Upward Longwave Radiation Research Articles

Single-footprint retrieval of clear-sky surface longwave radiation from hyperspectral AIRS data

Surface longwave radiation (SLR) derived from remotely sensed data facilitates understanding of the SLR in global climate change. Hyperspectral infrared sounders aboard space platforms provide information on the surface and vertical structure of Earth’s atmosphere. However, currently, SLR products estimated from these observations are unavailable, which hampers their application potential for Earth’s radiation budget in the context of global warming. To address this issue, we developed simple and effective SLR model under clear-sky conditions using at-sensor spectral radiances from Atmospheric Infrared Sounder (AIRS). The model was found to be insensitive to AIRS instrument noise, and showed good performances based on a simulation dataset. The AIRS footprint geometrical model was proposed to match the AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) data to estimate the cloud fraction. Validation against ground-based measurements found that the surface upward longwave radiation model has a bias of 3.18 W/m2, root-mean-square error (RMSE) of 30.51 W/m2, and R2 of 0.84; the surface downward longwave radiation model has a bias of 0.77 W/m2, RMSE of 29.09 W/m2, and R2 of 0.78. The large validation biases at two ground sites reflect the limited spatial representativeness for AIRS footprints. Terrain-induced altitude differences and spatial inhomogeneity can redistribute the spatial distributions of SLR. Moreover, the model performances were weakly dependent on seasonal variation. The results indicate that the proposed model provides a foundation for the further development of operational SLR products.

How Do Different Reanalysis Radiation Datasets Perform in West Qilian Mountains?

Solar radiation plays an important role in the cryospheric water cycle, especially in alpine regions. This study presents an evaluation of the Modern-Era Retrospective analysis for Research and Applications 2 (MERRA2), ERA5, High Asia Refined analysis version 2 (HAR v2), JRA-55, and National Centers for Environmental Prediction/Climate Forecast System Reanalysis datasets at different time scales by comparing observed datasets from July 2010 to December 2015 at 4,550 m in the Laohugou Basin. In terms of shortwave radiation, ERA5 performs significantly better than the other reanalysis radiation datasets. For downward shortwave radiation, HAR v2 performs better than ERA5 on only two timescales, 3 months and half-year, with mean absolute errors (MAEs) of 13.28 and 7.96 w/m2. The upward shortwave radiation, ERA5, outperforms the other reanalysis datasets on all 12 timescales. For downward longwave radiation, ERA5 also performs significantly better, with only MERRA2 outperforming ERA5 on the daily scale and annual scale, with R2, bias, root mean square error, and MAE of 0.6, 0.95, −9.51 w/m2, −9.41 w/m2, 34.98 w/m2, 9.46 w/m2, and 27.52 w/m2, 9.41 w/m2, respectively. In the upward longwave radiation, HAR v2 performs better than the other reanalysis datasets on all timescales, except for ERA5, which has a better R2 of 0.92 on the annual scale. All the reanalysis datasets can show the variation trend of the four radiation parameters in different seasons and achieve a better performance in winter. Therefore, ERA5 is recommended for regions without shortwave radiation observations, and HAR v2 and ERA5 are recommended for longwave radiation simulations. Although there are obvious shortcomings in the reanalysis radiation datasets, they still provide important supplementary information for research in high-altitude areas, where the observed datasets are too sparse.

The sensitivity of parameterization schemes in thermodynamic modeling of the landfast sea ice in Prydz Bay, East Antarctica

Abstract Based on the measurements conducted over the landfast sea ice in Prydz Bay, East Antarctica during the sea-ice growth season in 2016, various parameterization schemes in the high-resolution thermodynamic snow/ice model HIGHTSI are evaluated. The parameterization scheme of turbulent fluxes produces the largest errors compared with the parameterization schemes for other surface heat fluxes. However, the sea-ice thickness simulation is most sensitive to the differences in upward longwave radiation at the surface. In addition, the sea-ice thickness simulation during the growth season is highly sensitive to the oceanic heat flux, and a new oceanic heat flux parameterization scheme based on the bulk method is proposed. The new parameterization scheme is tested in a second year, and it significantly improves the model performance relative to the standard configuration when compared against observations. Finally, the seasonal variation in the heat budget and its influence on the sea-ice thickness variation are analyzed. The net shortwave radiation, sensible heat flux and conductive heat flux (the net longwave radiation and latent heat flux) are found to be the surface heat sources (heat sinks) during the growth season. The larger conductive heat flux and the smaller oceanic heat flux can intensify the growth of sea ice.

