Clear-sky Radiation Research Articles

Interdecadal variations of aerosol and its composition over the Fenwei Plain based on multi-source observations

Understanding the variations and potential source of air pollution is essential for implementing targeted mitigation actions. However, the distribution and long-term trends of Aerosol Optical Depth (AOD) and its components over the Fenwei Plain (FWP) have not been thoroughly investigated. Furthermore, the potential source contribution of AOD loading is still unclear. Thus, maximum synthesis and Mann-Kendall trend (MK) test with Sen's Slope methods are employed to reveal the spatiotemporal variation characteristics of AOD over the FWP. The Potential Source Contribution Function (PSCF) model was applied to analyze the potential source contribution of AOD over the FWP. Results demonstrated that the AOD in spatial pattern exhibited consistency with the topography. AOD over the FWP fluctuated annually from 2000 to 2020, with an increase in the previous decade followed by a gradual decline after 2011. There was a significant monthly variation in AOD with higher values in August (0.47±0.21) and lower in November (0.29±0.12). A positive AOD trend was confirmed from 2000 to 2010 yet a negative trend is identified from 2011 to 2020. The sulfate aerosol (AODSU) exhibited an increasing trend over an extended period. Clear-sky radiation shows a negative trend at the surface and the top of the atmosphere (TOA) from 2000 to 2010, which is consistent with the trend in AOD. The AOD in FWP was primarily influenced by local emissions, with contributions from northern and northwestern sources. This research offers an enhanced overarching comprehension of the distribution and regional climate effects of aerosols over the FWP.

Extreme summer temperature anomalies over Greenland largely result from clear-sky radiation and circulation anomalies

The polar regions have been undergoing amplified warming in recent years. In particular, Greenland has experienced anomalously warm summers with intense melt rates. We employ a surface radiation budget framework to examine the causes for positive and negative summer temperature anomaly events over Greenland from 1979 to 2021. We found a dominant contribution of the clear-sky downwelling longwave radiation and the surface albedo feedback to temperature anomalies. Atmospheric temperature perturbations dominate the effect of anomalous emissivity on clear-sky downwelling longwave radiation. In warm years, enhanced turbulent heat exchange due to increased surface temperature and diabatic warming in the troposphere induces adiabatic heating of the atmosphere, enhanced moisture advection, and a high-pressure anomaly with a blocking-like anti-cyclonic circulation anomaly following peak temperature days. Different modes of natural climate variability, in particular, related to blocking over Greenland, can further amplify or dampen the ongoing warming trend, causing extreme temperature events.

The Predictability of a Heavy Rainfall Event during the Summer of 2022 Using an All-sky Radiance Assimilation Experiment

This paper presents the results of the recent development of the all-sky radiance assimilation system in the Korean Integrated Model (KIM). In the cycled analysis and forecast experiments, the increased coverage of radiance data in cloudy regions improved the quality of initial fields for mass variables, temperature and humidity. The experimental period covered the record-breaking heavy rainfall event on August 9, 2022. We examined the simulation accuracy of the western North Pacific subtropical high (WNPSH) in both clear- and all-sky experiments. In the clear-sky experiment, northward propagation of the WNPSH was restricted. A humid bias exists with clear-sky radiance assimilation over the WNPSH region. Since humid air is lighter than dry air, in this situation, the geopotential height (GPH) should be lower to achieve the same pressure, and a low-pressure bias occurs. All-sky radiance assimilation dries the moisture field, which helps elevate the GPH over the WNPSH region. The expansion of the WNPSH yielded a steeper confrontation in the air between the land and ocean around the southeastern sea of the Korean Peninsula to predict the strength of rainfall events more accurately. A more accurate simulation of the jet stream outlet was also demonstrated in an all-sky experiment. This study shows that the all-sky radiance assimilation can help to more accurately predict extreme rainfall events via proper simulations of large-scale fields.

