Shortwave Irradiance Research Articles

Retrieval of Solar Shortwave Irradiance from All-Sky Camera Images

The present work proposes a new model based on a convolutional neural network (CNN) to retrieve solar shortwave (SW) irradiance via the estimation of the cloud modification factor (CMF) from daytime sky images captured by all-sky cameras; this model is named CNN-CMF. To this end, a total of 237,669 sky images paired with SW irradiance measurements obtained by using pyranometers were selected at the following three sites: Valladolid and Izaña, Spain, and Lindenberg, Germany. This dataset was randomly split into training and testing sets, with the latter excluded from the training model in order to validate it using the same locations. Subsequently, the test dataset was compared with the corresponding SW irradiance measurements obtained by the pyranometers in scatter density plots. The linear fit shows a high determination coefficient (R2) of 0.99. Statistical analyses based on the mean bias error (MBE) values and the standard deviation (SD) of the SW irradiance differences yield results close to −2% and 9%, respectively. The MBE indicates a slight underestimation of the CNN-CMF model compared to the measurement values. After its validation, model performance was evaluated at the Antarctic station of Marambio (Argentina), a location not used in the training process. A similar comparison between the model-predicted SW irradiance and pyranometer measurements yielded R2=0.95, with an MBE of around 2% and an SD of approximately 26%. Although the precision provided by the SD at the Marambio station is lower, the MBE shows that the model’s accuracy is similar to previous results but with a slight overestimation of the SW irradiance. Finally, the determination coefficient improved to 0.99, and the MBE and SD are about 3% and 11%, respectively, when the CNN-CMF model is used to estimate daily SW irradiation values.

Solar and Wind Energy Feasibility for a Water Treatment and Recirculation System Intended for Carniculture: Comparative Study Between the Cities Of Monteiro and Sousa – Paraíba – Brazil

Objective: This article presents a comparative study of renewable solar and wind energy production capacity between Monteiro and Sousa cities, located in the semi-arid region of Paraíba state, Brazil, to analyze the feasibility of using solar panels and/or wind turbines for energy supply in a water recirculation and treatment model applied to carciniculture. Method: A hypothetical-deductive method was employed and a bibliographic character was adopted in the research, taking as basis technical-scientific work information. Additionally, the research also presents quantitative theory, since it makes use of quantifiable results presented from measurable data that need to be properly expressed. A composite system was proposed, initially consisting of six identical units exposed in Figure 1, disposed under a roof, over which photovoltaic plates are placed for the supply of electrical energy to the hydraulic pumps contained in the system. The modeling study was based on wind speed and solar irradiance data in the cities of Monteiro and Sousa, with coordinates latitude -37.1214299 and longitude -7.8983769, and latitude -38.2285597 and longitude -6.7671611. These information were extracted from the Terraclimate database, using scripts written in Java and Python languages for extraction and processing. To predict wind power energy, the average wind speed in meters per second was used for each month, from January 1st, 2010 to December 31st, 2020. For modeling of photovoltaic power prediction, the average short-wave irradiance (W/m²) per month was considered, during the same period. To establish the monthly mean temperature, the average temperatures in Celsius were considered for the period from January 1st, 2010 to December 31st, 2020. For verification of the sufficiency of wind and photovoltaic systems for energy production maintenance, the energy demand of the System of Carciniculture was compared with the energy production by each of the sources considered, and based on the analysis made, it was defined which is the best energy production systemto be used and the best city where the defined system will be installed. Results and conclusions: The results show that the use of solar energy is economical, reduces social impacts generating employment and elevates environmental awareness, and has low environmental impact. The study found that solar energy generation capacity is sufficient and most suitable to keep the shrimp farming system running throughout the year, with observed variations between 226.8 kWh/month and 299.7 kWh/month in Souza city, and between 232.2 kWh/month and 369.0 kWh/month in Monteiro city, quantities more than enough for energy supply of the shrimp culture system, which presents a demand of 207.4 kWh/month. Implications of the research: The study points out that renewable energy can be an alternative more economical than other methods of energy generation, which could be a positive response to environmental and economic problems affecting the northeastern region, especially along the São Francisco River transposition, where Monteiro and Souza cities are among the last to receive it. Originality/Value: The use of solar energy is a viable solution for providing energy to shrimp culture. Additionally, the study also points out that this method may be more economical than other methods of energy generation.