Recent Observed Changes in Extreme High‐Temperature Events and Associated Meteorological Conditions over Africa

AbstractMore frequent and intensified high‐temperature extremes are acceptable indicators of global warming, which pose serious socio‐economic impacts. In the present research, the Climate Prediction Center daily minimum and maximum temperature are used to characterize high temperatures into intensity of hot days (TXx), hot nights (TNx), and frequency indices based on the 90th percentile of hot days (TX90p) and hot nights (TN90p) as defined by the Expert Team on Climate Change Detection and Indices from 1981 to 2020 over Africa. The regression approach based on iterative reweighted least squares and correlation analyses are used to estimate the trends in extreme high‐temperature events and their relationship with various meteorological variables. Furthermore, the Pruned exact linear time algorithm is used to assess if the maximum temperature experienced an abrupt change. Results show that many parts of Africa experienced more frequent and intensified hot days and nights in the current period (1998–2020) compared to the recent past (1981–1997), suggesting a clear shift in climate. Thus, we used the climatological mean differences between meteorological parameters before and after the breakpoint to assess the relationship between atmospheric conditions and extreme high‐temperature events. As a result, we found that the current period observed an increase in the geopotential height at 500 hPa and reduced total cloud cover, as well as an increase in upward longwave radiation resulting in an upsurge in the frequency of hot days over many African sub‐regions. The present study's findings provide useful information for future planning and development of early warning systems to cope with risks associated with hot extremes.

Retrieval of Daytime Surface Upward Longwave Radiation Under All-Sky Conditions With Remote Sensing and Meteorological Reanalysis Data

Surface upward longwave radiation (SULR) is a key parameter that regulates surface radiation budget balance and matter-energy exchange. However, the state-of-the-art SULR retrieval methods based on remotely sensed data are only effective under clear skies, which mean that existing methods are unable to generate spatiotemporal continuous SULR product at regional or global scale. Herein, taking the advantage of long-pending abundant ground-based radiation observations, satellite products and meteorological reanalysis data, a data-driven random forest (RF) method is proposed to retrieve the instantaneous SULR under all-sky conditions. Based on spectral samples of different surface types and simulation results from the moderate resolution atmospheric transmission (MODTRAN), spectral transformation is carried out to transform SULR of various measured domains into the defined 4~100 μm domain at first. SULR and surface downward shortwave radiation (SDSR) observations from seven stations of the Surface Radiation Budget Network (SURFRAD) and nine stations of the Baseline Surface Radiation Network (BSRN) are used in model’s training and testing procedures, and the RF model achieves a high accuracy with the root-mean-square error (RMSE) of 10.45 W/m² on test set. In model evaluation, ground measurements from 14 stations of FLUXNET have been used, and the overall RMSE is 18.40 W/m². In the actual application process, SDSR is estimated by remotely sensed data of Meteosat Second Generation (MSG). The accuracy of RF model has been validated with the observations from five stations of BSRN in 2021, and RMSEs are 17.00, 10.94, 12.17, 27.89 and 12.54 W/m², respectively. Validation result shows that the data-driven method is capable of estimating SULR under all-sky conditions with a high accuracy. Finally, sensitivity analysis has been carried out, and the established RF model keeps robust even though there are great uncertainties among input parameters.

