Longwave Radiation Components Research Articles

Modeling the mid-piacenzian warm climate using the water isotope-enabled Community Earth System Model (iCESM1.2-ITPCAS)

The mid-Piacenzian Warm Period (MPWP, ~ 3.264–3.025 Ma) is the most recent example of a persistently warmer climate in equilibrium with atmospheric CO2 concentrations similar to today. Towards studying patterns and dynamics of a warming climate the MPWP is often compared to today. Following the Pliocene Model Intercomparison Project, Phase 2 (PlioMIP2) protocol we prepare a water isotope-enabled Community Earth System Model (iCESM1.2) simulation that is warmer and wetter than the PlioMIP2 multi-model ensemble (MME). While our simulation resembles PlioMIP2 MME in many aspects we find added insights. (1) Considerable warmth at high latitudes exceeds previous simulations. Polar amplification (PA) is comparable to proxies, enabled by iCESM1.2’s high climate sensitivity and a distinct method of ocean initialization. (2) Major driver of warmth is the downward component of clear-sky surface long-wave radiation (ΔTrlds_clearsky\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\varDelta T_{\ ext{rlds}\\_\ ext{clearsky}}$$\\end{document}). (3) In iCESM1.2 modulated dominance of dynamic (δDY) processes causes different low-latitude (~ 30 S°–10°N) precipitation response than the PlioMIP2 MME, where thermodynamic processes (δTH) dominate. (4) Modulated local condensation leads to lower δ18Op across tropical Indian Ocean and surrounding Asian-African-Australian monsoon regions. (5) We find contrasting changes in tropical atmospheric circulations (Hadley and Walker cells). Anomalous regional meridional (zonal) circulation, forced by changes in tropical-subtropical (tropical) diabatic processes, presents a more comprehensive perspective than explaining weakened and expanded Hadley circulation (strengthened and westward-shifted Walker circulation) via static stability. (6) Enhanced Atlantic meridional overturning circulation owes to a closed Bering Strait.

A daily 5-km all-sky sea-surface longwave radiation product based on statistically modified deep neural network and spatiotemporal analysis for 1981–2018

Longwave radiation components, including downward, upward, and net longwave radiation (DLR, ULR, and NLR, respectively), are essential parameters in heat flux exchange across the ocean–atmosphere interface. However, few long-term, high-resolution, and accurate sea–surface longwave radiation (SSLR) products are available. We generated the first high-resolution (5-km) all-sky daily SSLR product from Advanced Very High-Resolution Radiometer (AVHRR) top-of-atmosphere observations, combined with the European Center for Medium-Range Weather Forecasts Reanalysis V5 near-surface meteorological variables and National Oceanic and Atmospheric Administration sea–surface temperatures from 1981 to 2018. We coupled the densely connected convolutional neural network and bidirectional long short-term memory neural network as a retrieval algorithm. The training dataset was generated using integrated SSLR samples from 2002 to 2012 at 437 globally distributed locations. The archived product, SSLR_AVHRR, showed a high accuracy against 81,546 buoy-based observations from eight observation networks, with an R2 of 0.96 (1.00, 0.77), root mean square error of 10.27 (4.51, 9.27) Wm−2, and mean bias error of −1.30 (0.30, −0.72) Wm−2 for DLR (ULR, NLR) retrievals. Based on SSLR_AVHRR, the global DLR (ULR) flux exhibited a significantly (p-value < 0.05) increasing trend of 1.03 (1.08) Wm−2/decade during 1982–2018. The trend was 0.24 (0.34) Wm−2/decade during 1982–2000, which increased to 1.79 (1.45) Wm−2/decade during 2001–2018. This globally increasing trend was dominantly impacted by the significant increases in high latitude, particularly in the Arctic Ocean. Trend variations at low latitudes, which were more frequent than at middle and high latitudes because of the El Niño-Southern Oscillation, mitigated the increasing rates of global DLR and ULR after strong El Niño years, whereas the global NLR flux remained relatively stable throughout the study period. This method can be extended and applied to estimate other air-sea fluxes based on a unified estimating framework to help mitigate imbalanced energy and freshwater budgets at the air-sea interface to some degree.