All‐sky assimilation of FY‐4A AGRI water vapor channels: An observing system experiment study for south Asian monsoon prediction

AbstractIn this study, a month‐long parallel experiment is conducted to assess the assimilation effects of all‐sky radiance (ASR) versus clear‐sky radiance (CSR) in the single and multiple water vapor (WV) channels provided by the Advanced Geostationary Radiation Imager (AGRI) onboard the Fengyun‐4A (FY‐4A) satellite. The Weather Research and Forecasting model data assimilation system (WRFDA) is utilized for assimilating the FY‐4A AGRI WV observations. Compared with the CSR, the assimilated data of the ASR increases by ~1.7 times in WV channel 9 and around 2.4 times in the multiple WV channels (channels 9 and 10). Both the CSR and ASR assimilation results demonstrate that the simulated brightness temperature (TB) from the WRF analyses is closer to the TB observations from Sondeur Atmospherique du Profil d'Humidite Intertropicale par Radiometrie (SAPHIR) channels 1–2 and Microwave Humidity Sounder (MHS) channel 3, as compared with the control experiment where only conventional data are assimilated. Furthermore, a larger improvement is noted in assimilation of multiple WV channel against assimilation of a single WV channel for both CSR and ASR runs. Overall, the analyses and forecasts generated from the ASR run exhibit superior performance compared with the CSR run when verified against SAPHIR and MHS measurements, as well as the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) analyses. The verification of the rainfall predicted by the WRF against the Global Satellite Mapping of Precipitation (GSMaP) products over India indicates that the assimilation of the ASR in multiple WV channels has the largest impact on rainfall prediction. Moreover, the ASR run demonstrates an accurate prediction of heavy rainfall events that are missed in the control experiment and underestimated in the CSR run.

Observations and Estimates of Wet-Bulb Globe Temperature in Varied Microclimates

Abstract Wet-bulb globe temperature (WBGT) is used to assess environmental heat stress and accounts for the influences of air temperature, humidity, wind speed, and radiation on heat stress. Measurements of WBGT are highly sensitive to slight changes in environmental conditions and can vary several degrees Celsius across small distances (tens to hundreds of meters). Relative to observations with an International Organization for Standardization (ISO)-compliant WBGT meter, this work assesses the accuracy of WBGT measurements made with a popular handheld meter (the Kestrel 5400 Heat Stress Tracker) and WBGT estimates. Measurements were made during the summers of 2019–21 in a variety of suburban and urban environments in North Carolina, including three high school campuses. WBGT can be estimated from standard weather station variables, and many of these stations report cloud cover in lieu of solar radiation. Therefore, this work also evaluates the accuracy of clear-sky radiation estimates and adjustments to those estimates based on cloud cover. WBGT estimated with the method from Liljegren et al. from a weather station were on average 0.2°C warmer than Observed WBGT, while the Kestrel 5400 WBGT was 0.7°C warmer. Large variations in WBGT were observed across surfaces and shade conditions, with differences of 0.9°C (0.3°–1.4°C) between a tennis court and a neighboring grass field. The method for estimating clear-sky radiation in Ryan and Stolzenbach was most accurate and the clear-sky radiation modified by percentage cloud cover was found to be within 75 W m−2of observations on average. Significance Statement Wet-bulb globe temperature (WBGT) is a heat stress index that accounts for the effects of air temperature, humidity, wind, and radiation on humans. However, WBGT is not routinely measured at weather stations. This work demonstrated the accuracy of estimating WBGT with methods from Liljegren et al. (2008), finding it to be more accurate than measurements from a popular handheld meter, the Kestrel 5400 Heat Stress Tracker. Variations in WBGT that result in different danger levels were found between measurements over a tennis court and a neighboring grass field, and between sun and shade conditions. Understanding the magnitude of these differences and the biases with WBGT estimates and measurements can inform the planning of outdoor activity to robustly safeguard health.

Quantitation of the Surface Shortwave and Longwave Radiative Effect of Dust with an Integrated System: A Case Study at Xianghe.