Sensitivity of Summertime Convection to Aerosol Loading and Properties in the United Arab Emirates

The Weather Research and Forecasting (WRF) model is used to investigate convection–aerosol interactions in the United Arab Emirates (UAE) for a summertime convective event. Both an idealized and climatological aerosol distributions are considered. The convection on 14 August 2013 was triggered by the low-level convergence of the cyclonic circulation associated with the Arabian Heat Low (AHL) and the daytime sea-breeze circulation. Numerical experiments reveal a high sensitivity to aerosol properties. In particular, replacing 20% of the rural aerosols by carbonaceous particles has a comparable impact on the surface radiative fluxes to increasing the aerosol loading by a factor of 10. In both cases, the UAE-averaged net shortwave flux is reduced by ~90 W m−2 while the net longwave flux increases by ~51 W m−2. However, when the aerosol composition is changed, WRF generates 20% more precipitation than when the aerosol loading is increased, due to a broader and weaker AHL. The surface downward and upward shortwave and upward longwave radiation fluxes are found to scale linearly with the aerosol loading. An increase in the amount of aerosols also leads to drier conditions and a delay in the onset of convection due to changes in the AHL.

Characteristics of Turbulence and Aerosol Optical and Radiative Properties during Haze–Fog Episodes in Shenyang, Northeast China

The characteristics of turbulence in the planetary boundary layer (PBL) and the aerosol optical and radiative properties during haze and haze–fog mixed episodes on 22–27 January 2021, in Shenyang, a provincial city in Northeast China, were analyzed using meteorological and aerosol observations. During the haze episode, the hourly mean PM2.5 concentration reached a maximum of 337 µg m−3 and visibility decreased to 1.6 km. The PM2.5 concentration decreased gradually during the haze–fog mixed episode as a result of the scavenging effects of fog, but visibility mostly remained below 1 km owing to high ambient relative humidity (>90%). During the haze–fog mixed episode, an increasing proportion of PM2.5 led to a higher ratio of the backward to the total scattering coefficient. As fog occurred, downward shortwave radiation arriving at the surface was significantly reduced, and upward longwave radiation increased and almost equaled the downward longwave radiation, which can be used as a good indicator for distinguishing haze and fog. Mechanical turbulence was weak during both episodes, and latent heat flux varied within a wider range during the haze–fog mixed episode. The PBL dynamic structure affected the vertical distribution of aerosols/fog droplets. Aerosol-rich layers appeared at altitudes below 0.5 km and above 0.6 km during the haze episode. The elevated aerosol layer was related to the aerosol transport from upstream polluted areas caused by strong upper-level turbulence, and it began to mix vertically after sunrise because of convective turbulence. Aerosols and fog droplets were mostly trapped in a shallower PBL with a height of 0.2–0.4 km during the haze–fog mixed episode because of weaker turbulence.

Playing on natural or artificial turf sports field? Assessing heat stress of children, young athletes, and adults in Hong Kong

Exercising in an unusually hot environment may aggravate exertional heat illness. Turf material significantly affects the microenvironment and heat-stress sensation of sports-field users. However, the difference in human- biometeorological effects between different sports-field turf materials demands further investigation. This study compared artificial (AT) with natural turf (NT) fields, investigating three age groups (children, young athletes, and adults), two physical activities (playing soccer and walking), and three heat stress indicators (HI, Heat Index; WBGT, Wet Bulb Globe Thermometer; and COMFA, COMfort FormulA). The results showed heat-stress underestimation by HI and WBGT. In contrast, COMFA, incorporating comprehensive environmental and human physiological parameters, provided a more targeted and reliable heat-stress assessment. COMFA indicated a longer heat-stress duration exercising at AT than NT. Compared to NT, children suffered a 24% longer “Extreme danger” duration at AT in sunny daytime. The AT-NT difference in human-biometeorological effect was limited concerning human convection, evaporation, metabolic heat, and emitted longwave radiation, but was considerable in human absorbed radiation. AT had lower albedo than NT, hence field users absorbed more upward longwave radiation but less upward shortwave radiation, highlighting important control by the radiant environment. NT sports fields are recommended for a healthy outdoor thermal environment, especially for children.

