Incoming Shortwave Radiation Research Articles

Testing the suitability of Marginal Distribution Sampling as a gap‐filling method using some meteorological data from seven sites in West Africa

AbstractMeteorological data are useful in many fields related to climate change studies and their use often requires them to be continuous. To date, marginal distribution sampling (MDS), which consists of filling a missing value with an average of the data that are found in similar meteorological conditions over a flexible time window, is widely adopted in the FLUXNET community. In this work, we evaluate the performance of MDS at diurnal and monthly scales for the incoming shortwave radiation (Swin), relative humidity (RH), vapour pressure deficit (VPD), air and soil temperatures (Tair, Tsoil) acquired across seven sites in West Africa. The criteria tested are the MDS's ability to (i) fill gaps while reducing the error rate, (ii) represent proper variability within data and finally (iii) ensure homogeneity between its output and original data. We found during the daytime that MDS is adequate for filling gaps in Swin when both reducing error rate and a good representation of variability are targeted. If the goal is to have a small error rate, then this approach is recommended for all investigated variables except VPD. During nighttime, MDS is satisfactory to minimize the error when filling gaps in Tair, Tsoil and RH while to represent their variabilities it becomes more sensitive to the rate of missing data. At a monthly scale, the gap‐filled data are consistent with the original ones for all variables attributable to data size and a wider sliding window that allows more data under similar conditions to be considered.

Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach

Abstract. Long-range weather forecasts provide predictions of atmospheric, ocean and land surface conditions that can potentially be used in land surface and hydrological models to predict the water and energy status of the land surface or in crop growth models to predict yield for water resources or agricultural planning. However, the coarse spatial and temporal resolutions of available forecast products have hindered their widespread use in such modelling applications, which usually require high-resolution input data. In this study, we applied sub-seasonal (up to 4 months) and seasonal (7 months) weather forecasts from the latest European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system (SEAS5) in a land surface modelling approach using the Community Land Model version 5.0 (CLM5). Simulations were conducted for 2017–2020 forced with sub-seasonal and seasonal weather forecasts over two different domains with contrasting climate and cropping conditions: the German state of North Rhine-Westphalia (DE-NRW) and the Australian state of Victoria (AUS-VIC). We found that, after pre-processing of the forecast products (i.e. temporal downscaling of precipitation and incoming short-wave radiation), the simulations forced with seasonal and sub-seasonal forecasts were able to provide a model output that was very close to the reference simulation results forced by reanalysis data (the mean annual crop yield showed maximum differences of 0.28 and 0.36 t ha−1 for AUS-VIC and DE-NRW respectively). Differences between seasonal and sub-seasonal experiments were insignificant. The forecast experiments were able to satisfactorily capture recorded inter-annual variations of crop yield. In addition, they also reproduced the generally higher inter-annual differences in crop yield across the AUS-VIC domain (approximately 50 % inter-annual differences in recorded yields and up to 17 % inter-annual differences in simulated yields) compared to the DE-NRW domain (approximately 15 % inter-annual differences in recorded yields and up to 5 % in simulated yields). The high- and low-yield seasons (2020 and 2018) among the 4 simulated years were clearly reproduced in the forecast simulation results. Furthermore, sub-seasonal and seasonal simulations reflected the early harvest in the drought year of 2018 in the DE-NRW domain. However, simulated inter-annual yield variability was lower in all simulations compared to the official statistics. While general soil moisture trends, such as the European drought in 2018, were captured by the seasonal experiments, we found systematic overestimations and underestimations in both the forecast and reference simulations compared to the Soil Moisture Active Passive Level-3 soil moisture product (SMAP L3) and the Soil Moisture Climate Change Initiative Combined dataset from the European Space Agency (ESA CCI). These observed biases of soil moisture and the low inter-annual differences in simulated crop yield indicate the need to improve the representation of these variables in CLM5 to increase the model sensitivity to drought stress and other crop stressors.