Snowmelt estimation using an empirical radiation model

This study developed a novel approach for estimating snowmelt using an empirical radiation model, referred to as the Empirical Radiation Snowmelt Model, or ERSM. ERSM assumes that energy available to melt snow is equivalent to the sum of the shortwave radiation absorbed by the snowpack and the net longwave radiation at the snow surface. ERSM has two components. The first component is an empirically determined relationship between the observed daily snowmelt and the daily potential shortwave radiation. The longwave radiation component is implicitly estimated through its influence on the observed snowmelt. The daily potential shortwave radiation was found using two calculated parameters: the top-of-the-atmosphere shortwave radiation and the albedo of the snow surface. This first component simulates the average snowmelt that will occur for a given level of the potential shortwave radiation. The second component of ERSM estimates the difference between the average snowmelt simulated from the potential shortwave radiation (first component) and the actual snowmelt that occurred on any day. Observations from 20 SNOTEL11SNOTEL-U.S. Department of Agriculture, Natural Resources Conservation Service Snow Telemetry site. sites in the Truckee River Watershed were used to develop separate ERSM parameters for each site. ERSM was able to robustly predict snowmelt for all sites considered in this study. The error statistics vary with the magnitude of the observed daily snowmelt and the best results were found for magnitudes at which the majority of snowmelt occurs. A particularly valuable application of ERSM is its use to estimate the melt factor required by temperature index snowmelt models. ERSM can explain a large degree of the observed variance of the temperature index melt factor.

Analysis of the surface energy budget during supercooling in rivers

In northern rivers, heat loss from the water surface is the key driver of supercooling in rivers and the subsequent generation of river ice. The ability to estimate the different surface heat components is crucial to accurately model supercooling and the various ice formation processes. To calibrate these models, concurrent water temperature and local meteorological data are needed, which can be a challenging task. Therefore, it is important to understand the relative importance of the different heat components on supercooling of water. For this purpose, the properties of 190 supercooling events observed during the 2016–2017 season on two regulated rivers in Alberta, Canada were analyzed together with the calculated surface heat budget using weather data from local weather stations. Longwave radiation was found to be the dominant negative heat flux for 80.0% of all events. During supercooling events, the longwave radiation and sensible components had average values of −65.7 and −46.6 W/m2, respectively. The evaporative heat flux component was found to be negligible with an average value −4.52 W/m2. Sensible heat flux tended to be the dominant cooling heat flux when the air temperature was approximately -15 °C or colder. The shortwave radiation component was the dominant warming heat flux for 97.4% of all events with an average value 52.6 W/m2. The diurnal cycling of the net heat flux due to shortwave radiation was found to be the most significant factor in determining the start and end of supercooling events.

Generating 5 km resolution 1981–2018 daily global land surface longwave radiation products from AVHRR shortwave and longwave observations using densely connected convolutional neural networks