Aerosols play a crucial role in the surface radiative budget by absorbing and scattering both shortwave and longwave radiation. While most aerosol types exhibit a relatively minor longwave radiative forcing when compared to their shortwave counterparts, dust aerosols stand out for their substantial longwave radiative forcing. In this study, radiometers, a sun photometer, a microwave radiometer and the parameterization scheme for clear-sky radiation estimation were integrated to investigate the radiative properties of aerosols. During an event in Xianghe, North China Plain, from 25 April to 27 April 2018, both the composition (anthropogenic aerosol and dust) and the aerosol optical depth (AOD, ranging from 0.3 to 1.5) changed considerably. A notable shortwave aerosol radiative effect (SARE) was revealed by the integrated system (reaching its peak at -131.27 W·m-2 on 26 April 2018), which was primarily attributed to a reduction in direct irradiance caused by anthropogenic aerosols. The SARE became relatively consistent over the three days as the AODs approached similar levels. Conversely, the longwave aerosol radiative effect (LARE) on the dust days ranged from 8.94 to 32.93 W·m-2, significantly surpassing the values measured during the days of anthropogenic aerosol pollution, which ranged from 0.35 to 28.67 W·m-2, despite lower AOD values. The LARE increased with a higher AOD and a lower Ångström exponent (AE), with a lower AE having a more pronounced impact on the LARE than a higher AOD. It was estimated that, on a daily basis, the LARE will offset approximately 25% of the SARE during dust events and during periods of heavy anthropogenic pollution.

SkyGAN: Realistic Cloud Imagery for Image‐based Lighting

AbstractAchieving photorealism when rendering virtual scenes in movies or architecture visualizations often depends on providing a realistic illumination and background. Typically, spherical environment maps serve both as a natural light source from the Sun and the sky, and as a background with clouds and a horizon. In practice, the input is either a static high‐resolution HDR photograph manually captured on location in real conditions, or an analytical clear sky model that is dynamic, but cannot model clouds. Our approach bridges these two limited paradigms: a user can control the sun position and cloud coverage ratio, and generate a realistically looking environment map for these conditions. It is a hybrid data‐driven analytical model based on a modified state‐of‐the‐art GAN architecture, which is trained on matching pairs of physically‐accurate clear sky radiance and HDR fisheye photographs of clouds. We demonstrate our results on renders of outdoor scenes under varying time, date and cloud covers. Our source code and a dataset of 39 000 HDR sky images are publicly available at https://github.com/CGGMFF/SkyGAN.

Direct Assimilation of Ground-Based Microwave Radiometer Clear-Sky Radiance Data and Its Impact on the Forecast of Heavy Rainfall

Ground-based microwave radiometer (GMWR) data with high spatial and temporal resolution can improve the accuracy of weather forecasts when effectively assimilated into numerical weather prediction. Nowadays, the major method to assimilate these data is via indirect assimilation by assimilating the retrieved profiles, which introduces large retrieval errors and cannot easily be represented by an error covariance matrix. Direct assimilation, on the other hand, can avoid this issue. In this study, the ground-based version of the Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV-gb) was selected as the observation operator, and a direct assimilation module for GMWR radiance data was established in the Weather Research and Forecasting Model Data Assimilation (WRFDA). Then, this direct assimilation module was applied to assimilate GMWR data. The results were compared to the indirect assimilation experiment and demonstrated that direct assimilation can more effectively improve the model’s initial fields in terms of temperature and humidity than indirect assimilation while avoiding the influence of retrieval errors. In addition, direct assimilation performed better in the precipitation forecast than indirect assimilation, making the main precipitation center closer to the observation. In particular, the improvement in the precipitation forecast with a threshold of 60 mm/6 h was obvious, and the corresponding TS score was significantly enhanced.