Snow cover duration in northern Finland and the influence of key variables through a conceptual framework based on observed variations in snow depth

Seasonal snow cover duration is the net result from many processes acting on snow fallen on the Earth's surface. Several of these processes feed back into the atmosphere-cryosphere system causing non-linear interactions. The timing of snow retreat is of essential importance, but the duration of snow cover has large spatiotemporal variabilities. However, from a large data set of observed snow depth changes in northern Finland, systematic similar evolutions are identified that allow for a considerable simplification and reduction of the complexity in snow depth changes. Here, a novel conceptual framework is designed based on dividing the season into two main periods (dark and bright period, based on solar irradiance), for which snow depth decrease is parameterized based on three variables, average temperature, incoming shortwave radiation, and light-absorbing particles (LAP) in the snow. The processes are simplified into two linear relations, and a new formulation for concentration enhancement of LAP, which is dependent on snow depth decrease, is given. The results show that the seasonal snow cover duration is shifted by about one day for every 10 mm snow water equivalent of precipitation. This effect is comparable in scale to that of doubling of the amount of LAP concentration in snow. We also found that the combined shift in snow cover duration from interannual variability in ambient temperature and shortwave radiation (warm and bright vs. cold and dark season) is large enough to explain the variability of a couple of weeks for a given precipitation amount in Northern Finland.

Mapping Prediction of Surface Solar Radiation with Linear Regression Models: Case Study over Reunion Island

This paper presents a novel mapping prediction method for surface solar radiation with linear regression models. The dataset for surface solar radiation prediction is the daily surface incoming shortwave radiation (SIS) product from CM SAF SARAH-E. The spatial resolution is 0.05° × 0.05° and the temporal coverage is from 2007 to 2016. The first five years (2007–2011) are used as training data, and the remaining five years (2012–2016) are used as test data in the prediction model. Datasets were detrended, de-seasonalized, and normalized before being applied to multiple linear regression (MLR), principal component regression (PCR), stepwise regression (SR), and partial least squares regression (PLSR), which are used to perform prediction mapping. The statistical analysis using MAE, MSE, and RMSE shows that the PCR model had the smallest MAE, MSE, and RMSE as compared to the other three models. The PCR model seems better for SSR mapping prediction over Reunion Island. Although the PCR model provides better prediction results, its MAE, MSE, and RMSE are quite large.

Shortwave absorption by wildfire smoke dominated by dark brown carbon

Wildfires emit large amounts of black carbon and light-absorbing organic carbon, known as brown carbon, into the atmosphere. These particles perturb Earth’s radiation budget through absorption of incoming shortwave radiation. It is generally thought that brown carbon loses its absorptivity after emission in the atmosphere due to sunlight-driven photochemical bleaching. Consequently, the atmospheric warming effect exerted by brown carbon remains highly variable and poorly represented in climate models compared with that of the relatively nonreactive black carbon. Given that wildfires are predicted to increase globally in the coming decades, it is increasingly important to quantify these radiative impacts. Here we present measurements of ensemble-scale and particle-scale shortwave absorption in smoke plumes from wildfires in the western United States. We find that a type of dark brown carbon contributes three-quarters of the short visible light absorption and half of the long visible light absorption. This strongly absorbing organic aerosol species is water insoluble, resists daytime photobleaching and increases in absorptivity with night-time atmospheric processing. Our findings suggest that parameterizations of brown carbon in climate models need to be revised to improve the estimation of smoke aerosol radiative forcing and associated warming.

