Incoming Shortwave Radiation Research Articles

Quantifying Aspect‐Dependent Snowpack Response to High‐Elevation Wildfire in the Southern Rocky Mountains

AbstractIncreasing wildfire frequency and severity in high‐elevation seasonal snow zones presents a considerable water resource management challenge across the western United States (U.S.). Wildfires can affect snowpack accumulation and melt patterns, altering the quantity and timing of runoff. While prior research has shown that wildfire generally increases snow melt rates and advances snow disappearance dates, uncertainties remain regarding variations across complex terrain and the energy balance between burned and unburned areas. Utilizing paired in situ data sources within the 2020 Cameron Peak burn area on the Front Range of Colorado, U.S., during the 2021–2022 winter, we found no significant difference in peak snow water equivalent (SWE) magnitude between burned and unburned areas. However, the burned south aspect reached peak SWE 22 days earlier than burned north. During the ablation period, burned south melt rates were 71% faster than unburned south melt rates, whereas burned north melt rates were 94% faster than unburned north aspects. Snow disappeared 7–11 days earlier in burned areas than unburned areas. Net energy differences at the burned and unburned weather station sites were seasonally variable, the burned area snowpack lost more net energy during the winter, but gained more net energy during the spring. Increased incoming shortwave radiation at the burned site was 6x more impactful in altering the net shortwave radiation balance than the decline in surface albedo. These findings emphasize the need for post‐wildfire water resource planning that accounts for aspect‐dependent differences in energy and mass balance to accurately predict snowpack storage and runoff timing.

SENSITIVITY OF A 1D LAKE MODEL TO THE INPUT METEOROLOGICAL DATA

The paper evaluates how the choice of a source of meteorological data used as boundary conditions and the changes in model calibration parameters affect the adequate performance of a model of lake thermo- and hydrodynamics. The quality of simulation of water temperature dynamics in a small lake by a onedimensional GLM model using data from an automatic meteorological station on the lake shore, a state weather station and two global reanalyses was quantitatively assessed. It is shown that the best modeling result (RMSE of water temperature calculation 0,8-2,0°C, Nash-Sutcliffe efficiency >0,7) can be achieved using data sets that explicitly provide incoming shortwave and longwave radiation fluxes. At the same time, good representation of the bottom water temperature requires correct setting of wind regime, which is only possible if data from instrumental ground-based observations at a stationary weather station are applied. Combining ground-based observations of wind speed, air temperature and humidity with radiation fluxes from global reanalyses makes it possible to achieve a calculation error ≤1°C at all depths.The analysis of model sensitivity to calibration parameters in case when the reanalysis data are applied showed that parameters related to wind mixing, i.e. the scaling factor for wind speed and constants related to the in-model description of wind impact energy, have the greatest influence on the final calculation error. If we change the intensity coefficients of other types of mixing during calibration it does not lead to an obvious trend in the quantitative estimates of modeling quality. It could also be reasonable to introduce correction multipliers to the values of air temperature and solar radiation fluxes, thus neutralizing the effect of unrepresentativeness of the meteorological data applied for a particular lake, as well as to correct the value of solar radiation extinction coefficient relative to the value obtained from the Secchi depth. The results of the study could be used to justify the choice of meteorological data source and to optimize the methods of calibration of lake thermal stratification models

Solar Radiation Triggers the Bimodal Leaf Phenology of Central African Evergreen Broadleaved Forests