All‐sky infrared radiance assimilation of a geostationary satellite in the Japan Meteorological Agency's global system

AbstractAll‐sky assimilation of infrared (IR) radiances has been developed for water vapor bands of the geostationary satellite Himawari‐8 in the operational global data assimilation system. Cloud‐dependent quality control, bias correction, and observation error modeling are essential developments to effectively utilize the all‐sky radiances (ASRs). ASR assimilation increases the assimilated number of observations by 2.8 times and improves the coverage relative to the traditional clear‐sky radiance (CSR) assimilation. The additional observations better alleviate model dry biases in the middle and upper tropospheric humidity. ASR assimilation brings statistically significant improvements in the background (first guess) in humidity, temperature, and wind over the CSR assimilation. It also better improves short‐range forecasts of the middle and upper tropospheric temperature and humidity up to day 3 in the Tropics. A mixed impact in the stratospheric temperature is under investigation. The impacts of various aspects of the ASR assimilation configuration are evaluated with sensitivity assimilation experiments. The interband correlation and cloud‐dependent standard deviation of the observation error are crucial, whereas the cloud dependency of the correlation is not so important. Although ASRs at a single band were assimilated in many previous studies targeting severe weather using research‐based regional assimilation systems due to decreasing independent information in the presence of clouds, they are distinctly inferior to not only ASRs at multiple bands but also CSRs at multiple bands in a global data assimilation system that contains fewer cloud‐affected scenes. The cloud‐dependent bias correction predictors are essential in the presence of observation‐minus‐background bias that increases with cloud effects.

Impacts of Assimilating FY-4A AGRI Clear-Sky Water Vapor Radiance on Short-Range Weather Prediction during Indian Summer Monsoon

ABSTRACT This study aims to assess the impacts of assimilating the clear-sky radiances from the Advanced Geosynchronous Radiation Imager (AGRI) onboard the Fengyun-4A (FY-4A) satellite on 72-h forecasts. First, we compare the water vapour (WV) brightness temperature (TB) in July 2018 from the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) analyses and Weather Research and Forecasting (WRF) forecasts with the clear-sky AGRI WV channel observations. The results suggest that the NCEP GDAS analyses are more consistent with the AGRI observations than the WRF forecasts, and the AGRI observations can be utilized to improve the initial conditions of the WRF model by data assimilation, especially in water vapour and surface temperature. After the preliminary verification, two identical cycling assimilation experiments are performed with and without the AGRI WV TB assimilation for a month. The results reveal that the WRF forecasts with AGRI TB assimilation are closer to satellite observations than the first guess in both WV channels. The validation with WV channel data of the Microwave Humidity Sounder (MHS) and SAPHIR sensors indicates that after the AGRI data assimilation, the errors are smaller than in the control experiment (without AGRI assimilation). The assimilation of the TB observed by AGRI WV channels shows a remarkable positive impact on moisture forecasts at middle and upper levels. Comparison of the TB from the WRF forecasts with the MHS observations suggests that the AGRI WV channel assimilation can improve the predictions. Overall, assimilating AGRI WV observations can positively influence the WRF analyses and forecasts.

Impacts of Observation Forward Operator on Infrared Radiance Data Assimilation with Fine Model Resolutions

Abstract All-sky radiance assimilation often has non-Gaussian observation error distributions, which can be exacerbated by high model spatial resolutions due to better resolved nonlinear physical processes. For ensemble Kalman filters, observation ensemble perturbations can be approximated by the linearized observation operator (LinHx) that uses the observation operator Jacobian of ensemble mean rather than the full observation operator (FullHx). The impact of observation operator on infrared radiance data assimilation is examined here by assimilating synthetic radiance observations from channel 1025 of GIIRS with increased model spatial resolutions from 7.5 km to 300 m. A tropical cyclone is used, while the findings are expected to be generally applied. Compared to FullHx, LinHx provides larger magnitudes of correlations and stronger corrections around observation locations, especially when all-sky radiances are assimilated at fine model resolutions. For assimilating clear-sky radiances with increasing model resolutions, LinHx has smaller errors and improved vortex intensity and structure than FullHx. But when all-sky radiances are assimilated, FullHx has advantages over LinHx. Thus, for regimes with more linearity, LinHx provides stronger correlations and imposes more corrections than FullHx; but for regimes with more nonlinearity, LinHx provides detrimental non-Gaussian prior error distributions in observation space, unrealistic correlations, and overestimated corrections, compared to FullHx. Significance Statement Assimilating satellite radiances has been essential for numerical weather prediction. All-sky radiance assimilation can improve the analyses and forecasts of tropical cyclones, but it often has non-Gaussian observation error distributions. With increased model resolutions, nonlinear physical processes can be better resolved, which leads to non-Gaussian error distributions of state variables. Nonlinearity and non-Gaussianity impose great challenges for data assimilation (DA), since most DA theories assume linear processes and Gaussian error distributions. As the spatial resolutions of observations and numerical models will keep increasing, the potential issues of assimilating high-spatial-resolution observations given fine model resolutions need to be examined. The linearized observation forward operator, as an alternative to remedy non-Gaussianity for radiance DA, is investigated. With model resolution increasing from 7.5 km to 300 m, the linearized observation operator has advantages over the full observation operator for assimilating clear-sky radiances, but the opposite is true for assimilating all-sky radiances.