Direct impact of solar farm deployment on surface longwave radiation

Motivated by a previous study of using the Moderate Resolution Imaging Spectroradiometers (MODIS) observations to quantify changes in surface shortwave spectral reflectances caused by six solar farms in the southwest United States, here we used a similar method to study the longwave effects of the same six solar farms, with emphases on surface emissivities and land surface temperature (LST). Two MODIS surface products were examined: one relying on generalized split-window algorithm while assuming emissivities from land cover classifications (MYD11A2), the other based on Temperature Emissivity Separation algorithm capable of dynamically retrieving emissivities (MYD21A2). Both products suggest that, compared to adjacent regions without changes before and after solar farm constructions, the solar farm sites have reduced outgoing radiances in three MODIS infrared window channels. Such reduction in upward longwave radiation is consistent with previous in situ measurements. The MYD11A2 results show constant emissivities before and after solar farm constructions because its land type classification algorithm is not aware of the presence of solar farms. The estimated daytime and nighttime LST reduction due to solar farm deployment are ∼1–4K and ∼0.2–0.9K, respectively. The MYD21A2 results indicate a decrease in Band 31 (10.78–11.28 μm) emissivity up to −0.01 and little change in Band 32 (11.77–12.27 μm) emissivity. The LST decreases in the MYD21A2 is slightly smaller than its counterpart in the MYD11A2. Laboratory and in situ measurements indicate the longwave emissivity of solar panels can be as low as 0.83, considerably smaller than MODIS retrieved surface emissivity over the solar farm sites. The contribution of exposed and shaded ground within the solar farm to the upward longwave radiation needs to be considered to fully explain the results. A synthesis of MODIS observations and published in situ measurements is presented. Implication for parameterizing such solar farm longwave effect in the climate models is also discussed.

Seasonal Changes in Arctic Cooling After Single Mega Volcanic Eruption

To investigate the pure long-term influence of single mega volcanic eruption (SMVE) of universal significance on Arctic temperature changes in summer and winter, the Samalas eruption in Indonesia which is the largest eruption over the past millennium is selected as an ideal eruption for simulation study based on Community Earth System Model. The significant Arctic cooling lasts for 16 years after the Samalas eruption. The obvious Arctic cooling shifts from summer to winter, and this seasonal change of cooling after the SMVE only exists in the high-latitude Arctic region. The cooling range in Arctic summer is larger than that in winter during the first 2 years, due to the strong weakening effect of volcanic aerosol on summer incident solar radiation and the snow-ice positive feedback caused by the rapid expansion of summer sea ice, while the winter sea ice in the same period doesn’t increase obviously. Starting from the third year, the Arctic winter cooling is more intense and lasting than summer cooling. The direct weakening effect of aerosol on solar radiation, which is the main heat source in Arctic summer, is greatly weakened during this period, making summer cooling difficult to sustain. However, as the main heat source in Arctic winter, the sea surface upward longwave radiation, sensible heat, and latent heat transport still maintain a large decrease. Furthermore, sea ice expansion and albedo increase result in the decrease in solar radiation and heat absorbed and stored by the ocean in summer. And the isolation effect of sea ice expansion on air-sea heat transfer in winter during this period makes the heat transfer from the ocean to the atmosphere correspondingly reduce in winter, thus intensifying the Arctic winter cooling. Additionally, the Arctic Oscillation (AO) changes from the negative phase to the positive phase in summer after the SMVE (such as Samalas), while it is reversed in winter. This phase change of AO is also one of the reasons for the seasonal changes in Arctic cooling.

Evaluation of Surface Upward Longwave Radiation in the CMIP6 Models with Ground and Satellite Observations

Surface upward longwave radiation (SULR) is an indicator of thermal conditions over the Earth’s surface. In this study, we validated the simulated SULR from 51 Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) through a comparison with ground measurements and satellite-retrieved SULR from the Clouds and the Earth’s Radiant Energy System, Energy Balanced and Filled (CERES EBAF). Moreover, we improved the SULR estimations by a fusion of multiple CMIP6 GCMs using multimodel ensemble (MME) methods. Large variations were found in the monthly mean SULR among the 51 CMIP6 GCMs; the bias and root mean squared error (RMSE) of the individual CMIP6 GCMs at 133 sites ranged from −3 to 24 W m−2 and 22 to 38 W m−2, respectively, which were higher than those found between the CERES EBAF and GCMs. The CMIP6 GCMs did not improve the overestimation of SULR compared to the CMIP5 GCMs. The Bayesian model averaging (BMA) method showed better performance in simulating SULR than the individual GCMs and simple model averaging (SMA) method, with a bias of 0 W m−2 and an RMSE of 19.29 W m−2 for the 133 sites. In terms of the global annual mean SULR, our best estimation for the CMIP6 GCMs using the BMA method was 392 W m−2 during 2000–2014. We found that the SULR varied between 386 and 393 W m−2 from 1850 to 2014, exhibiting an increasing tendency of 0.2 W m−2 per decade (p < 0.05).