Surface longwave radiation (SLWR) components, including downward longwave radiation (DLR), upward longwave radiation (ULR), and net longwave radiation (NLR), are major contributors to the Earth's surface radiation budget and play important roles in ecological, hydrological, and atmospheric processes. Previous SLWR products have different drawbacks, such as being temporally short (after 2000), spatially coarse (≥ 25 km), and instantaneous values, which hinder their in-depth applications in land surface process modeling and climate trends analysis. Here, we reported the Advanced Very High-Resolution Radiometer (AVHRR)-based Global LAnd Surface Satellites (GLASS-AVHRR) SLWR products over the global land surface at a 5 km spatial resolution and 1 day temporal resolution between 1981 and 2018. These products were generated using multiple densely connected convolutional neural networks (DesCNNs) from the AVHRR top-of-atmosphere (TOA) reflected and emitted observations and European Centre for Medium-Range Weather Forecasts (ECMWF) fifth generation reanalysis (ERA5) near-surface meteorological data. DesCNNs were trained using integrated SLWR samples derived from the Moderate Resolution Imaging Spectroradiometer (MODIS)-based GLASS, Clouds and the Earth's Radiant Energy System Synoptic (CERES-SYN), and ERA5 SLWR products. In situ measurements from 231 globally distributed sites were used to evaluate the GLASS-AVHRR SLWR estimates. The results illustrated the overall high accuracies of GLASS-AVHRR SLWR products with root-mean-square-errors (RMSEs) of 18.66, 14.92, and 16.29 Wm−2, and mean bias errors (MBEs) of −2.69, −3.77, and 0.49 Wm−2 for all-sky DLR, ULR, and NLR, respectively. We found good correlation and consistency between GLASS-AVHRR and both CERES-SYN and ERA5 in terms of spatial patterns, latitudinal gradient, and temporal evolution. Our results revealed the significant contribution of shortwave observations to SLWR estimation owing to the high amounts of clouds over polar regions and water vapor and clouds in tropical areas, which was not previously widely recognized by the remote sensing community. GLASS-AVHRR SLWR products were updated, documented, and made available to the public at www.glass.umd.edu and www.geodata.cn.

Downwelling longwave radiation and sensible heat flux observations are critical for surface temperature and emissivity estimation from flux tower data

Land surface temperature (LST) is a preeminent state variable that controls the energy and water exchange between the Earth’s surface and the atmosphere. At the landscape-scale, LST is derived from thermal infrared radiance measured using space-borne radiometers. In contrast, plot-scale LST estimation at flux tower sites is commonly based on the inversion of upwelling longwave radiation captured by tower-mounted radiometers, whereas the role of the downwelling longwave radiation component is often ignored. We found that neglecting the reflected downwelling longwave radiation leads not only to substantial bias in plot-scale LST estimation, but also have important implications for the estimation of surface emissivity on which LST is co-dependent. The present study proposes a novel method for simultaneous estimation of LST and emissivity at the plot-scale and addresses in detail the consequences of omitting down-welling longwave radiation as frequently done in the literature. Our analysis uses ten eddy covariance sites with different land cover types and found that the LST values obtained using both upwelling and downwelling longwave radiation components are 0.5–1.5 K lower than estimates using only upwelling longwave radiation. Furthermore, the proposed method helps identify inconsistencies between plot-scale radiometric and aerodynamic measurements, likely due to footprint mismatch between measurement approaches. We also found that such inconsistencies can be removed by slight corrections to the upwelling longwave component and subsequent energy balance closure, resulting in realistic estimates of surface emissivity and consistent relationships between energy fluxes and surface-air temperature differences. The correspondence between plot-scale LST and landscape-scale LST depends on site-specific characteristics, such as canopy density, sensor locations and viewing angles. Here we also quantify the uncertainty in plot-scale LST estimates due to uncertainty in tower-based measurements using the different methods. The results of this work have significant implications for the combined use of aerodynamic and radiometric measurements to understand the interactions and feedbacks between LST and surface-atmosphere exchange processes.

Neural network-based approach for estimation of downwelling longwave radiation flux under cloudy-sky conditions

Net surface radiation defines the availability of radiation energy on and near the surface to drive many physical and physiological processes such as latent heat, sensible heat fluxes, and evapotranspiration. One of the prime challenges of modeling radiation budget is estimation of net longwave radiation. Incoming or downwelling longwave radiation (LWin) flux is one of the two key components of net longwave radiation. Its estimation in cloudy conditions has always been a challenge due to lack of instrumentation and regular measurements at different spatial scales. In this study, two artificial neural network (ANN) multi-layer perceptron (MLP) models were developed for LWin flux estimation under cloudy-sky during daytime and nighttime using half-hourly flux measurements over different agro-climatic settings and several atmospheric parameters from measurements, satellite-based observations, and model outputs. A comparative evaluation was made between existing or newly developed multivariate linear regression (MVR) models and ANN-based models. The latter set of models were found to be superior to the best MVR model during both daytime and nighttime. The ANN models were found to have consistent performance across different sites and cloud types except less accuracy in sub-humid or humid climate and in deep convection cloud. The ANN models showed overall accuracies of 2.7% and 3.3% of measured mean and R2 of 0.86 and 0.85 for daytime and nighttime, respectively, when compared with independent data of in-situ measurements.