AbstractCentral African evergreen broadleaved forests around the equator exhibit a double annual cycle for canopy phenology and carbon uptake seasonality. The underlying drivers of this behavior are poorly understood and the double seasonality is not captured by land surface models (LSM). In this study, we developed a new leaf phenology module into the ORCHIDEE LSM (hereafter ORCHIDEE‐AFP), which utilizes short‐wave incoming radiation (SWd) as the main driver of leaf shedding and partial rejuvenation of the canopy, to simulate the double seasonality of central African forests. The ORCHIDEE‐AFP model has been evaluated by using field data from two forest sites and satellite observations of the enhanced vegetation index (EVI), which is a proxy of young leaf area index (LAIYoung) with leafage less than 6 months, as well as six products of GPP or GPP proxies. Results demonstrate that ORCHIDEE‐AFP successfully reproduces observed leaf turnover (R = 0.45) and young leaf abundance (R = 0.74), and greatly improve the representation of the bimodal leaf phenology. The proportion of grid cells with a significant positive correlation between the seasonality of modeled LAIYoung and observed EVI increased from 0.2% in the standard model to 27% in the new model. For photosynthesis, the proportions of grid cells with significant positive correlations between modeled and observed seasonality range from 26% to 65% across the six GPP evaluation products. The improved performance of the ORCHIDEE‐AFP model in simulating leaf phenology and photosynthesis of central African forests will allow a more accurate assessment of the impacts of climate change in tropical forests.

Response of sea surface temperature to atmospheric rivers

Atmospheric rivers (ARs), responsible for extreme weather conditions, are mid-latitude systems that can cause significant damage to coastal areas. While forecasting ARs beyond two weeks remains a challenge, past research suggests potential benefits may come from properly accounting for the changes in sea surface temperature (SST) through air–sea interactions. In this paper, we investigate the impact of ARs on SST over the North Pacific by analyzing 25 years of ocean reanalysis data using an SST budget equation. We show that in the region of strong ocean modification, ocean dynamics can offset over 100% of the anomalous SST warming that would otherwise arise from atmospheric forcing. Among all ocean processes, ageostrophic advection and vertical mixing (diffusion and entrainment) are the most important factors in modifying the SST tendency response. The SST tendency response to ARs varies spatially. For example, in coastal California, the driver of enhanced SST warming is the reduction in ageostrophic advection due to anomalous southerly winds. Moreover, there is a large region where the SST shows a warming response to ARs due to the overall reduction in the total clouds and subsequent increase in total incoming shortwave radiation.

Drivers of the Extreme Early Spring Glacier Melt of 2022 on the Central Tibetan Plateau

AbstractExtreme glacier melt has important implications for climate change studies and glacier‐related hazards. Few attempts have been made to study the characteristics and mechanisms of extreme melt on the Tibetan Plateau (TP) and surroundings, one of the largest concentrations of glaciers beyond the polar regions. To address this gap, we investigated the magnitude and possible drivers of anomalous early spring glacier melt in 2022 on the central TP using multi‐source observations (October 2020–July 2022) of Kuoqionggangri and Sangqu glaciers and an energy and mass balance model. Our results show that anomalous melt of both glaciers occurred in early spring (18 March–10 April 2022), when glaciers are traditionally expected to be frozen. There were 89 cumulative hours with air temperatures above 0°C, with a positive cumulative air temperature of 121.80°C hour at 5,700 m on Kuoqionggangri Glacier. The glacier‐wide cumulative melts on Kuoqionggangri and Sangqu glaciers from 18 March to 10 April 2022 were 22 ± 14.2 and 48 ± 37.5 mm w.e., respectively. Such anomalous glacier melt was driven by high incoming shortwave radiation and sensible heat flux, which were influenced by low cloud fraction and precipitation, and high air temperature during early spring. The weakening and northward‐shift of the westerlies, coupled with descending air motions over the central TP, reduced cloud fraction and hindered the transport of cold, moist air to the central TP. These changes occurred both in the central TP and the Himalaya, indicating the influence of macroscale atmospheric circulation patterns on this extreme glacier melt.

On the Importance of Regime-Specific Evaluations for Numerical Weather Prediction Models as Demonstrated Using the High-Resolution Rapid Refresh (HRRR) Model