Analysis of the Radiation Fluxes over Complex Surfaces on the Tibetan Plateau

Analysis of long-term, ground-based observation data on the Tibetan Plateau help to enhance our understanding of land-atmosphere interactions and their influence on weather and climate in this region. In this paper, the daily, monthly, and annual averages of radiative fluxes, surface albedo, surface temperature, and air temperature were calculated for the period of 2006 to 2019 at six research stations on the Tibetan Plateau. The surface energy balance characteristics of these six stations, which include alpine meadow, alpine desert, and alpine steppe, were then compared. The downward shortwave radiation at stations BJ, QOMS, and NAMORS was found to decrease during the study period, due to increasing cloudiness. Meanwhile, the upward shortwave radiation and surface albedo at all stations were found to have decreased overall. Downward longwave radiation, upward longwave radiation, net radiation, surface temperature, and air temperature showed increasing trends on inter-annual time scales at most stations. Downward shortwave radiation was maximum in spring at BJ, QOMS, NADORS, and NAMORS, due to the influence of the summer monsoon. Upward shortwave radiation peaked in October and November due to the greater snow cover. BJ, QOMS, NADORS, and NAMORS showed strong sensible heat fluxes in the spring while MAWORS showed strong sensible heat fluxes in the summer. The monthly and diurnal variations of surface albedo at each station were “U” shaped. The diurnal variability of downward longwave radiation at each station was small, ranging from 220 to 295 W·m−2.The diurnal variation in surface temperature at each station slightly lagged behind changes in downward shortwave radiation, and the air temperature, in turn, slightly lagged behind the surface temperature.

A comparative study on the surface radiation characteristics of photovoltaic power plant in the Gobi desert

In order to identify impacts of photovoltaic (PV) power plant on surface radiation, this paper conducted a comparative study on the surface radiation and surface albedo characteristics between the PV site and reference site in the Gobi area in Xinjiang, China in the summer of 2020. The results show that, the upward long-wave radiation at the PV site was significantly lower than that at the reference site in the night, while the two were basically the same during the daytime. The average surface albedo at the PV site (0.14) was 39.1% lower than that at the reference site (0.23). Net radiation was higher at the PV site than that at the reference site throughout the whole day. The average net radiation of the underlying surface at the PV site was 30.7% more than that at the reference site, 75% of which was contributed by lower upward shortwave radiation and 25% was due to nocturnal lower upward longwave radiation at the PV site.

Adaptation and validation of a voxel based energy transport model for conifer species

A spatially explicit energy balance model previously developed for deciduous trees was extended to account for physical differences in conifer species. These differences include the emission and scattering of radiation in needles compared to leaves as well as the boundary-layer conductance for needles. To validate the model, an array of sensors was placed in and around two separate isolated Picea pungens trees in a heterogeneous urban environment. Model validation examined components of the local-volume averaged needle energy budget utilizing radiative and turbulent fluxes as the forcing inputs. Analysis focused on the model's ability to reproduce integrated upward shortwave and longwave radiation, local radiation attenuation through the tree crown, and local needle surface temperature. The model performed quite well with R2 values above 0.9 for calculated versus measured integrated upward longwave and shortwave radiation and above 0.87 for needle surface temperature. The high level of agreement with experimental measurements was only possible with the modifications made to the boundary layer conductance for needles.

Why is the November Siberian High Intensity More Predictable by NCEP-CFSv2 Model?

