than in the understory of the undisturbed locations and a greater negative net radiation on the seismic lines compared with that observed off the lines. Furthermore, the average wind speed on the seismic lines were eight and seven times higher at the east–west and south–north oriented seismic lines than the adjacent wooded peatland, respectively. Together, these changes resulted in a denser snowpack on the seismic line and overall higher snow water equivalent in the pre‐melt snowpack. This provided insulation for the soil, and soil temperature on the lines stayed above freezing 7 days longer at the east–west oriented site or retained non‐freezing condition at the south–north oriented site in the upper 15 cm. This would result in more microbial activity and potential higher over‐winter carbon releases.

Evaluation of Nine Planetary Boundary Layer Turbulence Parameterization Schemes of the Weather Research and Forecasting Model Applied to Simulate Planetary Boundary Layer Surface Properties in the Metropolitan Region of São Paulo Megacity, Brazil

This study evaluates nine Planetary Boundary Layer (PBL) turbulence parameterization schemes from the Weather Research and Forecasting (WRF) mesoscale meteorological model, comparing hourly values of meteorological variables observed and simulated at the surface of the Metropolitan Region of São Paulo (MRSP). The numerical results were objectively compared with high-quality observations carried out on three micrometeorological platforms representing typical urban, suburban, and rural land use areas of the MRSP, during the 2013 summer and winter field campaigns as part of the MCITY BRAZIL project. The main objective is to identify which PBL scheme best represents the diurnal evolution of conventional meteorological variables (temperature, relative and specific humidity, wind speed, and direction) and unconventional (sensible and latent heat fluxes, net radiation, and incoming downward solar radiation) on the surface. During the summer field campaign and over the suburban area of the MRSP, most PBL scheme simulations exhibited a cold and dry bias and overestimated wind speed. They also overestimated sensible heat flux, with high agreement index and correlation values. In general, the PBL scheme simulations performed well for latent heat flux, displaying low mean bias error and root square mean error values. Both incoming downward solar radiation and net radiation were also accurately simulated by most of them. The comparison of the nine PBL schemes indicated the local Mellor-Yamada-Janjic (MYJ) scheme performed best during the summer period, particularly for conventional meteorological variables for the land use suburban in the MRSP. During the winter field campaign, simulation outcomes varied significantly based on the site’s land use and the meteorological variable analyzed. The MYJ, Bougeault-Lacarrère (BouLac), and Mellor-Yamada Nakanishi-Niino (MYNN) schemes effectively simulated temperature and humidity, especially in the urban land use area. The MYNN scheme also simulated net radiation accurately. There was a tendency to overestimate sensible and latent heat fluxes, except for the rural land use area where they were consistently underestimated. However, the rural area exhibited superior correlations compared to the urban area. Overall, the MYJ scheme was deemed the most suitable for representing the convectional and nonconventional meteorological variables on the surface in all urban, suburban, and rural land use areas of the MRSP.

Estimating crop evapotranspiration of wheat-maize rotation system using hybrid convolutional bidirectional Long Short-Term Memory network with grey wolf algorithm in Chinese Loess Plateau region

Accurate estimation of crop evapotranspiration (ET) is essential for the efficient utilization of agricultural water resources, crop production enhancement, and sustainable agricultural development. However, direct measurement of ET is highly expensive, intricate, and time-consuming, highlighting the imperative of establishing a novel model to accurately estimate ET in agricultural ecosystems. To address the above problems, this study proposed a novel model (GWA-CNN-BiLSTM), which incorporates Grey Wolf Algorithm (GWA), Convolutional Neural Network (CNN), and Bidirectional Long Short-Term Memory network (BiLSTM) as a hyperparameter adjuster, feature extractor, and regression component, respectively, to estimate ET built upon various input combinations comprising net solar radiation (Rn), vapor pressure deficit (VPD), average air temperature (Ta), soil water content (SWC), and leaf area index (LAI) about winter wheat-spring maize rotation system during 2012–2020 in the Loess Plateau. Besides, following a comparative assessment within GWA-CNN-BiLSTM, Convolutional Bidirectional Long Short-Term Memory network (CNN-BiLSTM), BiLSTM, Long Short-Term Memory network (LSTM), and Shuttleworth-Wallace (SW) models, the results revealed that GWA-CNN-BiLSTM under varied inputs obtained the superior performance, ranging from 0.562 to 0.957 in determination coefficient (R2), 8.4–41.5 % in relative root mean square error (RRMSE), 0.349 mm d−1 to 1.521 mm d−1 in mean absolute error (MAE), −3.26 % to 14.11 % in percent bias (PBIAS), and 0.820–1.091 in regression coefficient (b0), respectively. Moreover, while the accuracy of BiLSTM over LSTM was evident, its performance was notably improved by the incorporation of the CNN module. Additionally, LSTM-type models under complete input combination present better precision than SW by 29.7−51.4 % in R2, 44.2−76.1 % in RRMSE, and 33.6−63.4 % in MAE, respectively. Furthermore, the accuracy of all models under varied inputs exhibited excellence in winter wheat compared to spring maize, and corresponding improvements ranged 1.4−4.3 % in R2, 5.1−20.1 % in RRMSE, and 3.1−17.9 % in MAE, respectively. Besides, the meteorological factors (Rn, VPD, Ta) proved to be the most important inputs for ET estimation in winter wheat and spring maize. Wherein the importance of SWC exceeded that of LAI in winter wheat, while the opposite trend was observed in spring maize. In brief, GWA-CNN-BiLSTM is the highly recommended model to estimate ET of winter wheat-spring maize rotation system under diverse input data scenarios in the Loess Plateau, which can facilitate to offer valuable assistance in regional agriculture water management decisions.