Top‐of‐Atmosphere Radiation Budget and Cloud Radiative Effects Over the Tibetan Plateau and Adjacent Monsoon Regions From CMIP6 Simulations

AbstractThis study investigates the top‐of‐atmosphere (TOA) radiation budget (RT) and cloud radiative effects (CREs) over the Tibetan Plateau (TP) and adjacent Asian monsoon regions including Eastern China (EC) and South Asia (SA) using the Coupled Model Intercomparison Project 6 (CMIP6) simulations. Considerable simulation biases occur but specific causes differ in these regions. Most models underestimate the intensity of annual mean RT and cloud radiative cooling effect over the TP, and the RT during the cold‐warm transition period is hard to capture. The biases in surface temperature and cloud fractions substantially contribute to cloud‐radiation biases over the western and eastern TP, respectively. Over EC, the intensity of RT and cloud radiative cooling effect is seriously underestimated especially in the springtime when the model spread is large, and their biases are closely related to less low‐middle cloud fractions and weaker ascending motion. Over SA, simulation biases mainly arise from longwave radiative components associated with less high cloud fraction and weaker convection, with the large model spread in the summertime. The annual cycles of RT and CREs over EC and SA can be well reproduced by most models, while the summertime peak of the net CRE over the TP occurs later than the observation. The RT and its simulation bias strongly depend on the cloud radiative cooling effect over EC and SA. Our results demonstrate that contemporary climate models still have obvious difficulties in representing various complex cloud‐radiation processes in Asian monsoon regions.

Effect of the radiation balance on warming occurrence over West Africa

In this study, hourly atmospheric radiation and surface temperature data were taken from the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) database for the period of 36 years (1980–2015) in the West African region. The main objective of the research is to study the effect of the radiation balance on the warming scenario in West Africa. The research deduced the warming scenario from extreme weather events referred to as warm nights and hot days. The severity of the warming event was measured using the methods of climate sensitivity and trend. The effect of the radiation balance on the warming event was evaluated using a cross-correlation technique. Analyses showed a decrease from 140.37±2.11 W/m2 in 1980 to 132.89±2.18 W/m2 in 2015 in the average annual radiation balance in West Africa as a whole. This shows that the radiation balance budget has dominant long-wave radiation components that determine the warming effect on the surface of the earth. Also, the values of the sensitivity of the climate were observed between 1.74±0.08 and 3.92±0.69 in the studied regions. Meanwhile, the Intergovernmental Panel on Climate Change (IPCC) assessment study on the occurrence of surface warming sets these values between 1.5 and 4.5 threshold values. Furthermore, prevailing significant increasing trends were observed for warm nights and warm days temperatures with the highest values of 35.52±0.77 C and 42.34±0.73 °C respectively over the whole West African Region. Besides, the cross-correlation analysis showed that net radiation was related to extreme temperatures at a short response time with a strong correlation. Lastly, the findings indicate that the radiation balance has a significant contribution to the warming of the West African climate system. This will consequently lead to increased thermal stress, drought, and floods which could have adverse effects on agriculture, biodiversity, and ecosystems as a whole in the 21st century.

