Solar radiation in the cloud-free atmosphere

2021 ◽  
Author(s):  
Martin Wild
Keyword(s):  
Solar Radiation ◽  
Climate Models ◽  
Climate Model ◽  
Temporal Changes ◽  
Climate System ◽  
Radiation Budget ◽  
Radiative Effects ◽  
Free Atmosphere ◽  
Surface Solar Radiation ◽  
Radiative Fluxes

<p>The quantification of Earth’s solar radiation budget and its temporal changes is essential for the understanding of the genesis and evolution of climate on our planet. While the solar radiative fluxes in and out of the climate system can be accurately tracked and quantified from space by satellite programs such as CERES or SORCE, the disposition of solar energy within in the climate system is afflicted with larger uncertainties. A better quantification of the solar radiative fluxes not only under cloudy, but also under cloud-free conditions can help to reduce these uncertainties and is essential for example for the determination of cloud radiative effects or for the understanding of  temporal changes in the solar radiative components of the climate system.</p> <p>We combined satellite observations of Top of Atmosphere fluxes with the information contained in surface flux observations and climate models to infer the absorption of solar radiation in the atmosphere, which we estimated at 73 Wm<sup>-2</sup> globally under cloud-free conditions (Wild et al. 2019 Clim Dyn). The latest generation of climate models participating in CMIP6 is now able to reproduce this magnitude surprisingly well, whereas in previous climate model  generations the cloud-free atmosphere was typically too transparent for solar radiation, which stated a long-standing modelling issue (Wild 2020 Clim Dyn, Wild et al. 1995 JClim).</p> <p>With respect to changes in solar fluxes, there is increasing evidence that the substantial long-term decadal variations in surface solar radiation known as dimming and brightening occur not only under all-sky, but similarly also under clear-sky conditions (Manara et al. 2016 ACP, Yang et al. 2019 JClim; Wild et al. 2021 GRL). This points to aerosol radiative effects as major factor for the explanation of this phenomenon.</p>

scholarly journals Spatial variability of the sea-ice radiation budget and its effect on aggregate-area fluxes

2001 ◽  
Vol 33 ◽  
pp. 248-252 ◽  
Author(s):  
Xuanji Wang ◽  
Jeffrey R. Key
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Radiative Properties ◽  
Radiation Budget ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Radiative Fluxes ◽  
Cloud Properties ◽  
Longwave Flux

AbstractThe spatial and temporal variability of surface, cloud and radiative properties of sea ice are examined using new satellite-derived products. Downwelling short- and longwave fluxes exhibit temporal correlation over about 180 days, but cloud optical depth and cloud fraction show almost no correlation over time. The spatial variance of surface properties is shown to increase much less rapidly than that of cloud properties. The effect of small-scale inhomogeneity in surface and cloud properties on the calculation of radiative fluxes at ice- and climate-model gridscales is also investigated. Annual mean differences between gridcell fluxes computed from average surface and cloud properties and averages of pixel-by-pixel fluxes are 9.46% for the downwelling shortwave flux and −7.04% for the longwave flux. Therefore, using mean surface and cloud properties to compute surface radiative fluxes in a gridcell results in an overestimate of the shortwave flux and an underestimate of the longwave flux. Model sensitivity studies show that such biases may result in substantial errors in modeled ice thickness. Clearly, the sub-gridscale inhomogeneity of surface and atmospheric properties must be considered when estimating aggregate-area fluxes in sea-ice and climate models.

scholarly journals Improving the simulation of global aerosol with size-segregated anthropogenic number emissions

2017 ◽  
Author(s):  
Filippo Xausa ◽  
Pauli Paasonen ◽  
Risto Makkonen ◽  
Mikhail Arshinov ◽  
Aijun Ding ◽  
...  
Keyword(s):  
Particle Number ◽  
Climate Models ◽  
Climate Model ◽  
Dominant Role ◽  
Particle Diameter ◽  
Radiation Budget ◽  
Size Distributions ◽  
Anthropogenic Aerosol ◽  
Accumulation Mode ◽  
Climate Interactions