Abstract The scientific literature has many studies evaluating numerical weather prediction (NWP) models. However, many of those studies averaged across a myriad of different atmospheric conditions and surface forcings that can obfuscate the atmospheric conditions when NWP models perform well versus when they perform inadequately. To help isolate these different weather conditions, we used observations from the U.S. Climate Reference Network (USCRN) obtained between 1 January and 31 December 2021 to distinguish among different near-surface atmospheric conditions [i.e., different near-surface heating rates (), incoming shortwave radiation (SWd) regimes, and 5-cm soil moisture (SM05)] to evaluate the High-Resolution Rapid Refresh (HRRR) Model, which is a 3-km model used for operational weather forecasting in the United States. On days with small (large) , we found afternoon T biases of about 2°C (−1°C) and afternoon SWd biases of up to 170 W m−2 (100 W m−2), but negligible impacts on SM05 biases. On days with small (large) SWd, we found daytime temperature biases of about 3°C (−2.5°C) and daytime SWd biases of up to 190 W m−2 (80 W m−2). Whereas different SM05 had little impact on T and SWd biases, dry (wet) conditions had positive (negative) SM05 biases. We argue that the proper evaluation of weather forecasting models requires careful consideration of different near-surface atmospheric conditions and is critical to better identify model deficiencies in order to support improvements to the parameterization schemes used therein. A similar, regime-specific verification approach may also be used to help evaluate other geophysical models. Significance Statement Improving weather forecasting models requires careful evaluations against high-quality observations. We used observations from the U.S. Climate Reference Network (USCRN) and found that the performance of the High-Resolution Rapid Refresh (HRRR) Model varies as a function of differences in near-surface heating and solar radiation. This finding indicates that model evaluations need to be conducted under varying near-surface weather conditions rather than averaging across multiple weather types. This new approach will allow for model developers to better identify model deficiencies and is a useful step to helping improve weather forecasts.

Modeling net ecosystem exchange of CO2 with gated recurrent unit neural networks

The complex forcing mechanisms of biophysical drivers on ecosystem productivity, as well as some unknown relationships, stipulates the application of artificial intelligence techniques in modeling the ecosystem carbon cycle. In particular, various deep learning algorithms have been successfully applied to comprehend temporal relationships, though some issues regarding capturing temporal features for modeling CO2 fluxes across time scales remain unsolved. In this study, a gated recurrent unit (GRU) model was trained for simulating half-hourly net ecosystem exchange of CO2 (NEE) using 12-year continuous flux data (2009–2020) from seven experimental bioenergy crops in southwest Michigan, USA. The fields were historically managed either as corn-soybean rotation agricultural (AGR) or Conservation Reserve Program (CRP) lands and planted to no-till corn (AGR-C and CRP-C), restored-prairie (AGR-Pr and CPR-Pr), switchgrass (AGR-Sw and CRP-Sw) and smooth brome grass (CRP-Ref). We compared NEE simulations for the entire year, growing season, and non-growing season datasets, and analyzed relative importance of biophysical variables on variations of NEE. GRU performed well in simulating NEE at single site, with R2 of 0.89–0.93, 0.85–0.90, and 0.61–0.85 for the annual, growing season, and non-growing season datasets, respectively, which provided comparable accuracy and 6 % of run-time shorter than those of long short-term memory. R2 reached 0.70 and 0.80 across all sites and unique land-cover types. Radiation parameters contributed most to the variability of NEE. Contributions of individual variables appear more complex during the non-growing season and include incoming shortwave radiation, day of year, temperature, Monin-Obukhov stability, wind direction, and soil water content. The six most important forcing variables are consistent with our current understanding, although their ranked importance varied by ecosystem type and modeling scale. These results bring renewed insights in modeling observations at seasonal scales and provide guidance for variable selection to scale up measurements from one site to multiple land-cover types across the landscape.

Response of alpine ground temperatures to a rising atmospheric 0 °C isotherm in the period 1955–2021