Assimilation of Clear-sky FY-4A AGRI radiances within the WRFDA system for the prediction of a landfalling Typhoon Hagupit (2020)

The capability of assimilating Advanced Geostationary Radiance Imager (AGRI) radiances of FengYun-4A (FY-4A) satellite is realized in the framework of the Weather Research and Forecasting model's Data Assimilation (WRFDA) system. Two experiments are carried out based on a landfalling Typhoon Hagupit to discuss the added values of assimilating the clear-sky radiances on typhoon's analysis and prediction. One experiment assimilates both the AGRI radiances and the Global Telecommunications System (GTS) conventional data, while another experiment only applies GTS conventional data. The results show that the errors of the analysis fields are reduced after the assimilation of AGRI radiances, which can be reflected by the vertical root mean square error (RMSE) profile of both dynamic and thermodynamic variables against the radiosonde observations. Besides, the final improvement of the track and rainfall prediction can possibly be accredited to the analyzed 500 hPa geopotential height increment and the vertically averaged horizontal water vapor flux to some degree. The area is enlarged with relative humidity exceeding 95% by the assimilation of AGRI radiances in the typhoon core, leading to the refinement of both the rainfall distribution and intensity in the prediction. With the improved dynamic and thermodynamic fields, the track of the AGRI experiment is more accurate with a mean error 37 km in the whole 36 h.

Impact of assimilating atmospheric motion vectors from Himawari-8 and clear-sky radiance from FY-4A GIIRS on binary typhoons

Binary typhoons (Maysak and Haishen) uncommonly hit northeastern China in 2020, which brought historical extreme precipitation to this region within less than a week. The impact of high-frequency (15-min) assimilating atmospheric motion vectors (AMVs) from Himawari-8 and clear-sky radiance from Fengyun-4A (FY-4A) Geostationary Interferometric Infrared Sounder (GIIRS) on this rare case has been investigated based on the Weather Research and Forecasting Model (WRF) and three-dimensional variational (3D-Var) data assimilation system. The study indicates that the dynamic adjustment is obvious from assimilated hourly AMVs information, but it still needs to be combined with the 15-min FY-4A thermal field adjustment, which is essential for better forecast simulations of minimum sea level pressure (MSLP) and landfall precipitation. A detailed typhoon structure is accurately reproduced for Maysak (Haishen) with fewer (more) anomalies of upper-level warm temperatures and lower-level negative geopotential heights in the decay (intensification) phase. Meanwhile, the performance of three hourly landfall precipitation by Maysak is evaluated with better spatial distribution and higher equitable threat scores (ETS) for the large threshold (20 mm), resulting from wet bias reduction by much drier water vapor conditions in the analysis and more precise forecasts of relative humidity, water vapor transportation, and its divergence. However, it achieves neutral to negative impacts on track forecasts for Maysak and wind simulations at different levels. This research may provide guidance for monitoring and forecasting typhoons of assimilation from different satellite information in mid-to-high latitude regions in East Asia.