Modeling the incoming all-wave radiation in a planted trench system

Micro-catchment systems (MCs) are designed to harvest and utilize rainwater, with the aim of supporting crop growth in arid regions. While MCs were traditionally built with shallow infiltration basins, recent research indicates that MCs with deeper basins lose less water to the atmosphere than MCs with shallower basins. Consequently, we can expect more water to infiltrate the soil and be available to trees grown in deeper MCs than those grown in shallow MCs. The reduction in the direct water loss is owed, to a large extent, to the decreased flux of incoming shortwave radiation reaching the surface in deeper basins. The degree to which the incoming shortwave radiation reaching the floor of the MC is reduced, in turn, depends on the system’s dimensions and orientation, geographical location, canopy geometry, soil properties, date, and time. We present a model that calculates the incoming all-wave (short- and longwave) radiation flux densities reaching any point on the floor of a trench MC in which trees are planted. To add to previously developed models that considered direct radiation, diffuse radiation, and direct and diffuse radiation reflected downwards from the walls of the trench, the model accounts for possible shading and attenuation of the radiation caused by the presence of a canopy in the system. We have also added the component of longwave radiation, considering longwave radiation emitted from the atmosphere, from the canopy of trees planted within the system, and from the trench walls.We validated the model by comparing modeled results to field measurements inside a planted trench system. We used pyranometers to measure the incoming shortwave radiation and a 4-way net radiometer for the incoming longwave. Our results indicate that the model accurately depicts the diurnal course of shortwave and longwave radiation at different points on the floor of a N-S oriented trench MC and for different solar elevation angles. Simulations for the Negev Desert revealed that the presence of a canopy can strongly influence which trench configurations lead to the greatest decreases in incoming shortwave radiation. When a large canopy is present and the trench is wide, less radiation reaches the ground in N-S oriented trenches than in E-W oriented trenches. While the incoming longwave radiation at the bottom of the trench MC is higher than that on an equivalent horizontal surface at ground level, this increase is not enough to offset the decrease in shortwave radiation. The simulations indicate that the total incoming all-wave radiation (combined shortwave and longwave) inside trenches is less than that outside.

Cloud Influence on ERA5 and AMPS Surface Downwelling Longwave Radiation Biases in West Antarctica

AbstractThe surface downwelling longwave radiation component (LW↓) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW↓ signal measured at the surface. In this study, we examine the LW↓ model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 model relative to observations from the ARM West Antarctic Radiation Experiment (AWARE) campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud-layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW↓ during clear-sky conditions, high error variability (standard deviations &amp;gt; 20 W m−2) during any type of cloud occurrence, and negative LW↓ biases when LBCLs are observed (bias magnitudes &amp;gt;15 W m−2 in tenuous LBCL cases and &amp;gt;43 W m−2 in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for the identified LW↓ biases in both models is the result of excessive ice formation and growth, which could stem from the model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.

Micrometeorological determinants of pedestrian thermal exposure during record-breaking heat in Tempe, Arizona: Introducing the MaRTy observational platform

We report the first set of urban micrometeorological measurements for assessment of pedestrian thermal exposure during extreme heat in a dry climate. Hourly measurements of air temperature, humidity, wind speed and six-directional shortwave and longwave radiation were recorded with a mobile human-biometeorological station (MaRTy) from 10:00 to 21:00 local time, June 19, 2016, at 22 sites that include diverse microscale urban land cover. Sky view factor (SVF) and 360° pervious and impervious view factors for each location were calculated from six-directional fisheye photographs. Mean radiant temperature (TMRT) was determined using the six-directional method. Three-dimensional radiation budgets were decomposed into directional weighted shortwave and longwave radiation components to create a distinct TMRT profile for each site and determine the main drivers of TMRT and thermal exposure. Air temperature peaked locally at 48.5 °C, with a maximum TMRT of 76.4 °C at 15:00 MST in an east-west building canyon. Longwave radiation measured by laterally-oriented sensors dominated the TMRT budget, suggesting the importance of cooling vertical surfaces adjacent to pedestrians. Lateral shortwave radiation contributions were most spatially and temporally variable across TMRT profiles, reflecting the diverse shade conditions. The largest radiation fluxes contributing to TMRT were particularly sensitive to shade and secondarily to ground cover. Trees reduced afternoon TMRT up to 33.4 °C but exhibited a clear TMRT increase of up to 5 °C after sunset; during daytime, trees generated ground cover-dependent longwave radiant cooling or warming. Replacement of impervious with pervious ground cover cooled TMRT at all measurement times, even under dense tree shade. While recent work has found that adaptation cannot offset projected urban air temperature increases, outdoor thermal exposure depends on additional micrometeorological variables, including shortwave and longwave radiation, indicating the need and the opportunity to create pedestrian spaces that are radiantly cool within the context of future urban heat.