Ground temperatures in alpine terrain vary considerably over short distances, particularly due to differences in elevation and incoming short-wave radiation but also snow and surface conditions. To allow for direct cross-site, interregional, and cross-disciplinary comparisons, we introduce a parameter called the potential 0 °C isotherm (PZDI) in the ground. This parameter represents an aspect- and elevation independent geo-projection of ground temperatures. It was calculated for several ground temperature datasets from the (sub-)permafrost zone in the European Alps. We analyse the reaction of the PZDI at different depths to long-term changes in atmospheric temperature, represented by the atmospheric 0 °C isotherm (AZDI). The close correspondence of PZDI and AZDI mainly provided two new insights: Based on 15 boreholes, the PZDI/AZDI interaction allowed a depth-dependent analysis of the magnitude and temporal evolution of the disequilibrium between atmosphere and ground and the potential heat transfer processes involved. Moreover, it allowed a reconstruction of the development of ground temperatures in the European Alps during the second half of the 20th century, adding 50 years to the longest existing time series measured in ice-poor permafrost. This extension into the past reveals a major warming at the end of the 1980s, which occurred before the start of the available permafrost temperature observations. In the 1955–2021 period, the 5-year running mean of the AZDI rose by 400 m, while the PZDI at 15 m depth rose by about 300 m. Projecting this warming into a permafrost distribution map shows a decline in shallow, ice-poor permafrost area by roughly 60 % since the 1980s. We expect the PZDI to follow the AZDI and to increase by another 100 m in the coming decade and up to at least 14 m depth. This would increase the area with loss of shallow permafrost to approximately 80 % since the 1980s.

Combined Passive Heating Systems in Mediterranean, Low-Cost, Greenhouse Cucumber Crops

Greenhouse microclimate and crop response of winter cucumber cycles grown in unheated Mediterranean greenhouses with representative combinations of passive heating systems (fixed, plastic screen with and without black mulch; movable thermal screen with black mulch; and double-layer plastic covering with black mulch) were evaluated in Almería, SE Spain. In the first experiment, the black mulch in combination with a movable or fixed screen increased the marketable cucumber yield by 14%, which appears to be mostly attributable to higher substrate temperatures induced by the black mulch in the cold period. Moreover, the black mulch in combination with a fixed screen frequently led to screen water condensation. The use of a movable screen, rather than a fixed one, in combination with a black mulch increased the first-class cucumber yield in the second experiment and reduced the non-marketable one in the first experiment. This might be mainly attributable to the higher incoming shortwave radiation in the cold period. Moreover, the movable screen reduced the risk of water condensation on the screen and the crop. The cucumber in the greenhouse with the double-layer covering and black mulch, compared to that with movable screen and black mulch, received lower daily incoming shortwave radiation, particularly, during the second half of the cycle (mainly due to the formation of water condensation droplets on the lower surface of the external plastic film), which reduced crop yield. Further field research is needed to better quantify the most limiting factor for growth (substrate/soil or air temperature, radiation, or water condensation) in Mediterranean greenhouse crops.

Even cooler insights: On the power of forests to (water the Earth and) cool the planet.

Scientific innovation is overturning conventional paradigms of forest, water, and energy cycle interactions. This has implications for our understanding of the principal causal pathways by which tree, forest, and vegetation cover (TFVC) influence local and global warming/cooling. Many identify surface albedo and carbon sequestration as the principal causal pathways by which TFVC affects global warming/cooling. Moving toward the outer latitudes, in particular, where snow cover is more important, surface albedo effects are perceived to overpower carbon sequestration. By raising surface albedo, deforestation is thus predicted to lead to surface cooling, while increasing forest cover is assumed to result in warming. Observational data, however, generally support the opposite conclusion, suggesting surface albedo is poorly understood. Most accept that surface temperatures are influenced by the interplay of surface albedo, incoming shortwave (SW) radiation, and the partitioning of the remaining, post-albedo, SW radiation into latent and sensible heat. However, the extent to which the avoidance of sensible heat formation is first and foremost mediated by the presence (absence) of water and TFVC is not well understood. TFVC both mediates the availability of water on the land surface and drives the potential for latent heat production (evapotranspiration, ET). While latent heat is more directly linked to local than global cooling/warming, it is driven by photosynthesis and carbon sequestration and powers additional cloud formation and top-of-cloud reflectivity, both of which drive global cooling. TFVC loss reduces water storage, precipitation recycling, and downwind rainfall potential, thus driving the reduction of both ET (latent heat) and cloud formation. By reducing latent heat, cloud formation, and precipitation, deforestation thus powers warming (sensible heat formation), which further diminishes TFVC growth (carbon sequestration). Large-scale tree and forest restoration could, therefore, contribute significantly to both global and surface temperature cooling through the principal causal pathways of carbon sequestration and cloud formation.