Effect of phase-change materials in the performance of a solar air heater

This work presents an experimental analysis of a double-channel solar air heater (SAH) with and without phase-change material (PCM) as thermal energy storage system (TES). Two identical prototypes were designed and constructed, and one of them was modified to house macro- encapsulated PCM in the absorber plate. Both collectors were evaluated in an experimental setup instrumented for hot air temperature and velocity, solar radiation, temperature probes in the glass cover, absorber plate, PCM storage system, and a weather station to record the environmental conditions. To evaluate the performance of the SAH under sudden variations of solar radiation, three different case studies were considered with varying conditions of weather: clear sky and high radiation, partially cloudy, and clear sky with a substantial drop in solar radiation at noon. The maximum outlet temperatures reached by the SAH with PCM were 82 °C, 62 °C, and 79.5 °C for the three cases, respectively. The outlet temperature of the SAH without PCM was consistently 10 °C lower compared to the collector with PCM. The PCM maintained the heating during day irradiation transients and extended it after dusk, without any decrease in the thermal efficiency. Further studies of modeling and design optimization appear very pertinent.

Constrained future brightening of solar radiation and its implication for China's solar power.

As Earth's primary energy source, surface downward solar radiation (R s) determines the solar power potential and usage for climate change mitigation. Future projections of R s based on climate models have large uncertainties that interfere with the efficient deployment of solar energy to achieve China's carbon-neutrality goal. Here we assess 24 models in the latest Coupled Model Intercomparison Project Phase 6 with historical observations in China and find systematic biases in simulating historical R s values likely due to model biases in cloud cover and clear-sky radiation, resulting in largely uncertain projections for future changes in R s. Based on emergent constraints, we obtain credible R s with narrowed uncertainties by ∼56% in the mid-twenty-first century and show that the mean R s change during 2050-2069 relative to 1995-2014 is 30% more brightening than the raw projections. Particularly in North China and Southeast China with higher power demand, the constrained projections present more significant brightening, highlighting the importance of considering the spatial changes in future Rs when locating new solar energy infrastructures.

Cloud Detection Method Based on All-Sky Polarization Imaging.

Sky cloud detection has a significant application value in the meteorological field. The existing cloud detection methods mainly rely on the color difference between the sky background and the cloud layer in the sky image and are not reliable due to the variable and irregular characteristics of the cloud layer and different weather conditions. This paper proposes a cloud detection method based on all-sky polarization imaging. The core of the algorithm is the “normalized polarization degree difference index” (NPDDI). Instead of relying on the color difference information, this index identifies the difference between degree of polarization (DoPs) of the cloud sky and the clear sky radiation to achieve cloud recognition. The method is not only fast and straightforward in the algorithm, but also can detect the optical thickness of the cloud layer in a qualitative sense. The experimental results show a good cloud detection performance.

Improving the prediction of heavy rainfall with rapid-update dual-resolution hybrid En3DVar assimilation of all-sky AHI infrared water vapor radiances

The Advanced Himawari Imager (AHI) on board Himawari-8 provides continuous high-resolution observations of severe weather phenomena in space and time, providing a good data source for the rapidly updated cycling data assimilation in numerical weather prediction (NWP). In this study, the all-sky AHI water vapor infrared radiances were rapidly assimilated using a dual-resolution hybrid EnVar method to introduce the flow-dependent ensemble information with a reduced ensemble cost in a case study. Considering the greatly increased computational costs for all-sky radiance data assimilation, the sensitivity of the all-sky radiance data assimilation to the resolution of ensemble error covariance as well as the cycling frequency using dual-resolution EnVar was investigated. The impact of all-sky radiance data assimilation using the dual-resolution hybrid EnVar was then compared to the clear-sky radiance data assimilation.From the case study, it was found that the dual-resolution hybrid EnVar and the full-resolution hybrid EnVar generally performed comparable for the all-sky assimilation of the AHI water vapor radiances in this study. Both show great advantages over 3DVar in analyses and forecasts with different leading time for model state variables. However, the former cost much fewer computational resources with only a tiny loss of the accuracy. For the assimilation frequency of all-sky radiances using the dual-resolution hybrid EnVar, it was found that the half-hourly and hourly test both obtain the better results than the other two (namely the 10-minutely test and 3-hourly test). The former two have the comparable performances in rainfall forecast although the half-hourly test is better. Finally, in the dual-resolution hybrid EnVar framework, the all-sky AHI radiance assimilation impact was studied versus the clear-sky radiances as well as the conventional observations in a case study. The results present a generally positive improvement of the rainfall forecast with the larger rainfall thresholds, caused by the assimilation of the cloud-influenced AHI water vapor radiances.