Abstract. Climate models are important tools that are used for generating climate change projections, in which aerosol-climate interactions are one of the main sources of uncertainties. In order to quantify aerosol-radiation and aerosol-cloud interactions, detailed input of anthropogenic aerosol number emissions is necessary. However, the anthropogenic aerosol number emissions are usually converted from the corresponding mass emissions in precompiled emission inventories through a very simplistic method depending uniquely on chemical composition, particle size and density, which are defined for a few very wide main source sectors. In this work, the anthropogenic particle number emissions converted from the AeroCom mass in the ECHAM-HAM climate model were replaced with the recently-formulated number emissions from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS)-model, where the emission number size distributions vary, for example, with respect to the fuel and technology. A special attention in our analysis was put on accumulation mode particles (particle diameter dp > 100 nm) because of (i) their capability of acting as cloud condensation nuclei (CCN), thus forming cloud droplets and affecting Earth's radiation budget, and (ii) their dominant role in forming the coagulation sink and thus limiting the concentration of sub-100 nanometers particles. In addition, the estimates of anthropogenic CCN formation, and thus the forcing from aerosol-climate interactions are expected to be affected. Analysis of global particle number concentrations and size distributions reveal that GAINS implementation increases CCN concentration compared with AeroCom, with regional enhancement factors reaching values as high as 10. A comparison between modeled and observed concentrations shows that the increase in number concentration for accumulation mode particle agrees well with measurements, but it leads to a consistent underestimation of both nucleation mode and Aitken mode (dp > 100 nm) particle number concentrations. This suggests that revisions are needed in the new particle formation and growth schemes currently applied in global modeling frameworks.

scholarly journals A 16-year dataset (2000–2015) of high-resolution (3 h, 10 km) global surface solar radiation

2019 ◽  
Vol 11 (4) ◽  
pp. 1905-1915 ◽  
Author(s):  
Wenjun Tang ◽  
Kun Yang ◽  
Jun Qin ◽  
Xin Li ◽  
Xiaolei Niu
Keyword(s):  
High Resolution ◽  
Solar Radiation ◽  
Radiant Energy ◽  
Reanalysis Data ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Mean Bias Error ◽  
Bias Error ◽  
Surface Solar Radiation ◽  
Global Surface

Abstract. The recent release of the International Satellite Cloud Climatology Project (ISCCP) HXG cloud products and new ERA5 reanalysis data enabled us to produce a global surface solar radiation (SSR) dataset: a 16-year (2000–2015) high-resolution (3 h, 10 km) global SSR dataset using an improved physical parameterization scheme. The main inputs were cloud optical depth from ISCCP-HXG cloud products; the water vapor, surface pressure and ozone from ERA5 reanalysis data; and albedo and aerosol from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The estimated SSR data were evaluated against surface observations measured at 42 stations of the Baseline Surface Radiation Network (BSRN) and 90 radiation stations of the China Meteorological Administration (CMA). Validation against the BSRN data indicated that the mean bias error (MBE), root mean square error (RMSE) and correlation coefficient (R) for the instantaneous SSR estimates at 10 km scale were −11.5 W m−2, 113.5 W m−2 and 0.92, respectively. When the estimated instantaneous SSR data were upscaled to 90 km, its error was clearly reduced, with RMSE decreasing to 93.4 W m−2 and R increasing to 0.95. For daily SSR estimates at 90 km scale, the MBE, RMSE and R at the BSRN were −5.8 W m−2, 33.1 W m−2 and 0.95, respectively. These error metrics at the CMA radiation stations were 2.1 W m−2, 26.9 W m−2 and 0.95, respectively. Comparisons with other global satellite radiation products indicated that our SSR estimates were generally better than those of the ISCCP flux dataset (ISCCP-FD), the global energy and water cycle experiment surface radiation budget (GEWEX-SRB), and the Earth's Radiant Energy System (CERES). Our SSR dataset will contribute to the land-surface process simulations and the photovoltaic applications in the future. The dataset is available at  https://doi.org/10.11888/Meteoro.tpdc.270112 (Tang, 2019).

Changes in extreme surface solar radiation in EURO-CORDEX Regional Climate Models

2021 ◽  
Author(s):  
Blanka Bartok
Keyword(s):  
Climate Change ◽  
Power Generation ◽  
Solar Radiation ◽  
Solar Energy ◽  
Electricity Generation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Surface Solar Radiation ◽  
The Impact

<p>As solar energy share is showing a significant growth in the European electricity generation system, assessments regarding long-term variation of this variable related to climate change are becoming more and more relevant for this sector. Several studies analysed the impact of climate change on the solar energy sector in Europe (Jerez et al, 2015) finding light impact (-14%; +2%) in terms of mean surface solar radiation. The present study focuses on extreme values, namely on the distribution of low surface solar radiation (overcast situation) and high surface solar radiation (clear sky situation), since the frequencies of these situations have high impact on electricity generation.</p><p>The study considers 11 high-resolution (0.11 deg) bias-corrected climate projections from the EURO-CORDEX ensemble with 5 Global Climate Models (GCMs) downscaled by 6 Regional Climate Models (RCMs).</p><p>Changes in extreme surface solar radiation frequencies show different regional patterns over Europe.</p><p>The study also includes a case study determining the changes in solar power generation induced by the extreme situations.</p><p> </p><p> </p><p>Jerez et al (2015): The impact of climate change on photovoltaic power generation in Europe, Nature Communications 6(1):10014, 10.1038/ncomms10014</p><p> </p>

scholarly journals Influence of parallel computational uncertainty on simulations of the Coupled General Climate Model