Carbon flux in supraglacial debris over two ablation seasons at Miage Glacier, Mont Blanc massif, European Alps

The cryosphere plays an important role in the global carbon cycle, but few studies have examined carbon fluxes specifically on debris-covered glaciers. To improve understanding of the magnitude and variability of the atmospheric carbon flux in supraglacial debris, and its environmental controls, near-surface CO2 fluxes and meteorological variables were monitored over thick (0.23 m) and thin (0.04 m) debris at Miage Glacier, European Alps, over two ablation seasons, using an eddy covariance system. The CO2 flux alternates between downward and upward orientation in the day and night, respectively, and is dominated by uptake of CO2 in thick debris (mean flux = 1.58 g CO2 m−2 d−1), whereas flux magnitude is smaller and near net zero on thin debris (mean flux = −0.06 g CO2 m−2 d−1). These values infer a potential drawdown of >150 t CO2 km−2 over an ablation season, and >500 t CO2 (0.5 Gg CO2) for the whole debris-covered zone. The strong correlation of daytime CO2 flux magnitude with debris surface temperature suggests that atmospheric CO2 is consumed in hydrolysis and carbonation reactions at sediment-water interfaces in debris. Incoming shortwave radiation is key in heating debris, generating dilute meltwater, and providing energy for chemical reactions. CO2 drawdown on thin debris increases by an order of magnitude on days following frost events, implying that frost shattering generates fresh reactive sediment, which is rapidly chemically weathered with the onset of ice melting. Net CO2 release in the night, and in the daytime when debris surface temperature is below 7°C, is likely due to respiration by debris microorganisms. The combination of dilute meltwater, high temperature, and reactive mineral surfaces open to the atmosphere, makes supraglacial debris an ideal environment for rock chemical weathering. Debris-covered glaciers could be important to local and regional carbon cycling, and measurement of CO2 fluxes and controlling processes at other sites is warranted.

Attribution analysis of water use efficiency in tropical rubber plantations during drought-monsoon season transition

Understanding the water use efficiency (WUE) of rubber plantations to seasonal fluctuations is critical for understanding the water, energy, and carbon cycle in tropical regions. In this study, we examine the exchange of water and heat fluxes between land and atmosphere in rubber plantation ecosystems during monsoon and drought seasons, employing data collected from eddy covariance towers. Further attribution analysis demonstrates that drought-induced alterations in the water use efficiency are predominantly governed by changes in surface resistance (positive contribution). The contributions of incoming shortwave radiation are virtually counteracted by air temperature and longwave radiation. It is noteworthy that the light use efficiency presents the most conspicuous negative contribution; however, this effect is predominantly counterbalanced by vapor pressure deficit (VPD) and aerodynamic resistance. The elevated water use efficiency (WUE) observed in rubber plantation ecosystems during the drought season raises concerns regarding the potential implications of anthropogenic forests on food and water security in tropical regions.

АСПЕКТИ ПРОГНОЗУВАННЯ ТЕМПЕРАТУРНИХ РЕЖИМІВ АСФАЛЬТОБЕТОННОГО ПОКРИТТЯ В ЦІЛЯХ ПРОЄКТУВАННЯ НЕЖОРСТКОГО ДОРОЖНЬОГО ОДЯГУ

Introduction. The introduction to the paper describes the impact of critical temperatures and temperature loadings on the performance of the asphalt pavement layer and also on the entire flexible road pavement construction. Problem statement. The issues of the paper concern significant aspects of the pavement temperature regimes prediction used in various systems of the flexible road pavement designing. Purpose. The main goal of the paper is to review and compare the flexible road pavement designing approaches based on predicted temperatures of the asphalt pavement layer which may be reached under critical road pavement operating conditions. Results. The application of the theory of thermal diffusion as the framework for the description of establishing the asphalt pavement layer temperature equilibrium was reviewed. As it is assumed, when the maximum asphalt pavement layer temperature is reached exists the equilibrium between outgoing and incoming flows such as outgoing and incoming longwave radiation, shortwave incoming radiation, convection losses and heat transfer. After wide investigations carried out by an SHR program, the maximum asphalt pavement layer temperatures calculated on that heat flows balance were proposed to be used in the flexible road pavement designing. Also, the results of investigations carried out to develop the proposed theory of temperature equilibrium were analyzed and it was stated that under certain meteorological conditions the maximum asphalt pavement layer temperature will not be accompanied by the temperature equilibrium; the subsequent redistribution of heat flows may led to the values of temperature that significantly overcome the calculated maximum.