Heat Flux Sources Analysis to the Ross Ice Shelf Polynya Ice Production Time Series and the Impact of Wind Forcing

The variation of Ross Ice Shelf Polynya (RISP) ice production is a synergistic result of several factors. This study aims to analyze the 2003–2017 RISP ice production time series with respect to the impact of wind forcing on heat flux sources. RISP ice production was estimated from passive microwave sea ice concentration images and reanalysis meteorological data using a thermodynamic model. The total ice production was divided into four components according to the amount of ice produced by different heat fluxes: solar radiation component (Vs), longwave radiation component (Vl), sensible heat flux component (Vfs), and latent heat flux component (Vfe). The results show that Vfs made the largest contribution, followed by Vl and Vfe, while Vs had a negative contribution. Our study reveals that total ice production and Vl, Vfs, and Vfe highly correlated with the RISP area size, whereas Vs negatively correlated with the RISP area size in October, and had a weak influence from April to September. Since total ice production strongly correlates with the polynya area and this significantly correlates with the wind speed of the previous day, strong wind events lead to sharply increased ice production most of the time. Strong wind events, however, may only lead to mildly increasing ice production in October, when enlarged Vs reduces the ice production. Wind speed influences ice production by two mechanisms: impact on polynya area, and impact on heat exchange and phase transformation of ice. Vfs and Vfe are influenced by both mechanisms, while Vs and Vl are only influenced by impact on polynya area. These two mechanisms show different degrees of influence on ice production during different periods. Persistent offshore winds were responsible for the large RISP area and high ice production in October 2005 and June 2007.

Pseudo bond graph tunnel greenhouse model with accurate longwave/shortwave radiations model

ABSTRACT This research work is focused on the construction of an accurate longwave/shortwave radiation model on a tunnel greenhouse pseudo-bond graph model, widely used in Tunisia. This model includes sun position, useful incoming solar radiation model, sky longwave radiation model, inside longwave and shortwave radiation model. The key idea is to use bond graphs allowing a lumped modelling approach which is suitable for control applications. Furthermore, an evaluation of some longwave radiative model components was made, noting that these components are particularly sensitive regarding to the thermal behaviour of the model. Experimental tunnel greenhouse data are used as validation elements for the present model with globally good results. A comparative study was also performed between the present model and a previous bond graph model containing a simplistic radiative model. Practical simulation results show a clear improvement compared with the previous model.

Comparison of methodologies for cloud cover estimation in Brazil - A case study

Clouds are the major modulator of the shortwave and longwave radiation components of the Earth's energy balance and, as such, help to regulate the planet's temperature. In the energy sector, clouds are a source of instability in the generation of energy using solar technologies. This study aims at comparing three approaches to get cloud cover information in the Southeastern region of Brazil during the period of approximately three months. The first method, assumed as reference, uses all-sky camera pictures for the cloud cover estimation. The other two methodologies use downward longwave radiation with surface meteorological data and geostationary satellite data. Both methods presented good agreement with the camera for clear sky and overcast conditions, with probabilities of detection of 92.8% and 80.7% for the longwave method and 93.3% and 87.6% for the satellite method, respectively. The major problem occurs with the broken-clouds sky scenario, with probabilities of detection above 38%, where each method has its own specificity, such as, longwave emissivity of the atmosphere, spatial resolution and view geometry. The long-wave method has the minor R correlation with the camera (87%) when compared with the satellite method (93%) and requires a daily normalization, which make it not usable for instantaneous measurements. Regarding the satellite method, the most important issue is the spatial resolution, which has the major impact on the broken-clouds sky scenarios. The cloud masking works properly for large clouds with, at least, the size comparable to the satellite image pixel. Furthermore, the method using the all-sky camera also needs to be improved, because it presented some deficiencies, like very bright areas around the sun, sometimes identified as clouds, leading to cloud cover overestimation.