2012 ◽  
Vol 5 (2) ◽  
pp. 313-319 ◽  
Author(s):  
Z. Song ◽  
F. Qiao ◽  
X. Lei ◽  
C. Wang
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Quality Standard ◽  
Ensemble Member ◽  
Climate System ◽  
Climate System Model ◽  
Climate Simulations ◽  
Computational Uncertainty ◽  
The Impact ◽  
General Climate

Abstract. This paper investigates the impact of the parallel computational uncertainty due to the round-off error on climate simulations using the Community Climate System Model Version 3 (CCSM3). A series of sensitivity experiments have been conducted and the analyses are focused on the Global and Nino3.4 average sea surface temperatures (SST). For the monthly time series, it is shown that the amplitude of the deviation induced by the parallel computational uncertainty is the same order as that of the climate system change. However, the ensemble mean method can reduce the influence and the ensemble member number of 15 is enough to ignore the uncertainty. For climatology, the influence can be ignored when the climatological mean is calculated by using more than 30-yr simulations. It is also found that the parallel computational uncertainty has no distinguishable effect on power spectrum analysis of climate variability such as ENSO. Finally, it is suggested that the influence of the parallel computational uncertainty on Coupled General Climate Models (CGCMs) can be a quality standard or a metric for developing CGCMs.

Numerical simulation of surface solar radiation over Southern Africa. Part 1: Evaluation of regional and global climate models

2018 ◽  
Vol 52 (1-2) ◽  
pp. 457-477 ◽  
Author(s):  
Chao Tang ◽  
Béatrice Morel ◽  
Martin Wild ◽  
Benjamin Pohl ◽  
Babatunde Abiodun ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Solar Radiation ◽  
Southern Africa ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Surface Solar Radiation

scholarly journals Climate model attractors: chaos, quasi-regularity and sensitivity to small perturbations of external forcing

2001 ◽  
Vol 8 (4/5) ◽  
pp. 201-209 ◽  
Author(s):  
V. P. Dymnikov ◽  
A. S. Gritsoun
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Attractors ◽  
Atmospheric Model ◽  
Climate System ◽  
External Forcing ◽  
Attractor Dimension ◽  
Small Perturbations ◽  
System Sensitivity ◽  
Fluctuation Dissipation

Abstract. In this paper we discuss some theoretical results obtained for climate models (theorems for the existence of global attractors and inertial manifolds, estimates of attractor dimension and Lyapunov exponents, symmetry property of Lyapunov spectrum). We define the conditions for "quasi-regular behaviour" of a climate system. Under these conditions, the system behaviour is subject to the Kraichnan fluctuation-dissipation relation. This fact allows us to solve the problem of determining a system's sensitivity to small perturbations to an external forcing. The applicability of the above approach to the analysis of the climate system sensitivity is verified numerically with the example of the two-layer quasi-geostrophic atmospheric model.

scholarly journals Evaluating Climate Model Simulations of the Radiative Forcing and Radiative Response at Earth’s Surface

2019 ◽  
Vol 32 (13) ◽  
pp. 4089-4102 ◽  
Author(s):  
Ryan J. Kramer ◽  
Brian J. Soden ◽  
Angeline G. Pendergrass
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Lapse Rate ◽  
Radiation Budget ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract We analyze the radiative forcing and radiative response at Earth’s surface, where perturbations in the radiation budget regulate the atmospheric hydrological cycle. By applying a radiative kernel-regression technique to CMIP5 climate model simulations where CO2 is instantaneously quadrupled, we evaluate the intermodel spread in surface instantaneous radiative forcing, radiative adjustments to this forcing, and radiative responses to surface warming. The cloud radiative adjustment to CO2 forcing and the temperature-mediated cloud radiative response exhibit significant intermodel spread. In contrast to its counterpart at the top of the atmosphere, the temperature-mediated cloud radiative response at the surface is found to be positive in some models and negative in others. Also, the compensation between the temperature-mediated lapse rate and water vapor radiative responses found in top-of-atmosphere calculations is not present for surface radiative flux changes. Instantaneous radiative forcing at the surface is rarely reported for model simulations; as a result, intermodel differences have not previously been evaluated in global climate models. We demonstrate that the instantaneous radiative forcing is the largest contributor to intermodel spread in effective radiative forcing at the surface. We also find evidence of differences in radiative parameterizations in current models and argue that this is a significant, but largely overlooked, source of bias in climate change simulations.