Spatial Variability of Albedo and Net Radiation at Local Scale Using UAV Equipped with Radiation Sensors

Energy balance closure is an important feature in studies of ecosystem exchanges of energy and greenhouse gases using the eddy covariance method. Previous analyses show that this is still a problem with imbalances in the order of 0.6–0.7 to full closure (for only a few sites). It has been suggested that mesoscale transport processes that are not captured by the eddy covariance measurements are the main reason behind the closure problem. So far, very little action has been taken to investigate another potential cause of the problem, namely, the role of spatial variation in net radiation at the scale of typical flux footprints. The reason for this knowledge gap is mainly due to the lack of suitable methods to perform such investigations. Here, we show that such measurements can be performed with an unmanned aerial vehicle equipped with radiation sensors. A comparison using a reference radiometer on a fixed mast with a hovering UAV equipped with pyranometers for incoming and outgoing shortwave radiation and an infrared thermometer for surface temperature measurements shows that incoming and outgoing shortwave radiation can be measured with a standard error of 7.4 Wm−2 and 1.8 Wm−2, respectively. An application of the system was made over a five-year-old forest flux site in Sweden. Here, the net longwave radiation was estimated from the measured surface temperature and the calculated incoming longwave radiation. The results show that during the mission around noon on a clear day, distinct ‘hotspots’ existed over the plantation with the albedo varying between 15.5 and 17.9%, the surface temperature varying between 22.2 and 25.5 °C and the net radiation varying between 330 and 380 Wm−2. These variations are large enough to have a significant impact on the energy balance closure problem. Our conclusion is that we now have the tools to investigate the spatial variability of the radiation regime over flux sites and that this should be given more attention in the future.

Evolution of the microstructure and reflectance of the surface scattering layer on melting, level Arctic sea ice

The microstructure of the uppermost portions of a melting Arctic sea ice cover has a disproportionately large influence on how incident sunlight is reflected and absorbed in the ice/ocean system. The surface scattering layer (SSL) effectively backscatters solar radiation and keeps the surface albedo of melting ice relatively high compared to ice with the SSL manually removed. Measurements of albedo provide information on how incoming shortwave radiation is partitioned by the SSL and have been pivotal to improving climate model parameterizations. However, the relationship between the physical and optical properties of the SSL is still poorly constrained. Until now, radiative transfer models have been the only way to infer the microstructure of the SSL. During the MOSAiC expedition of 2019–2020, we took samples and, for the first time, directly measured the microstructure of the SSL on bare sea ice using X-ray micro-computed tomography. We show that the SSL has a highly anisotropic, coarse, and porous structure, with a small optical diameter and density at the surface, increasing with depth. As the melting surface ablates, the SSL regenerates, maintaining some aspects of its microstructure throughout the melt season. We used the microstructure measurements with a radiative transfer model to improve our understanding of the relationship between physical properties and optical properties at 850 nm wavelength. When the microstructure is used as model input, we see a 10–15% overestimation of the reflectance at 850 nm. This comparison suggests that either a) spatial variability at the meter scale is important for the two in situ optical measurements and therefore a larger sample size is needed to represent the microstructure or b) future work should investigate either i) using a ray-tracing approach instead of explicitly solving the radiative transfer equation or ii) using a more appropriate radiative transfer model.