Large Increase in Incident Shortwave Radiation due to the Ozone Hole Offset by High Climatological Albedo over Antarctica

Despite increasing scientific scrutiny in recent years, the direct impact of the ozone hole on surface temperatures over Antarctica remains uncertain. Here, this question is explored by using the Community Earth System Model–Whole Atmosphere Community Climate Model (CESM-WACCM), contrasting two ensembles of runs with and without stratospheric ozone depletion. It is found that, during austral spring, the ozone hole leads to a surprisingly large increase in surface downwelling shortwave (SW) radiation over Antarctica of 3.8 W m−2 in clear sky and 1.8 W m−2 in all sky. However, despite this large increase in incident SW radiation, no ozone-induced surface warming is seen in the model. It is shown that the lack of a surface temperature response is due to reflection of most of the increased downward SW, resulting in an insignificant change to the net SW radiative heating. To first order, this reflection is simply due to the high climatological surface albedo of the Antarctic snow (97% in visible SW), resulting in a net zero ozone-induced surface SW forcing. In addition, it is shown that stratospheric ozone depletion has a negligible effect on longwave (LW) radiation and other components of the surface energy budget. These results suggest a minimal role for ozone depletion in forcing Antarctic surface temperature trends on a continental scale.

Surface energy budget responses to radiative forcing at Summit, Greenland

Abstract. Greenland Ice Sheet surface temperatures are controlled by an exchange of energy at the surface, which includes radiative, turbulent, and ground heat fluxes. Data collected by multiple projects are leveraged to calculate all surface energy budget (SEB) terms at Summit, Greenland, for the full annual cycle from July 2013 to June 2014 and extend to longer periods for the radiative and turbulent SEB terms. Radiative fluxes are measured directly by a suite of broadband radiometers. Turbulent sensible heat flux is estimated via the bulk aerodynamic and eddy correlation methods, and the turbulent latent heat flux is calculated via a two-level approach using measurements at 10 and 2 m. The subsurface heat flux is calculated using a string of thermistors buried in the snow pack. Extensive quality-control data processing produced a data set in which all terms of the SEB are present 75 % of the full annual cycle, despite the harsh conditions. By including a storage term for a near-surface layer, the SEB is balanced in this data set to within the aggregated uncertainties for the individual terms. November and August case studies illustrate that surface radiative forcing is driven by synoptically forced cloud characteristics, especially by low-level, liquid-bearing clouds. The annual cycle and seasonal diurnal cycles of all SEB components indicate that the non-radiative terms are anticorrelated to changes in the total radiative flux and are hence responding to cloud radiative forcing. Generally, the non-radiative SEB terms and the upwelling longwave radiation component compensate for changes in downwelling radiation, although exact partitioning of energy in the response terms varies with season and near-surface characteristics such as stability and moisture availability. Substantial surface warming from low-level clouds typically leads to a change from a very stable to a weakly stable near-surface regime with no solar radiation or from a weakly stable to neutral/unstable regime with solar radiation. Relationships between forcing terms and responding surface fluxes show that the upwelling longwave radiation produces 65–85 % (50–60 %) of the total response in the winter (summer) and the non-radiative terms compensate for the remaining change in the combined downwelling longwave and net shortwave radiation. Because melt conditions are rarely reached at Summit, these relationships are documented for conditions of surface temperature below 0 °C, with and without solar radiation. This is the first time that forcing and response term relationships have been investigated in detail for the Greenland SEB. These results should both advance understanding of process relationships over the Greenland Ice Sheet and be useful for model validation.