scholarly journals Assessing the Surface Solar Radiation Budget in the WRF Model: A Spatiotemporal Analysis of the Bias and Its Causes

2016 ◽  
Vol 144 (2) ◽  
pp. 703-711 ◽  
Author(s):  
José A. Ruiz-Arias ◽  
Clara Arbizu-Barrena ◽  
Francisco J. Santos-Alamillos ◽  
Joaquín Tovar-Pescador ◽  
David Pozo-Vázquez
Keyword(s):  
Solar Radiation ◽  
Wrf Model ◽  
Cloud Amount ◽  
Principal Component ◽  
Spatiotemporal Analysis ◽  
Radiation Budget ◽  
Weather Research And Forecasting ◽  
Total Solar Radiation ◽  
Surface Solar Radiation ◽  
Solar Radiation Flux

Abstract Solar radiation plays a key role in the atmospheric system but its distribution throughout the atmosphere and at the surface is still very uncertain in atmospheric models, and further assessment is required. In this study, the shortwave downward total solar radiation flux (SWD) predicted by the Weather Research and Forecasting (WRF) Model at the surface is validated over Spain for a 10-yr period based on observations of a network of 52 radiometric stations. In addition to the traditional pointwise validation of modeled data, an original spatially continuous evaluation of the SWD bias is also conducted using a principal component analysis. Overall, WRF overestimates the mean observed SWD by 28.9 W m−2, while the bias of ERA-Interim, which provides initial and boundary conditions to WRF, is only 15.0 W m−2. An important part of the WRF SWD bias seems to be related to a very low cumulus cloud amount in the model and, possibly, a misrepresentation of the radiative impact of this type of cloud.

scholarly journals On the ability of RegCM4 regional climate model to simulate surface solar radiation patterns over Europe: an assessment using satellite-based observations

2015 ◽  
Vol 15 (22) ◽  
pp. 13195-13216 ◽  
Author(s):  
G. Alexandri ◽  
A. K. Georgoulias ◽  
P. Zanis ◽  
E. Katragkou ◽  
A. Tsikerdekis ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiative Transfer Model ◽  
Asymmetry Factor ◽  
Transfer Model ◽  
Potential Contribution ◽  
Absolute Deviation ◽  
Surface Solar Radiation

Abstract. In this work, we assess the ability of RegCM4 regional climate model to simulate surface solar radiation (SSR) patterns over Europe. A decadal RegCM4 run (2000–2009) was implemented and evaluated against satellite-based observations from the Satellite Application Facility on Climate Monitoring (CM SAF), showing that the model simulates adequately the SSR patterns over the region. The SSR bias between RegCM4 and CM SAF is +1.5 % for MFG (Meteosat First Generation) and +3.3 % for MSG (Meteosat Second Generation) observations. The relative contribution of parameters that determine the transmission of solar radiation within the atmosphere to the deviation appearing between RegCM4 and CM SAF SSR is also examined. Cloud macrophysical and microphysical properties such as cloud fractional cover (CFC), cloud optical thickness (COT) and cloud effective radius (Re) from RegCM4 are evaluated against data from CM SAF. Generally, RegCM4 underestimates CFC by 24.3 % and Re for liquid/ice clouds by 36.1 %/28.3 % and overestimates COT by 4.3 %. The same procedure is repeated for aerosol optical properties such as aerosol optical depth (AOD), asymmetry factor (ASY) and single-scattering albedo (SSA), as well as other parameters, including surface broadband albedo (ALB) and water vapor amount (WV), using data from MACv1 aerosol climatology, from CERES satellite sensors and from ERA-Interim reanalysis. It is shown here that the good agreement between RegCM4 and satellite-based SSR observations can be partially attributed to counteracting effects among the above mentioned parameters. The potential contribution of each parameter to the RegCM4–CM SAF SSR deviations is estimated with the combined use of the aforementioned data and a radiative transfer model (SBDART). CFC, COT and AOD are the major determinants of these deviations on a monthly basis; however, the other parameters also play an important role for specific regions and seasons. Overall, for the European domain, CFC, COT and AOD are the most important factors, since their underestimations and overestimations by RegCM4 cause an annual RegCM4–CM SAF SSR absolute deviation of 8.4, 3.8 and 4.5 %, respectively.

Sign in / Sign up

Export Citation Format

Share Document