As a critical system of the East Asian winter monsoon, the Siberian high has an important impact on the winter weather and climate anomalies in Eurasia. Using the National Center for Environment Prediction-Climate Forecast System version 2 (NCEP-CFSv2), this study comprehensively evaluates the seasonal and monthly prediction of the Siberian high intensity during the winter time (November to February). Results show that the NCEP-CFSv2 model can skillfully predict the Siberian high intensity only in November, the reasons for which are that the local thermal process, dynamic process, and Siberian snow cover extent mainly affect the Siberian high intensity in November. In terms of the thermal process, the NCEP-CFSv2 can better reproduce the Siberian high intensity in November and its related surface soil temperature, upward long-wave radiation, and other thermal factors in Siberia. In terms of the dynamic process, the NCEP-CFSv2 can better reproduce the Siberian high strength in November, which is associated with the low-level tropospheric divergent circulation and the sinking movement of the upper and middle layers in the Siberian area. The model also reproduces the relationship between the snow cover extent over Siberia and the Siberian high intensity in November. The thermodynamic process of the Siberian high and snow cover extent in the area are predictability sources of the Siberian High intensity in November, and the NCEP-CFSv2 can reasonably reproduce these predictability sources in November.

Refined urban canopy parameters and their impacts on simulation of urbanization-induced climate change

Changes in land cover and urban canopy structure caused by urbanization have important effects on regional climate. In this study, the Weather Research and Forecasting model is used to explore the influences of urbanization on local climate change in Guangzhou, a core city in the rapid urbanization region of the Pearl River Delta of China. Global Land Cover data from 2000 and 2018 are adopted to represent urban expansion, and urban canopy parameters (UCPs) established by a novel method are incorporated to represent changes in urban density. Model results reveal that the updated land cover and refined UCPs describe the surface information more accurately. The 10-m wind speed is reduced by 1–4 m/s and the 2-m air temperature is increased by 2–4 °C in urban areas, which brings the simulation results closer to observations. In terms of surface energy balance, upward longwave radiation is increased by 14.3 W/m2 and the land surface temperature is increased by 0–25 k; hence the net all-wave radiation is decreased by 15.6 W/m2. Meanwhile, the urban boundary layer height is increased by 192.2 m on average, but along with the decreased mean wind speed, the boundary layer ventilation is reduced by 500–3500 m2/s.

Clear-sky land surface upward longwave radiation dataset derived from the ABI onboard the GOES–16 satellite

ABSTRACT Surface upward longwave radiation (SULR) is one of the four components of the surface radiation budget, which is defined as the total surface upward radiative flux in the spectral domain of 4-100 μm. The SULR is an indicator of surface thermal conditions and greatly impacts weather, climate, and phenology. Big Earth data derived from satellite remote sensing have been an important tool for studying earth science. The Advanced Baseline Imager (ABI) onboard the Geostationary Operational Environmental Satellite (GOES-16) has greatly improved temporal and spectral resolution compared to the imager sensor of the previous GOES series and is a good data source for the generation of high spatiotemporal resolution SULR. In this study, based on the hybrid SULR estimation method and an upper hemisphere correction method for the SULR dataset, we developed a regional clear-sky land SULR dataset for GOES-16 with a half-hourly resolution for the period from 1st January 2018 to 30th June 2020. The dataset was validated against surface measurements collected at 65 Ameriflux radiation network sites. Compared with the SULR dataset of the Global LAnd Surface Satellite (GLASS) longwave radiation product that is generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the polar-orbiting Terra and Aqua satellites, the ABI/GOES-16 SULR dataset has commensurate accuracy (an RMSE of 15.9 W/m2 vs 19.02 W/m2 and an MBE of −4.4 W/m2 vs −2.57 W/m2), coarser spatial resolution (2 km at nadir vs 1 km resolution), less spatial coverage (most of the Americas vs global), fewer weather conditions (clear-sky vs all-weather conditions) and a greatly improved temporal resolution (48 vs 4 observations a day). The published data are available at http://www.dx.doi.org/10.11922/sciencedb.j00076.00062.