Evaluation of the Weather Research and Forecasting Model in the Durance Valley Complex Terrain during the KASCADE Field Campaign

AbstractIn the winter of 2012/13, the Katabatic Winds and Stability over Cadarache for the Dispersion of Effluents (KASCADE) observational campaign was carried out in southeastern France to characterize the wind and thermodynamic structure of the (stable) planetary boundary layer (PBL). Data were collected with two micrometeorological towers, a sodar, a tethered balloon, and radiosoundings. Here, this dataset is used to evaluate the representation of the boundary layer in the Weather Research and Forecasting (WRF) Model. In general, it is found that diurnal temperature range (DTR) is largely underestimated, there is a strong negative bias in both longwave radiation components, and evapotranspiration is overestimated. An illustrative case is subjected to a thorough model-physics evaluation. First, five PBL parameterization schemes and two land surface schemes are employed. A marginal sensitivity to PBL parameterization is found, and the sophisticated Noah land surface model represents the extremes in skin temperature better than does a more simple thermal diffusion scheme. In a second stage, sensitivity tests for land surface–atmosphere coupling (through parameterization of z0h/z0m), initial soil moisture content, and radiation parameterization were performed. Relatively strong surface coupling and low soil moisture content result in a larger sensible heat flux, deeper PBL, and larger DTR. The larger sensible heat flux is not supported by the observations, however. It turns out that, for the selected case, a combination of subsidence and warm-air advection is not accurately simulated, but this inaccuracy cannot fully explain the discrepancies found in the WRF simulations. The results of the sensitivity analysis reiterate the important role of initial soil moisture values.

Microclimate Modification by Urban Shade Trees – An Integrated Approach to Aid Ecosystem Service Based Decision-making

Since microclimate regulation is one of the most important services of vegetation that is directly perceived by urban population, many studies aimed to evaluate and map this service on different spatial scales. Most of the investigations focused on the modification of only one parameter, namely the reduction of air temperature. However, it is important to state that thermal sensation, health and well-being are influenced by more atmospheric parameters, including air humidity, wind velocity and the three-dimensional short- and long-wave radiation environment as well. This necessitates the assessment of the modification effect of urban vegetation on the thermal components separately. With the above mentioned objective, this paper presents the initial results of a microclimate investigation series carried out in Szeged, South-East Hungary. Systematic on-site measurements were carried out with a pair of special human-biometeorological stations on 20 clear summer days of 2015 in order to reveal the small-scale climate regulation potential of single trees in urban environment. Five healthy, mature trees were selected for the analysis, without the disturbing (additional shading) effect of any other trees or artificial objects. We compare separately the median values of the main thermal parameters – air temperature, relative humidity, as well as the short- and long-wave radiation components from the upper and lower hemisphere – measured under the canopy of the trees, and in the sun. Our results demonstrate that all of the five investigated tree specimens have significantly greater impact on the components of the radiation budget, while the modification of air temperature and humidity is rather small. Inter-species differences seem to be small in the warmest hours of the day, and may be attributed to the dimensional and canopy-characteristics. During the development of ecosystem service indicators it would be advisable to use integrated human-biometeorological indices which take into account all meteorological parameters that influence considerably human thermal comfort.

Topographic radiation modeling and spatial scaling of clear-sky land surface longwave radiation over rugged terrain

Abstract Longwave radiation (5–100 μm) is a critical component of the Earth's radiation budget. Most of the existing satellite-based retrieval algorithms are valid only for flat surfaces without accounting for topographic effects. This causes significant errors. Meanwhile, the fixed spatial resolution of remote sensing data makes it difficult to link the satellite-derived longwave radiation to different land models running on various scales. These deficiencies result in an urgent need for topographic modeling and spatial scaling studies of longwave radiation. In this paper, a longwave topographic radiation model (LWTRM) is proposed that quantifies all possible radiation-affecting factors over rugged terrain. For driving the LWTRM, a hybrid method for simultaneously deriving multiple components of longwave radiation from MODIS data is suggested based on artificial neuron networks (ANN) and the radiative transfer simulation. Topographically corrected longwave radiation is then derived by coupling the ANN outputs and LWTRM. Based on this, a general upscaling strategy for longwave radiation is presented. The results demonstrate that: (1) both the proposed LWTRM and the upscaling strategy are rather effective and work well over rugged areas; (2) the ANN-based retrieval method can produce longwave radiation with better accuracy(RMSE