Effects of spatial scale of atmospheric reanalysis data on clear-sky surface radiation modeling in tropical climates: A case study for Singapore

Solar resource assessments most generally require atmospheric information, which is customarily acquired from gridded datasets. The spatial scale mismatch problem, i.e., the difference in spatial representativeness of gridded data and in situ measurements, therefore becomes relevant. This study examines how the gridded data used as inputs to clear-sky radiation models can affect their performance at urban scale. The tropical island of Singapore is selected for the case study. Aerosol optical depth at 550 nm (AOD550), Å ngström exponent (AE), and precipitable water (PW) from both the MERRA-2 reanalysis and ground-based stations (AERONET and SuomiNet) are collected between 2013–2020. Firstly, it is found that, relatively to the AERONET ground truth, the bias in MERRA-2’s AOD550 is more prominent than that in AE or PW. Next, the bias propagation from the gridded inputs (AOD550, AE, and PW) to clear-sky radiation predictions is explored using various models. The estimated clear-sky direct normal irradiance (DNIcs) is more sensitive to AOD550 variation than the clear-sky global horizontal irradiance (GHIcs). Six clear-sky radiation models, five of which accept MERRA-2 gridded inputs, are compared with each other, and with the in situ irradiance measurements recorded at 9 sites. The inter-model difference across Singapore is remarkably consistent because the whole island fits inside a single MERRA-2 grid cell. Under high-AOD550 situations, however, the inter-model deviation becomes large for both GHIcs and DNIcs. The conventional model-versus-measurement comparison shows that each model achieves very different site-to-site performance, largely because the spatially-averaged inputs cannot fully represent the micro-climatic variability. Relatively speaking, no clear-sky radiation model significantly outperforms its peers. The simple MAC2 model and the empirical (locally derived) Yang GHIcs-only model are recommended for Singapore.

Simplified estimation modeling of land surface solar irradiation: A comparative study in Australia and China

Solar irradiation maps are fundamental geospatial datasets that have been used in a variety of research fields. However, it is difficult to estimate the continuous distribution of solar irradiation over large areas accurately by using conventional interpolation or extrapolation methods based on only a few observation stations. To tackle this problem, this study proposed a method to estimate spatially continuous land surface solar irradiation based on four machine learning models, namely, Gradient Boosting Machine (GBM), Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron (MLP). Clear-sky solar irradiation data were computed based on time and location, cloud optical thickness (COT) and aerosol optical thickness (AOT) that significantly influence solar irradiation were retrieved from Himawari-8 meteorological satellite images, and land surface solar irradiation data were obtained from observation stations for training and evaluation. To explore the weather effects on land surface solar irradiation, air temperatures, humidity, wind, and atmospheric pressure were also quantified and integrated into the models. As a comparative study, this study collected six-year historical data and estimated solar distribution at a 5-km spatial resolution in Australia and China. Based on the coefficient of determination (R2), normalized Root Mean Square Error (nRMSE), normalized mean bias error (nMBE), and consumption of time (t), the results show that GBM achieved the highest accuracy with R2>0.7 at all stations, followed by RF, SVR, and MLP. It suggests that the proposed method can provide an accurate and reliable estimation of land surface solar irradiation, compared with the theoretical solar irradiation without the obstacle of the atmosphere. The annual solar distribution maps created by the built methods indicate that the proposed method is simple and effective for large geographical regions and can be used worldwide when similar datasets are obtained.

Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the “21·7” Henan Extremely Persistent Heavy Rainfall

Assimilation of the FY-4A AGRI Clear-Sky Radiance Data in a Regional Numerical Model and Its Impact on the Forecast of the “21·7” Henan Extremely Persistent Heavy Rainfall