High-resolution (1 km) all-sky net radiation over Europe enabled by the merging of land surface temperature retrievals from geostationary and polar-orbiting satellites

Abstract. Surface net radiation (SNR) is a vital input for many land surface and hydrological models. However, most of the current remote sensing datasets of SNR come mostly at coarse resolutions or have large gaps due to cloud cover that hinder their use as input in models. Here, we present a downscaled and continuous daily SNR product across Europe for 2018–2019. Long-wave outgoing radiation is computed from a merged land surface temperature (LST) product in combination with Meteosat Second Generation emissivity data. The merged LST product is based on all-sky LST retrievals from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard the geostationary Meteosat Second Generation (MSG) satellite and clear-sky LST retrievals from the Sea and Land Surface Temperature Radiometer (SLSTR) onboard the polar-orbiting Sentinel-3A satellite. This approach makes use of the medium spatial (approx. 5–7 km) but high temporal (30 min) resolution, gap-free data from MSG along with the low temporal (2–3 d) but high spatial (1 km) resolution of the Sentinel-3 LST retrievals. The resulting 1 km and daily LST dataset is based on an hourly merging of both datasets through bias correction and Kalman filter assimilation. Short-wave outgoing radiation is computed from the incoming short-wave radiation from MSG and the downscaled albedo using 1 km PROBA-V data. MSG incoming short-wave and long-wave radiation and the outgoing radiation components at 1 km spatial resolution are used together to compute the final daily SNR dataset in a consistent manner. Validation results indicate an improvement of the mean squared error by ca. 7 % with an increase in spatial detail compared to the original MSG product. The resulting pan-European SNR dataset, as well as the merged LST product, can be used for hydrological modelling and as input to models dedicated to estimating evaporation and surface turbulent heat fluxes and will be regularly updated in the future. The datasets can be downloaded from https://doi.org/10.5281/zenodo.8332222 (Rains, 2023a) and https://doi.org/10.5281/zenodo.8332128 (Rains, 2023b).

WRF (v4.0)–SUEWS (v2018c) coupled system: development, evaluation and application

Abstract. The process of coupling the Surface Urban Energy and Water Scheme (SUEWS) into the Weather Research and Forecasting (WRF) model is presented, including pre-processing of model parameters to represent spatial variability in surface characteristics. Fluxes and mixed-layer height observations in the southern UK are used to evaluate a 2-week period in each season. Mean absolute errors, based on all periods, are smaller in residential Swindon than central London for turbulent sensible and latent heat fluxes (QH, QE) with greater skill on clear-sky days on both sites (for incoming and outgoing short- and long-wave radiation, QH and QE). Clear-sky seasonality is seen in the model performance: there is better absolute skill for QH and QE in autumn and winter, when there is a higher frequency of clear-sky days, than in spring and summer. As the WRF-modelled incoming short-wave radiation has large errors, we apply a bulk transmissivity derived from local observations to reduce the incoming short-wave radiation input to the land surface scheme – this could correspond to increased presence of aerosols in cities. We use the coupled WRF–SUEWS system to investigate impacts of the anthropogenic heat flux emissions on boundary layer dynamics by comparing areas with contrasting human activities (central–commercial and residential areas) in Greater London – larger anthropogenic heat emissions not only elevate the mixed-layer heights but also lead to a warmer and drier near-surface atmosphere.

Evaluation of reanalysis data and dynamical downscaling for surface energy balance modeling at mountain glaciers in western Canada