Broadband and filter radiometers at Ross Island, Antarctica: detection of cloud ice phase versus liquid water influences on shortwave and longwave radiation

Abstract. Surface radiometer data from Ross Island, Antarctica, collected during the austral summer 2015–2016 by the US Department of Energy Atmospheric Radiation Measurement (ARM) program West Antarctic Radiation Experiment (AWARE), are used to evaluate how shortwave and longwave irradiance respond to changing cloud properties as governed by contrasting meteorological regimes. Shortwave atmospheric transmittance is derived from pyranometer measurements, and cloud conservative-scattering optical depth is derived from filter radiometer measurements at 870 nm. With onshore flow associated with marine air masses, clouds contain mostly liquid water. With southerly flow over the Transantarctic Mountains, orographic forcing induces substantial cloud ice water content. These ice and mixed-phase clouds attenuate more surface shortwave irradiance than the maritime-influenced clouds and also emit less longwave irradiance due to colder cloud base temperature. These detected irradiance changes are in a range that can mean onset or inhibition of surface melt over ice shelves. This study demonstrates how basic and relatively low-cost broadband and filter radiometers can be used to detect subtle climatological influences of contrasting cloud microphysical properties at very remote locations.

Long‐Term Trends in Aerosols, Low Clouds, and Large‐Scale Meteorology Over the Western North Atlantic From 2003 to 2020

AbstractA continuous decrease in aerosols over the Western North Atlantic Ocean (WNAO) on a decadal timescale provides a long‐term benchmark to evaluate how various natural and anthropogenic processes affect the manifestation of aerosol‐cloud interactions in this region. Furthermore, the WNAO serves as a natural laboratory with diverse aerosol sources, marine boundary layer clouds more variable than those in marine stratocumulus deck regions, and unique flow regimes established by the Gulf Stream and the semi‐permanent Bermuda High. We investigate how satellite‐retrieved macrophysical and microphysical properties of low clouds and the surface shortwave irradiance changed from 2003 to 2020, in tandem with this aerosol decrease. The decadal changes in large‐scale meteorology related to the North Atlantic Oscillation (NAO) are also examined. We find a reduction in low‐cloud optical thickness, accompanied by fewer and larger cloud droplets, yet observe no significant changes in low‐cloud fraction and liquid water path. Despite the reduction in low‐cloud optical thickness together with aerosol decrease, a corresponding increase in the trends of surface shortwave irradiance, also known as surface brightening, is lacking. This absence of brightening is potentially related to concomitant changes found in large‐scale meteorology associated with NAO—Bermuda High strengthening, sea surface warming, and atmospheric moistening— as well as an increase in high‐level cloud fraction that can counteract the surface brightening. Ultimately, our findings suggest that spatial patterns of decadal meteorological variability introduce complexities in the surface cloud radiative effect over the WNAO, thereby complicating the isolation and examination of aerosol‐cloud interactions.

Detecting clear‐sky periods from photovoltaic power measurements

AbstractA method for detecting clear‐sky periods from photovoltaic (PV) power measurements is presented and validated. It uses five tests dealing with parameters characterizing the connections between the measured PV power and the corresponding clear‐sky power. To estimate clear‐sky PV power, a PV model has been designed using as inputs downwelling shortwave irradiance and its direct and diffuse components received at ground level under clear‐sky conditions as well as reflectivity of the Earth's surface and extraterrestrial irradiance, altogether provided by the McClear service. In addition to McClear products, the PV model requires wind speed and temperature as inputs taken from ECMWF twentieth century reanalysis ERA5 products. The performance of the proposed method has been assessed and validated by visual inspection and compared to two well‐known algorithms identifying clear‐sky periods with broadband global and diffuse irradiance measurements on a horizontal surface. The assessment was carried out at two stations located in Finland offering collocated 1‐min PV power and broadband irradiance measurements. Overall, total agreement ranges between 84% and 97% (depending on the season) in discriminating clear‐sky and cloudy periods with respect to the two well‐known algorithms serving as reference. The disagreement fluctuating between 6% and 15%, depending on the season, primarily occurs while the PV module temperature is adequately high and/or when the sun is close to the horizon with many more interactions between the radiation, the atmosphere and the ground surface.