The impact of atmospheric moisture transport on winter Arctic warming: Radiation versus latent heat release

AbstractAtmospheric moisture transport (AMT) contributes significantly to the recent accelerated Arctic warming. However, the impact of AMT has not been well quantified, not to mention the relative contribution of its impact on microphysical latent heating (LAH) and longwave radiative heating (LWH). A series of Polar‐WRF model experiments with different magnitudes of AMT are conducted to study the response of winter Arctic temperature to AMT variations. Results show that atmospheric precipitable water is very sensitive to AMT variations and thus can define the changes in surface air temperature by altering surface downward longwave radiation. Additionally, because evaporation and sublimation tend to balance the AMT‐induced moisture changes near the surface, LWH in the lower troposphere is determined by downward longwave radiation and thus can be the dominant factor for temperature variations. However, temperature in the mid‐ and upper troposphere is primarily determined by changes in LAH, because the content of ice‐phase cloud aloft is significantly affected by AMT. In addition, the changes in LWH in the mid‐ and upper troposphere are governed by upward longwave radiation, thus offsetting some of the temperature variations. These findings have implications for the attribution of Arctic current warming and the prediction of its future temperature change.

Characteristics of Downward and Upward Longwave Radiation at Athalassa, an Inland Location of the Island of Cyprus

In this study, two years of hourly longwave downward and upward irradiance measurements at Athalassa, an inland location, are used to analyze and compare them. A detailed quality control process was followed according to the suggested tests proposed by the Baseline Surface Radiation Network (BSRN) group. The criteria involved are based on physically possible, extremely rare and climatological limits. Furthermore, comparison tests were also applied between the two longwave components as well as with air and ground surface temperatures. Additionally, time consistency and persistency tests were applied. All the suspect data were excluded from the analysis. The data showed that the frequency distribution of downward longwave irradiances follows a normal distribution function, while the upward longwave follows an almost normal distribution but with a long positive tail. The annual mean daily downward longwave irradiation is 27.3 MJ m−2 and the annual mean daily upward longwave irradiation is 37.8 MJ m−2. The net longwave irradiation is always negative ranging from −5.9 to −12.1 MJ/m2. Various models were tested to estimate daylight and all day downward and upward longwave irradiances under clear-sky and all-sky conditions. For the comparison of measured and estimated values the root-mean-square errors and linear regression correlations have been used. The results of this comparison showed that Idso’s and Brunt’s models perform well, and they can be used to estimate downward longwave irradiance under clear-sky conditions. Furthermore, both models were extended to estimate the daylight downward longwave irradiance under all-sky conditions by taking into account the ratio of global to the clear-sky global solar irradiance. In this case, the RMSE of the local calibrated coefficients scheme of Idso’s model was 30.6 W m−2, while Brunt’s model showed slightly lower value (29.0 W m−2).

Vertical Gradient Variations in Radiation Budget and Heat Fluxes in the Urban Boundary Layer: A Comparison Study Between Polluted and Clean Air Episodes in Beijing During Winter

AbstractPrevious studies have reported air pollution‐radiation interactions in the urban boundary layer (UBL), but vertical gradient variations in the radiation budget and heat flux under air pollution conditions are relatively sparse. In this study, based on gradient observations from the Beijing 325 m meteorological tower in December 2015, the characteristics of near‐surface radiation balance and energy budget at three levels under different pollution conditions were comparatively investigated. Relative to clean days, both downward and upward shortwave radiation (DSR and USR) dropped during daytime, while downward and upward longwave radiation (DLR and ULR) enhanced during nighttime on heavily polluted days, showing that with evaluated height, the drop magnitudes of DSR and USR decreased, while the enhancement magnitude of DLR (ULR) decreased (increased). The combined effects of four radiation components significantly induced the reduction in net radiation (Rn) on polluted days, leading to the near‐surface energy budget change. In addition, the monthly averaged anthropogenic heat flux (Qf) was estimated to quantitatively calculate the heat storage (G) term in the surface energy budget. During daytime, compared to the clean episodes, the sensible heat flux (H) was reduced more than Rn in the whole near‐surface UBL during heavy polluted episodes, resulting in smaller H/(Rn + Qf) and larger G/(Rn + Qf). Finally, we revealed that weak thermal forcing effects caused by insufficient availability of net radiation energy at the surface and weak dynamic motion associated with weak winds were both responsible for the larger reduction (increase) in H (G) during pollution episodes in the whole near‐surface UBL.