Machine Learning Models for Approximating Downward Short-Wave Radiation Flux over the Ocean from All-Sky Optical Imagery Based on DASIO Dataset

Downward short-wave (SW) solar radiation is the only essential energy source powering the atmospheric dynamics, ocean dynamics, biochemical processes, and so forth on our planet. Clouds are the main factor limiting the SW flux over the land and the Ocean. For the accurate meteorological measurements of the SW flux one needs expensive equipment-pyranometers. For some cases where one does not need golden-standard quality of measurements, we propose estimating incoming SW radiation flux using all-sky optical RGB imagery which is assumed to incapsulate the whole information about the downward SW flux. We used DASIO all-sky imagery dataset with corresponding SW downward radiation flux measurements registered by an accurate pyranometer. The dataset has been collected in various regions of the World Ocean during several marine campaigns from 2014 to 2021, and it will be updated. We demonstrate the capabilities of several machine learning models in this problem, namely multilinear regression, Random Forests, Gradient Boosting and convolutional neural networks (CNN). We also applied the inverse target frequency (ITF) re-weighting of the training subset in an attempt of improving the SW flux approximation quality. We found that the CNN is capable of approximating downward SW solar radiation with higher accuracy compared to existing empiric parameterizations and known algorithms based on machine learning methods for estimating downward SW flux using remote sensing (MODIS) imagery. The estimates of downward SW radiation flux using all-sky imagery may be of particular use in case of the need for the fast radiative budgets assessment of a site.

Surface warming and wetting due to methane’s long-wave radiative effects muted by short-wave absorption

Although greenhouse gases absorb primarily long-wave radiation, they also absorb short-wave radiation. Recent studies have highlighted the importance of methane short-wave absorption, which enhances its stratospherically adjusted radiative forcing by up to ~ 15%. The corresponding climate impacts, however, have been only indirectly evaluated and thus remain largely unquantified. Here we present a systematic, unambiguous analysis using one model and separate simulations with and without methane short-wave absorption. We find that methane short-wave absorption counteracts ~30% of the surface warming associated with its long-wave radiative effects. An even larger impact occurs for precipitation as methane short-wave absorption offsets ~60% of the precipitation increase relative to its long-wave radiative effects. The methane short-wave-induced cooling is due largely to cloud rapid adjustments, including increased low-level clouds, which enhance the reflection of incoming short-wave radiation, and decreased high-level clouds, which enhance outgoing long-wave radiation. The cloud responses, in turn, are related to the profile of atmospheric solar heating and corresponding changes in temperature and relative humidity. Despite our findings, methane remains a potent contributor to global warming, and efforts to reduce methane emissions are vital for keeping global warming well below 2 °C above preindustrial values.

Anthropogenic heat due to energy consumption contributes to cooler and wetter summers in Southwest China

Anthropogenic heat release is the release of heat generated by anthropogenic energy consumption. The regional mean Anthropogenic heat release flux in Southwest China grew quickly from 0.06 Wm-2 in 1992 to a peak of 0.37 Wm-2 in 2019. This study examines the climatic effects and feedbacks of Anthropogenic heat release due to energy consumption in Southwest China during the boreal summer using simulations from the Community Earth System Model. The modeling results show that Anthropogenic heat release impacts on the lower-troposphere stability and affects large-scale atmospheric circulation in Southwest China, which transports more water vapor and consequently increases the humidity and low cloud cover in Southwest China. This effect impacts the energy balance at the surface by reducing the amount of incoming shortwave radiation that reaches the ground. Anthropogenic heat release decreases the average 2-m air temperature in Southwest China by 0.10 ± 0.01 K (1σ uncertainty) and also decreases the minimum and maximum air temperatures in Southwest China as well. Anthropogenic heat release contributes to cooler and wetter summers in Southwest China. The results show that Anthropogenic heat release is a non-negligible factor that impacts the climate of Southwest China. This study improves our understanding of the climate change resulting from human activities in Southwest China.