How to rapidly map outdoor mean radiation temperatures with high-spatial-resolution from UAV-derived multimodal images: A case study in Guangzhou

Mean radiation temperatures (MRTs) have gained widespread attention due to its close relationship with human health. Notwithstanding the availability of existing methods for evaluating MRT (such as ground-based measurements and numerical simulations), it remains a challenge to rapidly and accurately acquire MRTs with a high spatial resolution. This study thus proposed an efficient methodology for evaluating spatial MRTs of urban spaces on the microscale through multimodal images derived from unmanned aerial vehicles (UAVs). Based on UAVs and near-ground measurements, point-cloud data characterizing long- and short-wave irradiance from three-dimensional (3D) surfaces were obtained via photogrammetry and retrieval models. Spatial MRTs were then sampled based on a mapped 3D radiation field and ray-tracing. Comparison of the sampled MRTs with measured MRTs (near the ground) through globe temperatures exhibited a high consistency (R2: 0.980, RMSE: 3.080 °C) and a small difference (almost less than 2.5 °C), demonstrating the applicability and accuracy of our proposed method. In conjunction with near-ground meteorological variables, outdoor thermal comfort (OTC) indicators with a high spatial resolution were derived; further comparisons suggested the SET* and UTCI as ideal indicators to evaluate microscale OTC of hot and humid areas through our method. From the perspective of application, this method can further refine the assessment of the urban thermal environment as well as the human thermal comfort of micro-scale spaces based on simulations or remote sensing observations with lower spatial resolution, which will provide specific suggestions for redesign or redevelopment of the micro-scale areas. Additionally, the thermal mapping with high spatial resolution obtained by this method can also be used as a reference to evaluate the accuracy of related numerical models.

Soot-on-snow experiment: artificial deposition of light-absorbing particles onto snow surfaces in 2018

The absorption of shortwave irradiance in snow depends on the physical properties of snow (e.g., snow grain size and shape, liquid water content, etc.) and light-absorbing particles (LAP). Originating from natural and anthropogenic sources, LAP has been reported to accelerate snowmelt significantly in different regions globally. Yet, our process-level understanding of LAP after deposition onto snow remains rather limited. Here we investigate the impacts of artificial deposition of different LAP onto snow surfaces in an outdoor environment of northern Finland. Following LAP dry deposition into a custom-made tent standing on top of the snowpack, the albedo was followed along with the properties of snow in snow pit measurements throughout the spring season. The results showed that the albedo decay at the end of the season for the different spots were linked to the initial amount and type of LAP that were deposited onto the snowpack. Measured snow temperature profiles from LAP doped snow versus natural reference snow illustrated that the LAP affected snow had higher temperatures in the subsurface snow layers. Collected snow samples analyzed for size distribution of soot particles revealed no apparent agglomeration of soot particles during thaw-freezing events taking place during the experiment. Despite the relatively large perturbation of the experimentally deposited LAP, their impact on the season length was only up to 3 days. Additional experiments are, nevertheless, needed to better constrain the effects of LAP on snow albedo, melt rate, and other associated processes.

A quality-assured dataset of nine radiation components observed at the Shangdianzi regional GAW station in China (2013–2022)

Abstract. The New Baseline Surface Radiation (NBSR) system was established at the Shangdianzi (SDZ) regional Global Atmosphere Watch (GAW) station in 2013 to observe nine broadband radiation components, i.e. the global, direct, diffuse, and upwelling shortwave irradiance (GSWI, DSWI, DifSWI, and UpSWI); the photosynthetically active radiation (PAR); the ultraviolet irradiance (UVAI and UVBI); and the down- and upwelling longwave irradiance (DnLWI and UpLWI). To test the 1 min raw radiometric data, a Hybrid Algorithm for Radiation Data Quality Control (HARDQC) is presented in this study based on well-established methods, together with the solar irradiance dataset and the spectral features of the instrument bands. Subsequently, a NBSR dataset, which consists of radiation data at multiple timescales (i.e. 1 min, hourly, daily, monthly, monthly average hourly, and monthly average daily) over 2013–2022, is established and evaluated. Results show that more than 98.7 % of all radiation components passed the physical possibility test. The percentages of those that passed the extremely rare test are greater than 98.6 % for all radiation components except for the DnLWI (97.1 %). The percentages of those that passed the comparison test are greater than 83.3 % (GSWI), 78.3 % (DSWI), 81.7 % (DifSWI), 93.1 % (UpSWI), 88.9 % (PAR), 95.6 % (UVAI), 96.3 % (UVBI), 99.8 % (DnLWI), and 99.7 % (UpLWI), respectively. Due to data logger faults, removal of the instruments for calibration, and lightning strikes, some apparent data gaps in the upwelling radiation components (January 2015–August 2017) and all radiation components (December 2018; July to September 2021) were detected. Despite the existence of a few imperfections in the NBSR dataset, it is still reliable to apply it in many fields such as the validation of satellite products and numerical models, the investigation of relationships between radiation and atmospheric composition, and the detection of changes in the surface fluxes. The dataset described in this paper is available at https://doi.org/10.1594/PANGAEA.963330 (Quan et al., 2023b).