Abstract. Regional-scale surface energy balance (SEB) models of glacier melt require forcing by coarse-gridded data from reanalysis or global climate models that need to be downscaled to glacier scale. As on-glacier meteorological observations are rare, it generally remains unknown how exact the reanalysis and downscaled data are for local-scale SEB modeling. We address this question by evaluating the performance of reanalysis from the European Centre for Medium-Range Weather Forecasts (ERA5 and ERA5-Land reanalysis), with and without downscaling, at four glaciers in western Canada with available on-glacier meteorological measurements collected over different summer seasons. We dynamically downscale ERA5 with the Weather Research and Forecasting (WRF) model at 3.3 and 1.1 km grid spacing. We find that our SEB model, forced separately with the observations and the two reanalyses, yields less than 10 % difference in simulated total melt energy and shows strong correlations (0.86) in simulated time series of daily melt energy at each site. The good performance of the reanalysis-derived melt energy is partly due to cancellation of biases between overestimated incoming shortwave radiation and substantially underestimated wind speed and subsequently turbulent heat fluxes. Downscaling with WRF improves the simulation of wind speed, while other meteorological variables show similar performance to ERA5 without downscaling. The choice of WRF physics parameterization schemes is shown to have a relatively large impact on the simulations of SEB components but a smaller impact on the modeled total melt energy. The results increase our confidence in dynamical downscaling with WRF for long-term glacier melt modeling in this region.

Transpiration Dynamics in Co-Located Maize, Sorghum, and Soybean Closed Canopies and Their Environmental Controls

Highlights Hourly sap flow measured in co-located and identically managed maize, sorghum, and soybean closed canopies. PAR, VPD, and ETr were strongly correlated to transpiration (T) normalized by LAI. Negative response of T to high VPD (3-4 kPa) was observed for maize and sorghum. Counterclockwise hysteresis observed for diurnal T-VPD and T-PAR. MLR models were developed to estimate T using VPD and PAR. Abstract. Transpiration (T) dominates terrestrial hydrological fluxes and is strongly coupled with vegetation productivity and water use efficiency across different biomes, including agricultural systems. Studying how T in field crops responds to environmental variability has important implications to inform and predict agroecosystems’ response to a changing environment. However, comparative T rates among major field crops remain unknown in many regions where drought severity and limited freshwater availability are projected, such as the Central U.S. Plains. We address this knowledge gap by monitoring and characterizing hourly T for field-grown maize, grain sorghum, and soybean crops under the same weather, soil, and management regimes using sap flow sensors. The relationships among crop-specific T and air temperature (Tair), relative humidity (RH), wind speed (u2), vapor pressure deficit (VPD), incoming shortwave radiation (Rs), photosynthetically active radiation (PAR), net radiation (Rn), and grass- and alfalfa-reference evapotranspiration (ETo, ETr) were investigated. T normalized by leaf area index (T LAI-1) was most correlated with PAR (r=0.88), ETr (r=0.84), and VPD (r=0.81). Mean sensitivity of T LAI-1 to unit change in Tair, Rs, PAR, Rn, u2, RH, VPD, and ETr for maize and sorghum was 88% and 59% greater than that of soybean, respectively. All crops showed non-linear T LAI-1 response to increasing VPD, and a negative response of T LAI-1 to VPD was observed in the 3.0-4.0 kPa VPD range for maize and sorghum. Each crop demonstrated a counterclockwise hysteresis effect to diurnal T-VPD and T-PAR, which was 177% and 87% greater (for T-VPD) and 44% and 17% greater (for T-PAR) in maize and sorghum, respectively, than soybean. Transpiration has rarely been measured in row crops, especially in a comparative fashion, and thus, the concurrent T dynamics and their environmental controls characterized in this research are of critical importance. These data can be instrumental for quantitatively assessing change in true crop water use (transpiration) and thus crop suitability under projected environmental change. Keywords: Hysteresis, Photosynthetically active radiation, Reference evapotranspiration, Sapflow, Vapor pressure deficit.

A comparative study of the land–atmosphere energy and water exchanges over the Tibetan Plateau and the Yangtze River Region