Upper tropospheric cloud‐radiation interaction induced by monsoon surge over the South China Sea

AbstractWe have investigated cloud formation over the South China Sea in the upper troposphere and its impacts on the radiation budget of the troposphere and ocean surface under monsoon surges using satellite and reanalysis products and an atmospheric numerical model. During strong surges (SS), the upper tropospheric (UT) cloud formation in central South China Sea shows a clear diurnal cycle, peaking around 12–14 local solar time when the incoming solar radiation is the strongest. The enhanced UT clouds attenuate the incoming solar radiation in the upper troposphere reducing the net downward shortwave radiation flux at the surface by approximately 28% in SS compared with no surge case. In contrast the downward longwave radiation flux is enhanced mainly from the middle to upper troposphere in SS. The cooling because of the diminished incoming shortwave radiation overwhelms the warming due to the longwave radiation at the ocean surface. This cloud radiative forcing is observed partly over the cold tongue in sea surface temperature (SST) in the South China Sea. Numerical simulations with a 1‐dimensional slab ocean model suggests that the monsoon‐induced UT cloud radiative forcing contributes partially to maintain and reinforce the SST cold tongue with a tendency of about 0.08 K in 6 days or about 1/6 of one standard deviation of the Cold Tongue Index in December. The latent heat flux due to the monsoon surge is still the most significant factor maintaining the cold tongue.

Temperature and precipitation biases in CORDEX RCM simulations over South America: possible origin and impacts on the regional climate change signal

Precipitation and temperature biases from a set of Regional Climate Models from the CORDEX initiative have been analysed to assess the extent to which the biases may impact the climate change signal. The analysis has been performed for the South American CORDEX domain. A large warm bias was found over central Argentina (CARG) for most models, mainly in the summer season. Results indicate that the possible origin of this bias is an overestimation of the incoming shortwave radiation, in agreement with an underestimation of the relative humidity at 850 hPa, a variable that could be used to diagnose cloudiness. Regarding precipitation, the largest biases were found during summertime over northeast of Brazil (NEB), where most models overestimate the precipitation, leading to wet biases over that region. This bias agrees with models’ underestimation of both the moisture flux convergence and the relative humidity at lower levels of the atmosphere. This outcome suggests that the generation of more clouds in the models may drive the wet bias over NEB. These systematic errors could affect the climate change signal, considering that these biases may not be stationary. For both CARG and NEB regions, models with higher warm biases project higher warming levels, mainly in the summer season. In addition, it was found that these relationships are statistically significant with a confidence level of 95%, pointing out that biases are linearly linked with the climate change signal. For precipitation, the relationship between the biases and the projected precipitation changes is only statistically significant for the NEB region, where models with the largest wet biases present the greatest positive precipitation changes during the warm season. As in the case of biases, the analysis of the temperature and precipitation projections over some regions of South America suggests that clouds could affect them. The results found in this study point out that the analysis of the bias behaviour could help in a better interpretation of the climate change signal.

Effects of transport on a biomass burning plume from Indochina during EMeRGe-Asia identified by WRF-Chem