Radiative Regime According to the New RAD-MSU(BSRN) Complex in Moscow: The Roles of Aerosol, Surface Albedo, and Sunshine Duration

The radiative budget is one of the key factors that influences climate change. The aim of this study was to analyze the radiative regime in Moscow using the RAD-MSU(BSRN) complex and to estimate the radiative effects of the main geophysical factors during the 2021–2023 period. This complex is equipped and maintained according to the recommendations of the Baseline Surface Radiation Network; however, it is not a part of this network. In cloudless conditions, the decrease in global shortwave irradiance (Q) is about 18–22% due to the aerosol content with a pronounced change in the direct to diffuse ratio. In winter, the increase in Q is about 45 W/m2 (or 9%) at h = 30° due to a high surface albedo and reduced aerosol and water vapor contents, while the net shortwave irradiance (Bsh) demonstrates a significant decrease due to the prevailing effects of snow albedo. In cloudy conditions, a nonlinear dependence of Q and Bsh cloud transmittance on the relative sunshine duration is observed. The mean changes in Q for the 2021–2023 against the 1955–2020 period are characterized by negative anomalies (−22%) in winter and positive anomalies in summer (+3%) due to the changes in cloudiness. This is in line with the global tendencies in the long-term changes in shortwave irradiance in moderate climates in Europe in recent years.

Shortwave and longwave components of the surface radiation budget measured at the Thule High Arctic Atmospheric Observatory, Northern Greenland

Abstract. The Arctic climate is influenced by the interaction of shortwave (SW) and longwave (LW) radiation with the atmosphere and the surface. The comprehensive evolution of the Surface Radiative Fluxes (SRF) on different time scales is of paramount importance to understanding the complex mechanisms governing the Arctic climate. However, only a few sites located in the Arctic region provide long-term time series of SRF allowing for capturing of the seasonality of atmospheric and surface parameters and for carrying out validation of satellite products and/or reanalyses. This paper presents the daily and monthly SRF record collected at the Thule High Arctic Atmospheric Observatory (THAAO, 76.5∘ N, 68.8∘ W), in North-Western Greenland. The downwelling components of the SW (DSI) and the LW (DLI) irradiances have been measured at THAAO since 2009, whereas the collection of the upwelling SW (USI) and LW (ULI) irradiance was started in 2016, together with additional measurements, such as meteorological parameters and column water vapour. The datasets of DSI (Meloni et al., 2022a; https://doi.org/10.13127/thaao/dsi), USI (Meloni et al., 2022b; https://doi.org/10.13127/thaao/usi), DLI (Meloni et al., 2022c; https://doi.org/10.13127/thaao/dli), ULI (Meloni et al., 2022d; https://doi.org/10.13127/thaao/uli), and near-surface air temperature (Muscari et al., 2018; https://doi.org/10.13127/thaao/met), can be accessed through the THAAO web site (https://www.thuleatmos-it.it/data, last access: 16 January 2024). The DSI is absent (solar zenith angle ≥90∘) from 29 October to 13 February, assuming maxima in June (monthly mean of 277.0 Wm−2), when it is about half of the total incoming irradiance. The USI maximum occurs in May (132.4 Wm−2) owing to the combination of moderately high DSI values and high albedo. The shortwave surface albedo (A) assumes an average of 0.16 during summer, when the surface is free of snow. Differently, during months of snow-covered surface, when solar radiation allows A to be estimated, its values are greater than 0.6. A large interannual variability is observed in May and September, months characterized by rapidly changing surface conditions, having a link with air temperature anomalies. The DLI and ULI maxima occur in July and August, and the minima in February and March. ULI is always larger than DLI and shows a wider annual cycle. ULI is well described by a fourth-order polynomial fit to the air temperature (R2>0.99 for monthly data and R2>0.97 for daily data). The Surface Radiation Budget (SRB) is positive from April to August, when absorption of solar radiation exceeds the infrared net cooling, with a maximum value of 153.2 Wm−2 in June. From November to February, during the polar night, the LW net flux varies between −34.5 and −43.0 Wm−2. In March and September, the negative LW net flux overcomes the positive SW contribution, producing a negative SRB. The THAAO measurements show clear evidence of the influence of several regional weather/climate events, that appear strongly linked with SRF anomalies. These anomalies were found, for example, during summer 2012, when a large ice melting event took place over Greenland, and during winter 2019–2020, which was extraordinarily cold in the Arctic region.