Role of Surface Energy Fluxes in Urban Overheating Under Buoyancy‐Driven Atmospheric Conditions

AbstractUrbanization alters land surface properties in absorbing, reflecting and emitting radiation as well as infiltrating, evaporating and storing water. This consequently modifies surface energy and water fluxes and, thus, urban climates. Weak synoptic flow, clear sky conditions and higher surface temperatures in cities compared to their rural surroundings create a buoyancy‐driven atmospheric circulation, in which surface energy fluxes become the main determinants of urban daytime overheating. Here, we demonstrate the role of surface energy fluxes for warming and cooling processes in the urban canopy layer under buoyancy‐driven atmospheric conditions. We improve and apply an integrated CFD‐GIS modeling approach to provide a detailed analysis of fine‐scale land‐atmosphere interactions and assess the surfaces' profound implications on energy and water exchange. We show that variations in the ratios of the surface energy fluxes to the net radiation can be separated from meteorological conditions (wind speed, air temperature and incoming solar radiation) and emissivity values, varying explicitly with changes in land surface type and water availability for vegetated areas. Based on the energy flux ratios, we introduce an approach to assess the surface‐induced warming and cooling effect and its contribution to urban overheating in the urban canopy layer, under buoyancy‐driven atmospheric conditions, directly applicable to strategic urban planning for climate change adaptation. Independent of meteorological conditions, this approach can be used to evaluate different surface materials (both natural and artificial) and climate adaptation measures, such as urban nature‐based solutions and blue‐green infrastructures, and to monitor changes in the energy and water balance.

A new perennial forage module coupled with the ECOSMOS terrestrial ecosystem model: Calibration and evaluation for Urochloa (syn. Brachiaria) brizantha

Pastures represent the main land use type in Brazil and are used for livestock production and maintenance of land ownership. Most pasture areas exhibit signs of degradation related to inadequate management, which affects pasture biomass production. Terrestrial ecosystem models are effective tools for evaluating the economic and ecological returns associated with distinct management scenarios. In this paper, a new forage module implemented in the ECOSystem MOdel Simulator (ECOSMOS) is formulated, and ECOSMOS-Forage model calibration and evaluation results were obtained for estimating tropical forage growth under continuous and rotational stocking methods subject to grazing or cutting regimes. A set of equations to simulate the daily carbon allocation, growth, senescence, and morphological characteristics of Urochloa (syn. Brachiaria) brizantha cvs. Marandu and Piatã were proposed. Biophysical and physiological parameters, including the solar radiation balance, soil water content, evapotranspiration and carbon assimilation, were calibrated and evaluated with one micrometeorological experiment. Additionally, two sets of parameters were calibrated for Marandu grass growth under continuous and rotational stocking. Based on the Marandu parameterization, a third set of parameters, thereby adjusting a few parameters, was derived for the Piatã grass under rotational stocking. The ECOSMOS-Forage model could successfully capture the energy, carbon and water fluxes and biomass dynamics during growth cycles. The net radiation, evapotranspiration and gross primary production were simulated with agreement index (d) values of 0.97, 0.89, and 0.95, respectively, during the calibration phase and 0.98, 0.90, and 0.93, respectively, during the evaluation phase. Regarding model application to simulate forage growth under rotational stocking, the model could estimate aboveground, leaf and stem dry matter accumulation levels with d values ranging from 0.91 to 0.98. Although forage growth is relatively difficult to simulate, compared with annual crops, the results suggested that the model could provide high potential for simulating tropical perennial forage grasses.