Abstract. The Indochina biomass burning (BB) season in springtime has a substantial environmental impact on the surrounding areas in Asia. In this study, we evaluated the environmental impact of a major long-range BB transport event on 19 March 2018 (a flight of the High Altitude and Long Range Research Aircraft (HALO; https://www.halo-spp.de, last access: 14 February 2023) research aircraft, flight F0319) preceded by a minor event on 17 March 2018 (flight F0317). Aircraft data obtained during the campaign in Asia of the Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales (EMeRGe) were available between 12 March and 7 April 2018. In F0319, results of 1 min mean carbon monoxide (CO), ozone (O3), acetone (ACE), acetonitrile (ACN), organic aerosol (OA), and black carbon aerosol (BC) concentrations were up to 312.0, 79.0, 3.0, and 0.6 ppb and 6.4 and 2.5 µg m−3, respectively, during the flight, which passed through the BB plume transport layer (BPTL) between the elevation of 2000–4000 m over the East China Sea (ECS). During F0319, the CO, O3, ACE, ACN, OA, and BC maximum of the 1 min average concentrations were higher in the BPTL by 109.0, 8.0, 1.0, and 0.3 ppb and 3.0 and 1.3 µg m−3 compared to flight F0317, respectively. Sulfate aerosol, rather than OA, showed the highest concentration at low altitudes (<1000 m) in both flights F0317 and F0319 resulting from the continental outflow in the ECS. The transport of BB aerosols from Indochina and its impacts on the downstream area were evaluated using a Weather Research Forecasting with Chemistry (WRF-Chem) model. The modeling results tended to overestimate the concentration of the species, with examples being CO (64 ppb), OA (0.3 µg m−3), BC (0.2 µg m−3), and O3 (12.5 ppb) in the BPTL. Over the ECS, the simulated BB contribution demonstrated an increasing trend from the lowest values on 17 March 2018 to the highest values on 18 and 19 March 2018 for CO, fine particulate matter (PM2.5), OA, BC, hydroxyl radicals (OH), nitrogen oxides (NOx), total reactive nitrogen (NOy), and O3; by contrast, the variation of J(O1D) decreased as the BB plume's contribution increased over the ECS. In the lower boundary layer (<1000 m), the BB plume's contribution to most species in the remote downstream areas was <20 %. However, at the BPTL, the contribution of the long-range transported BB plume was as high as 30 %–80 % for most of the species (NOy, NOx, PM2.5, BC, OH, O3, and CO) over southern China (SC), Taiwan, and the ECS. BB aerosols were identified as a potential source of cloud condensation nuclei, and the simulation results indicated that the transported BB plume had an effect on cloud water formation over SC and the ECS on 19 March 2018. The combination of BB aerosol enhancement with cloud water resulted in a reduction of incoming shortwave radiation at the surface in SC and the ECS by 5 %–7 % and 2 %–4 %, respectively, which potentially has significant regional climate implications.

Effects of Different Land Use Types on Soil Surface Temperature in the Heihe River Basin

The micrometeorological elements, radiation budget, and surface energy distribution at four sites with land cover types of vegetable, orchard, maize, and desert in the Heihe River basin (HRB) from June 2012 to September 2012 are compared to investigate the differences in the land–atmosphere interaction between different surface types and the biophysical effects of land use and land cover change on surface temperature. The desert site has the highest soil surface temperature during both daytime and nighttime. The strongest cooling effects of maize, orchard, and vegetable are −20.43, −19.35, and −16.42 K, respectively, during daytime, and the average cooling effects are −1.38, −2.52, and −0.93 K, respectively, at nighttime. The differences in the surface cooling effects of the non-desert sites relative to the desert are attributed to the differences in albedo and incoming shortwave radiation, emissivity and incoming longwave radiation, sensible heat flux, latent heat flux, and soil surface heat flux, according to the direct decomposed temperature metric theory. The radiation terms have negative feedbacks on the cooling effects in the non-desert sites. Latent heat flux plays a key role in the differences in the surface temperature among the four sites during both daytime and nighttime, and the soil surface heat flux is also a main factor at night.

Evaluation of the convection-permitting regional climate model CNRM-AROME41t1 over Northwestern Europe

Since a decade, convection-permitting regional climate models (CPRCM) have emerged showing promising results, especially in improving the simulation of precipitation extremes. In this article, the CPRCM CNRM-AROME developed at the Centre National de Recherches Météorologiques (CNRM) since a few years is described and evaluated using a 2.5-km 19-year long hindcast simulation over a large northwestern European domain using different observations through an added-value analysis in which a comparison with its driving 12-km RCM CNRM-ALADIN is performed. The evaluation is challenging due to the lack of high-quality observations at both high temporal and spatial resolutions. Thus, a high spatio-temporal observed gridded precipitation dataset was built from the collection of seven national datasets that helped the identification of added value in CNRM-AROME. The evaluation is based on a series of standard climatic features that include long-term means and mean annual cycles of precipitation and near-surface temperature where CNRM-AROME shows little improvements compared to CNRM-ALADIN. Additional indicators such as the summer diurnal cycle and indices of extreme precipitation show, on the contrary, a more realistic behaviour of the CNRM-AROME model. Moreover, the analysis of snow cover shows a clear added-value in the CNRM-AROME simulation, principally due to the improved description of the orography with the CPRCM high resolution. Additional analyses include the evaluation of incoming shortwave radiation, and cloud cover using satellite estimates. Overall, despite some systematic biases, the evaluation indicates that CNRM-AROME is a suitable CPRCM that is superior in many aspects to the RCM CNRM-ALADIN.