Supercooled liquid water clouds observed over Dome C, Antarctica: temperature sensitivity and cloud radiative forcing

Abstract. Clouds affect the Earth climate with an impact that depends on the cloud nature (solid and/or liquid water). Although the Antarctic climate is changing rapidly, cloud observations are sparse over Antarctica due to few ground stations and satellite observations. The Concordia station is located on the eastern Antarctic Plateau (75∘ S, 123∘ E; 3233 m above mean sea level), one of the driest and coldest places on Earth. We used observations of clouds, temperature, liquid water, and surface irradiance performed at Concordia during four austral summers (December 2018–2021) to analyse the link between liquid water and temperature and its impact on surface irradiance in the presence of supercooled liquid water (liquid water for temperature less than 0 ∘C) clouds (SLWCs). Our analysis shows that, within SLWCs, temperature logarithmically increases from −36.0 to −16.0 ∘C when liquid water path increases from 1.0 to 14.0 g m−2. The SLWC radiative forcing is positive and logarithmically increases from 0.0 to 70.0 W m−2 when liquid water path increases from 1.2 to 3.5 g m−2. This is mainly due to the downward longwave component that logarithmically increases from 0 to 90 W m−2 when liquid water path increases from 1.0 to 3.5 g m−2. The attenuation of shortwave incoming irradiance (that can reach more than 100 W m−2) is almost compensated for by the upward shortwave irradiance because of high values of surface albedo. Based on our study, we can extrapolate that, over the Antarctic continent, SLWCs have a maximum radiative forcing that is rather weak over the eastern Antarctic Plateau (0 to 7 W m−2) but 3 to 5 times larger over West Antarctica (0 to 40 W m−2), maximizing in summer and over the Antarctic Peninsula.

Changes in cloudiness contribute to changing seasonality in the Baltic Sea region

In the Baltic Sea region, a significant increase in solar radiation has been detected during the past half-century. Changes in shortwave irradiance are associated with atmospheric transparency and cloudiness parameters like cloud fraction and albedo. One of the most important reasons for day-to-day changes in cloudiness is the synoptic-scale atmospheric circulation; thus, we look for reasons for solar radiation trends due to changes in atmospheric circulation. We analysed regional time series and trends from satellite-based cloud climate data record CLARA-A2 for the Baltic Sea region in 1982–2018. As the rise in solar radiation depends on the seasonally averaged values of total fractional cloud cover (CFC), surface incoming shortwave radiation (SIS) and occurrences of circulation types were analysed. We show that the shift in seasonality connected to the earlier accumulated sums of SIS is at least partly explained by the changes in synoptic-scale atmospheric circulation.

The historical Greenland Climate Network (GC-Net) curated and augmented level-1 dataset

Abstract. The Greenland Climate Network (GC-Net) consists of 31 automatic weather stations (AWSs) at 30 sites across the Greenland Ice Sheet. The first site was initiated in 1990, and the project has operated almost continuously since 1995 under the leadership of the late Konrad Steffen. The GC-Net AWS measured air temperature, relative humidity, wind speed, atmospheric pressure, downward and reflected shortwave irradiance, net radiation, and ice and firn temperatures. The majority of the GC-Net sites were located in the ice sheet accumulation area (17 AWSs), while 11 AWSs were located in the ablation area, and two sites (three AWSs) were located close to the equilibrium line altitude. Additionally, three AWSs of similar design to the GC-Net AWS were installed by Konrad Steffen's team on the Larsen C ice shelf, Antarctica. After more than 3 decades of operation, the GC-Net AWSs are being decommissioned and replaced by new AWSs operated by the Geological Survey of Denmark and Greenland (GEUS). Therefore, making a reassessment of the historical GC-Net AWS data is necessary. We present a full reprocessing of the historical GC-Net AWS dataset with increased attention to the filtering of erroneous measurements, data correction and derivation of additional variables: continuous surface height, instrument heights, surface albedo, turbulent heat fluxes, and 10 m ice and firn temperatures. This new augmented GC-Net level-1 (L1) AWS dataset is now available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2023) and will continue to be refined. The processing scripts, latest data and a data user forum are available at https://github.com/GEUS-Glaciology-and-Climate/GC-Net-level-1-data-processing (last access: 30 November 2023). In addition to the AWS data, a comprehensive compilation of valuable metadata is provided: maintenance reports, yearly pictures of the stations and the station positions through time. This unique dataset provides more than 320 station years of high-quality atmospheric data and is available following FAIR (findable, accessible, interoperable, reusable) data and code practices.