A comprehensive understanding of energy and water cycle characteristics in different regions is crucial for studying local land–atmosphere interactions and predicting regional weather and climate change. To explore similarities and differences in land–atmosphere energy and water exchanges between two regions—the Tibetan Plateau (TP), characterized by higher elevation and a drier climate, and the Yangtze River Region (YRR), with lower elevation and a wetter climate—this study analyzed and compared the radiation components and the turbulent heat fluxes at eight sites covering various land-cover types, including alpine desert and alpine grassland on the TP, as well as urban and grassland on the YRR. The following results were obtained: (1) Over the TP, the annual mean incoming and outgoing shortwave radiation are 251.3 and 59.6 W m−2, which are 1.70 and 2.87 times the values in the YRR, respectively. The incoming and outgoing longwave radiation are 231.5 and 338.0 W m−2, which are 0.64 and 0.83 times those in the YRR, respectively. However, the difference in net radiation is relatively small. (2) In grassland over both the TP and YRR, the latent heat fluxes have higher values of 35.0 and 38.8 W m−2, respectively, leading to a higher heating efficiency. Alpine desert has the highest sensible heat flux (SH) value of 42.1 W m−2, due to sparse vegetation and lower soil moisture, followed closely by urban land cover with an average SH value of 38.2 W m−2. These results highlight the different characteristics of land–atmosphere interaction across different land covers in different climatic contexts, laying the groundwork for future investigations of additional land–atmosphere coupling processes.摘要正确认识不同区域能量和水分循环特征是研究局地地气相互作用及准确预测区域天气, 气候变化的关键. 为了研究属于干旱/半干旱气候的青藏高原 (TP) 和湿润/半湿润气候的长江流域 (YRR) 之间地表能量和水分交换的异同, 本文对比分析了两个区域8个不同地表类型 (包括高山荒漠, 高山草地, (平原) 城市和 (平原) 草地等) 观测站点的地表辐射和能量通量数据. 结果显示: (1) TP由于高原大气层稀薄且空气洁净, 年平均入射短波辐射为251.3 W m−2, 是YRR的1.7倍. 加之高原地表反照率高导致反射辐射 (59.6 W m−2) 是YRR的2.87倍. 入射及出射的长波辐射为231.5和338.0 W m−2, 分别为YRR的0.64和0.83. 而两个区域的净辐射差异不大; (2) 草地站更多的潜热释放使得地表总加热效率高于城市和高山荒漠, TP和YRR的草地站的年平均潜热分别为35.0 和 38.8 W m−2, 而植被稀疏且土壤干燥的高山荒漠地区感热最大, 年平均感热为42.1 W m−2; 其次是城市下垫面, 其年平均感热为37.7 W m−2. 研究结果揭示了不同气候背景下典型下垫面地气相互作用特征, 为地气相互作用过程深入分析奠定了基础.

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.

Projections of central Arctic summer sea surface temperatures in CMIP6

One of the most dramatic climate responses to future global warming is the near-disappearance of the perennial sea ice cover in the central Arctic Ocean, a phenomenon known as the ice-free summer Arctic. The immediate consequence of an ice-free Arctic would be the surface warming of the central Arctic Ocean, where sea surface temperatures (SSTs) used to be at freezing levels. Through an analysis of climate models participating in the climate model intercomparison project phase-6, this study demonstrates a wide range of responses in the central Arctic SSTs in August–September as a result of the projected ice-free summer Arctic. These responses vary from 0.7 to 8 °C in the shared socioeconomic pathway 2 (SSP2-4.5), referred to as the ‘middle of the road’ scenario, in which socioeconomic and technological trends do not significantly deviate from historical patterns. The extent of the central Arctic sea surface warming in August–September is found to have a loose correlation with the September sea ice extent (SIE), but a stronger connection to the SIE during spring to early summer (May–July), when incoming shortwave radiation is most intense. In certain climate models, the perennial sea ice cover disappears completely in September, causing central Arctic SSTs to rise by 5 °C–8 °C by the end of the 21st century. This leads to a bimodal distribution of annual SSTs. Further analysis reveals a close relationship between mid-summer SSTs in the central Arctic Ocean and preceding winter sea ice thickness (SIT). This underscores the significance of winter SIT in predicting future Arctic surface warming and marine heatwaves.