Hydrothermal conditions of southern and northern slope soils of northeastern Great Xing'an Mountain, China

The purpose of the article is to study the influence features of polar-oriented slopes on the near-surface energy and hydrothermal balance in the seasonal cryolithozone. The authors carried out a complex of field observations including measurement of air and underlying surface temperature, soil moisture, solar radiation and wind speed at the hydrological stations of Songling (southern slope) and Luoguhe (northern slope) in the northeast of the Great Xing'an Mountain (China). The analysis of the data obtained allowed to conclude that, on the one hand, the long-term influence of the thermal balance components causes significant differences in the soil structure and properties on differently oriented slopes. The number of daily freeze-thaw soil cycles on the southern slope (100 cycles) significantly exceeds the ones on the northern slope (56 cycles). The soil on the southern soil is 3 °C warmer than that on the northern slope, and its humidity in the area of the Songling hydrological station is lower than that at the Luoguhe station. On the other hand, differences in soil properties control the energy exchange between the atmosphere and the earth's surface, this means that the incoming short-wave solar radiation and heat flux into the soil on the southern slope is greater than on the northern one. Therefore, slope orientation is one of the significant environmental factors affecting the influx of solar energy, temperature and humidity of the soils in the northeastern Great Xing'an Mountain. It also has a decisive role for the spatial distribution and evolution of seasonal permafrost in the region and, accordingly, affects the stability and safety of engineering structures. The performed research is important for understanding the relationship between climate and frozen soil in the mountainous areas with seasonal cryolithozone as well as for optimization of boundary conditions when modeling rock freeze-thaw processes.

Assessment of the impact of atmospheric aerosols and meteorological data assimilation on simulation of the weather over India during summer 2015

This study investigates the sensitivity of climate model-predicted surface radiation and surface meteorological parameters to atmospheric aerosols and meteorological data assimilation (meteorological initial and boundary conditions) utilizing the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). For this purpose, three sets of simulations including WRFChemCntrl (WRFChem without meteorological data assimilation), WRFChemDA (WRFChem with meteorological data assimilation) and WRFDA (WRF only with meteorological data assimilation) were performed over the South Asian domain. A 12-hourly cyclic 3-dimensional variational (3DVAR) meteorological data assimilation (DA) of in-situ meteorological observations was used to generate WRFChemDA and WRFDA reanalyses, during summer (March–May) 2015. The Carbon Bond Mechanism-Z (CBMZ) gas-phase chemistry with Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) was selected for the chemistry simulations. A reduction in incoming shortwave radiation (∼10–60 W/m2) over the Indian landmass and a slight increase (∼10–20 W/m2) over the surrounding oceanic region due to the influence of aerosols in WRF-Chem simulations was observed, suggesting that aerosols effects, were simulated by the model successfully. These effects of aerosols were further evident in the model output of other parameters such as outgoing longwave radiation at the surface, 2-m temperature (T2), 2-m relative humidity (RH2), and planetary boundary layer height (PBLH). Our results also show that the inclusion of aerosols in the WRFDA simulations (i.e WRFChemDA) improved the prediction of incoming shortwave radiation but deteriorated some of the meteorological parameters. However, an improved agreement between model simulated radiation, T2, RH2 and PBLH and observations was evident in WRFChemDA output compared to WRFChemCntrl output, reinforcing DA induced improvements in meteorological parameters for a given model set-up.