On the Large Variation in Atmospheric CO2 Concentration at Shangdianzi GAW Station during Two Dust Storm Events in March 2021

Dust storms have large impacts on air quality and meteorological elements; however, their relationships with atmospheric greenhouse gases (e.g., CO2) and radiation components remain uncertain. In this study, the co-variation of dust and CO2 concentrations and its possible influencing mechanism are examined using observations at the Shangdianzi (SDZ) regional Global Atmosphere Watch (GAW) station along with simulations of the Vegetation Photosynthesis and Respiration Model coupled with the Weather Research and Forecasting model (WRF-VPRM), during two dust storm events on 15 and 28 March 2021. During these events, hourly CO2 concentrations decreased by 40–50 ppm at SDZ while dust concentrations increased to 1240.6 and 712.4 µg m−3. The elevated dust increased diffusive shortwave irradiance by 50–60% and decreased direct shortwave irradiance by ~60% along with clouds. The dust events were attributed to the passages of two cold front systems over northern China. At SDZ, during the frontal passages, wind speed increased by 3–6 m s−1, and relative humidity decreased by 50–60%. The CO2 variations associated with the frontal systems were captured by the WRF-VPRM despite the overestimated surface CO2 level at SDZ. Biogenic CO2 flux plays an indistinctive role in the large CO2 variation at SDZ, as it is weak during the non-growing season. The cold fronts pushed polluted air southeastward over the North China Plain and replaced it with low-CO2 air from Northwest China, leading to the decline in CO2. These findings demonstrate that mesoscale synoptic conditions significantly affect the regional transport and dispersion of CO2, which can influence the prediction of terrestrial carbon balance on a regional scale.

Detection and attribution of an anomaly in terrestrial photosynthesis in Europe during the COVID-19 lockdown

Carbon dioxide (CO2) uptake by plant photosynthesis, referred to as gross primary production (GPP) at the ecosystem level, is sensitive to environmental factors, including pollutant exposure, pollutant uptake, and changes in the scattering of solar shortwave irradiance (SWin) − the energy source for photosynthesis. The 2020 spring lockdown due to COVID-19 resulted in improved air quality and atmospheric transparency, providing a unique opportunity to assess the impact of air pollutants on terrestrial ecosystem functioning. However, detecting these effects can be challenging as GPP is influenced by other meteorological drivers and management practices. Based on data collected from 44 European ecosystem-scale CO2 flux monitoring stations, we observed significant changes in spring GPP at 34 sites during 2020 compared to 2015–2019. Among these, 14 sites showed an increase in GPP associated with higher SWin, 10 sites had lower GPP linked to atmospheric and soil dryness, and seven sites were subjected to management practices. The remaining three sites exhibited varying dynamics, with one experiencing colder and rainier weather resulting in lower GPP, and two showing higher GPP associated with earlier spring melts. Analysis using the regional atmospheric chemical transport model (LOTOS-EUROS) indicated that the ozone (O3) concentration remained relatively unchanged at the research sites, making it unlikely that O3 exposure was the dominant factor driving the primary production anomaly. In contrast, SWin increased by 9.4 % at 36 sites, suggesting enhanced GPP possibly due to reduced aerosol optical depth and cloudiness. Our findings indicate that air pollution and cloudiness may weaken the terrestrial carbon sink by up to 16 %. Accurate and continuous ground-based observations are crucial for detecting and attributing subtle changes in terrestrial ecosystem functioning in response to environmental and anthropogenic drivers.