Significant changes in cloud radiative effects over Southwestern United States during the COVID-19 flight reduction period

Aircraft-induced clouds (AICs) are one of the most visible anthropogenic atmospheric phenomena, which mimic the natural cirrus clouds and perturb global radiation budget by reducing incoming shortwave (SW) radiation and trapping outgoing longwave (LW) radiation. The COVID-19 pandemic has caused a 70 % global decline in flight numbers from mid-March to October 2020, which provided a unique opportunity to examine the climatic impact of AICs. Among various regions, Western Europe and the Contiguous United States experienced the most substantial reduction in air traffic during the COVID-19 pandemic. Interestingly, only the Southwestern United States demonstrated a significant decrease in cirrus clouds, leading to notable changes in shortwave (SW) and longwave (LW) cloud radiative effects. Such changes were likely due to the reduction in AICs. However, further investigations indicated that this region also experienced abnormal high pressure and low relative humidity in the middle and upper atmosphere, resulting in unusual subsidence and dryness that prohibit the formation and maintenance of cirrus cloud. While it remains challenging to quantify the exact climatic impact of reduced AICs, the remarkable anomalies documented in this study provide valuable observational benchmark for future modelling studies of the climatic impact AICs.

Climatological assessment of the vertically resolved optical and microphysical aerosol properties by lidar measurements, sun photometer, and in situ observations over 17 years at Universitat Politècnica de Catalunya (UPC) Barcelona

Abstract. Aerosols are one of the most important pollutants in the atmosphere and have been monitored for the past few decades by remote sensing and in situ observation platforms to assess the effectiveness of government-managed reduction emission policies and assess their impact on the radiative budget of the Earth's atmosphere. In fact, aerosols can directly modulate incoming short-wave solar radiation and outgoing long-wave radiation and indirectly influence cloud formation, lifetime, and precipitation. In this study, we quantitatively evaluated long-term temporal trends and seasonal variability from a climatological point of view of the optical and microphysical properties of atmospheric particulate matter at the Universitat Politècnica de Catalunya (UPC), Barcelona, Spain, over the past 17 years, through a synergy of lidar, sun photometer, and in situ concentration measurements. Interannual temporal changes in aerosol optical and microphysical properties are evaluated through the seasonal Mann–Kendall test. Long-term trends in the optical depth of the recovered aerosol; the Ångström exponent (AE); and the concentrations of PM10, PM2.5, and PM1 reveal that emission reduction policies implemented in the past decades were effective in improving air quality, with consistent drops in PM concentrations and optical depth of aerosols. The seasonal analysis of the 17-year average vertically resolved aerosol profiles obtained from lidar observations shows that during summer the aerosol layer can be found up to an altitude of 5 km, after a sharp decay in the first kilometer. In contrast, during the other seasons, the backscatter profiles fit a pronounced exponential decay well with a well-defined scale height. Long-range transport, especially dust outbreaks from the Sahara, is likely to occur throughout the year. During winter, the dust aerosol layers are floating above the boundary layer, while during the other seasons they can penetrate the layer. The analysis also revealed that intense, short-duration pollution events during winter, associated with dust outbreaks, have become more frequent and intense since 2016. This study sheds some light on the meteorological processes and conditions that can lead to the formation of haze and helps decision makers adopt mitigation strategies to preserve large metropolitan areas in the Mediterranean basin.

Evaluation of summer mean radiant temperature simulation in ENVI-met in a hot Mediterranean climate

ENVI-met is currently one of the most popular simulation tools of urban microclimates, used by researchers and designers alike. Yet, in recent years some concerns have been raised regarding the software's capability to accurately simulate the effects of solar irradiance on increased heat stress, especially in hot weather conditions. These concerns have eventually led to the implementation of a new radiation scheme in version 5 of the software. This study set out to evaluate whether this new scheme increased the software's accuracy in evaluating incoming shortwave and longwave radiation fluxes, expressed as Mean Radiant Temperature (MRT), by comparing monitored and simulated summertime values at 60 locations.Our results show that while ENVI-met's new version improved MRT simulation accuracy, the software systematically underestimated the magnitude of MRT in both shaded and unshaded summer conditions. Our MRT evaluation resulted in an RMSE of 6.08 °C in the shade and 13.32 °C at locations fully exposed to solar radiation, which may result in inaccurate and less severe appreciation of outdoor heat stress, especially when outdoor shade is missing. Based on our analysis, we suggest that the origin of error may stem from inaccurate representation of longwave radiation fluxes emitted by ground surfaces.