Construction and Research of Ultra-Short Term Prediction Model of Solar Short Wave Irradiance Suitable for Qinghai–Tibet Plateau

The Qinghai–Tibet Plateau region has abundant solar energy, which presents enormous potential for the development of solar power generation. Accurate prediction of solar radiation is crucial for the safe and cost-effective operation of the power grid. Therefore, constructing a suitable ultra-short-term prediction model for the Tibetan Plateau region holds significant importance. This study was based on the autoregressive integrated moving average model (ARIMA), random forest model (RF), and long short-term memory model (LSTM) to construct a prediction model for forecasting the average irradiance for the next 10 min. By locally testing and optimizing the model parameter, the study explored the applicability of each model in different seasons and investigates the impact of factors such as training dataset and prediction time range on model accuracy. The results showed that: (1) the accuracy of the ARIMA model was lower than the persistence model used as a reference model, while both the RF model and LSTM model had higher accuracy than the persistence model; (2) the sample size and distribution of the training dataset significantly affected the accuracy of the models. When both the season (distribution) and sample size were the same, RF achieved the highest accuracy. The optimal sample sizes for ARIMA, RF, and LSTM models in each season were as follows: spring (3564, 1980, 4356), summer (2772, 4752, 2772), autumn (3564, 3564, 4752), and winter (3168, 3168, 4752). (3) The prediction forecast horizon had a significant impact on the model accuracy. As the forecast horizon increased, the errors of all models gradually increased, reaching a peak between 80 and 100 min before slightly decreasing and then continuing to rise. When both the season and forecast horizon were the same, RF had the highest accuracy, with an RMSE lower than ARIMA by 65.6–258.3 W/m2 and lower than LSTM by 3.7–83.3 W/m2. Therefore, machine learning can be used for ultra-short-term forecasting of solar irradiance in the Qinghai–Tibet Plateau region to meet the forecast requirements for solar power generation, providing a reference for similar studies.

Surface Solar Extremes in the Most Irradiated Region on Earth, Altiplano

Abstract Satellites have consistently pointed to the Altiplano of the Atacama Desert as the place on Earth where the world’s highest surface irradiance occurs. This region, near the Tropic of Capricorn, is characterized by its high elevation, prevalent cloudless conditions, and relatively low concentrations of ozone, aerosols, and precipitable water. Aimed at studying the variability of the surface solar irradiance and detecting atmospheric composition changes in the Altiplano, an atmospheric observatory was set up in 2016 at the northwestern border of the Chajnantor Plateau (5,148 m MSL, 22.95°S, 67.78°W, Chile). Here, we report on the first 5 years of measurements at this observatory that establish the Altiplano as the region that receives the highest-known irradiation on Earth and illuminate the unique features of surface solar extremes at high-altitude locations. We found that the global horizontal shortwave (SW) irradiance on the plateau is on average 308 W m−2 (equivalent to an annual irradiation of 2.7 MWh m−2 yr−1, the highest worldwide). We also found that forward scattering by broken clouds often leads to intense bursts of SW irradiance; a record of 2,177 W m−2 was measured, equivalent to the extraterrestrial SW irradiance expected at approximately 0.79 astronomical units (AU) from the Sun. These cloud-driven surface solar extremes occur on the Chajnantor Plateau at a frequency, intensity, and duration not previously seen anywhere in the world, making the site an ideal location for studying the response of photovoltaic (PV) power plants to periods of enhanced SW variability.

Smoke‐Driven Changes in Photosynthetically Active Radiation During the U.S. Agricultural Growing Season

AbstractWildfire smoke is frequently present over the U.S. during the agricultural growing season and will likely increase with climate change. Studies of smoke impacts have largely focused on air quality and human health; however, understanding smoke's impact on photosynthetically active radiation (PAR) is essential for predicting how smoke affects plant growth. We compare surface shortwave irradiance and diffuse fraction (DF) on smoke‐impacted and smoke‐free days from 2006 to 2020 using data from multifilter rotating shadowband radiometers at 10 U.S. Department of Agriculture UV‐B Monitoring and Research Program stations and smoke plume locations from operational satellite products. On average, 20% of growing season days are smoke‐impacted, but smoke prevalence increases over time (r = 0.60, p < 0.05). Smoke presence peaks in the mid to late growing season (i.e., July, August), particularly over the northern Rocky Mountains, Great Plains, and Midwest. We find an increase in the distribution of PAR DF on smoke‐impacted days, with larger increases at lower cloud fractions. On clear‐sky days, daily average PAR DF increases by 10 percentage points when smoke is present. Spectral analysis of clear‐sky days shows smoke increases DF (average: +45%) and decreases total irradiance (average: −6%) across all six wavelengths measured from 368 to 870 nm. Optical depth measurements from ground and satellite observations both indicate that spectral DF increases and total spectral irradiance decreases with increasing smoke plume optical depth. Our analysis provides a foundation for understanding smoke's impact on PAR, which carries implications for agricultural crop productivity under a changing climate.

Combining Cloud Properties from CALIPSO, CloudSat, and MODIS for Top-of-Atmosphere (TOA) Shortwave Broadband Irradiance Computations: Impact of Cloud Vertical Profiles

Abstract Cloud vertical profile measurements from the CALIPSO and CloudSat active sensors are used to improve top-of-atmosphere (TOA) shortwave (SW) broadband (BB) irradiance computations. The active sensor measurements, which occasionally miss parts of the cloud columns because of the full attenuation of sensor signals, surface clutter, or insensitivity to a certain range of cloud particle sizes, are adjusted using column-integrated cloud optical depth derived from the passive MODIS sensor. Specifically, we consider two steps in generating cloud profiles from multiple sensors for irradiance computations. First, cloud extinction coefficient and cloud effective radius (CER) profiles are merged using available active and passive measurements. Second, the merged cloud extinction profiles are constrained by the MODIS visible scaled cloud optical depth, defined as a visible cloud optical depth multiplied by (1 − asymmetry parameter), to compensate for missing cloud parts by active sensors. It is shown that the multisensor-combined cloud profiles significantly reduce positive TOA SW BB biases, relative to those with MODIS-derived cloud properties only. The improvement is more pronounced for optically thick clouds, where MODIS ice CER is largely underestimated. Within the SW BB (0.18–4 μm), the 1.04–1.90-μm spectral region is mainly affected by the CER, where both the cloud absorption and solar incoming irradiance are considerable. Significance Statement The purpose of this study is to improve shortwave irradiance computations at the top of the atmosphere by using combined cloud properties from active and passive sensor measurements. Relative to the simulation results with passive sensor cloud measurements only, the combined cloud profiles provide more accurate shortwave simulation results. This is achieved by more realistic profiles of cloud extinction coefficient and cloud particle effective radius. The benefit is pronounced for optically thick clouds composed of large ice particles.

Evaluation of aerosol optical depths and clear-sky radiative fluxes of the CERES Edition 4.1 SYN1deg data product

Abstract. Aerosol optical depths (AODs) used for the Edition 4.1 Clouds and the Earth's Radiant Energy System (CERES) Synoptic 1∘ (SYN1deg) product are evaluated. AODs are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) observations and assimilated by an aerosol transport model (the Model for Atmospheric Transport and Chemistry – MATCH). As a consequence, clear-sky AODs closely match with those derived from MODIS instruments. AODs under all-sky conditions are larger than AODs under clear-sky conditions, which is supported by ground-based AErosol RObotic NETwork (AERONET) observations. When all-sky MATCH AODs are compared with Modern-Era Retrospective analysis for Research and Applications (Version 2; MERRA-2) AODs, MATCH AODs are generally larger than MERRA-2 AODs, especially over convective regions (e.g., the Amazon, central Africa, and eastern Asia). This variation is largely due to the differing methods of assimilating the MODIS AOD data product and the use of quality flags in our assimilation. Including AODs with larger retrieval uncertainty makes AODs over the convective regions larger. When AODs are used for clear-sky irradiance computations and computed downward shortwave irradiances are compared with ground-based observations, the computed instantaneous irradiances are 1 %–2 % larger than observed irradiances. The comparison of top-of-atmosphere clear-sky irradiances with those derived from CERES observations suggests that AODs used for surface radiation observation sites are 0.01–0.03 larger, which is within the uncertainty of instantaneous MODIS AODs. However, the comparison with AERONET AODs suggests that AODs used for computations over desert sites are 0.08 larger. The cause of positive biases in downward shortwave irradiance and in AOD for the desert sites is possibly due to the dust particle size and distribution, as defined by the MATCH transport model, and the transfer of that information into the radiative transfer model.