Abstract Low clouds over tropical oceans reflect a great proportion of solar radiation back to space and thereby cool the Earth, yet this phenomenon has been poorly simulated in several previous generations of climate models. The principal aim of the present study is to employ satellite observations to evaluate the representation of marine tropical low clouds and their radiative effect at the top of the atmosphere in a subset of latest climate models participating in CMIP6. We strive for regime‐oriented model validation and hence introduce a qualitative approach to discriminate stratocumulus (Sc) from shallow cumulus (Cu). The novel Sc‐Cu categorization has a conceptual advantage of being based on cloud properties, rather than relying on a model response to a cloud‐controlling factor. We find that CMIP6 models underestimate low‐cloud cover in both Sc‐regions and Cu‐regions of tropical oceans. A more detailed investigation of cloud biases reveals that most CMIP6 models underestimate the relative frequency of occurrence (RFO) of Sc and overestimate RFO of Cu. We further demonstrate that tropical low cloudiness in CMIP6 models remains too bright. The regime‐oriented validation represents the basis for improving parameterizations of physical processes that determine the cloud cover and radiative impact of Sc and Cu, which are still misrepresented in current climate models.
Abstract An idealized, three‐dimensional, 1 km horizontal grid spacing numerical simulation of a rapidly intensifying tropical cyclone is used to extend basic knowledge on the role of mean and eddy momentum transfer on the dynamics of the intensification process. Examination of terms in the tangential and radial velocity tendency equations provides an improved quantitative understanding of the dynamics of the spin‐up process within the inner‐core boundary layer and eyewall regions of the system‐scale vortex. Unbalanced and non‐axisymmetric processes are prominent features of the rapid spin‐up process. In particular, the wind asymmetries, associated in part with the asymmetric deep convection, make a substantive contribution ( ∼ 30%) to the maximum wind speed inside the radius of this maximum. The analysis provides a novel explanation for inflow jets sandwiching the upper‐tropospheric outflow layer which are frequently found in numerical model simulations. In addition, it provides an opportunity to assess the applicability of generalized Ekman balance during rapid vortex spin‐up. The maximum tangential wind occurs within and near the top of the frictional inflow layer and as much as 10 km inside the maximum gradient wind. Spin‐up in the friction layer is accompanied by supergradient winds that exceed the gradient wind by up to 20%. Overall, the results affirm prior work pointing to significant limitations of a purely axisymmetric balance description, for example, gradient balance/Ekman balance, when applied to a rapidly intensifying tropical cyclone.
The aim of this work is to describe the features and to validate a simple, fast, accurate and physical-based spectral radiative transfer model in the solar wavelength range under clear skies. The model, named SSolar-GOA (the first "S" stands for "Spectral"), was developed to evaluate the instantaneous values of spectral solar irradiances at ground level. The model data output are well suited to work at a spectral resolution of 1–10 nm, are adapted to commercial spectroradiometers or filter radiometers, and are addressed to a wide community of users for many different applications (atmospheric and environmental research studies, remote sensing, solar energy, agronomy/forestry, ecology, etc.). The model requirements are designed based on the simplicity of the analytical expressions for the transmittance functions in order to be easily replicated and applied by users. Although spectral, the model runs quickly and has sufficient accuracy. The model assumes a single mixed molecule-aerosol scattering layer where the original Ambartsumian method of "adding layers" in a one-dimensional medium is applied, obtaining a parameterized expression for the total transmittance of scattering. Absorption by the different atmospheric gases follows "band model" parameterized expressions. Both processes are applied to a single atmospheric homogeneous layer as necessary approaches for developing a simple model under the consideration of non-interaction. Besides, the input parameters must be realistic and easily available since the spectral aerosol optical depth (AOD) is the main driver of the model. The validation of the SSolar-GOA model has been carried out through extensive comparison with simulated irradiance data from the LibRadtran package and with direct/global spectra measured by spectroradiometers. Thousands of spectra under clear skies have been compared for different atmospheric conditions and solar zenithal angles (SZA). From the results of the comparison with LibRadtran, the SSolar-GOA model shows a high performance for the entire solar spectral range for direct, global, and diffuse spectral components with relative differences of +1 %, +3 %, and 8 %, respectively, and our model always gives an underestimation. Compared with the measured irradiance data of the Licor1800 and ASD spectroradiometers, the relative differences of direct and global components are within the overall experimental error (about ±2–12 %) with underestimated or overestimated values. The diffuse component presents the highest degree of difference which can reach ±20–30 %. Obviously, the relative differences depend strongly on the spectral solar region analysed and the SZA. Model approach errors combined with calibration instrument errors may explain the observed differences.
Abstract. The interaction between radiation and clouds represents a source of uncertainty in numerical weather prediction (NWP) due to both intrinsic problems of one-dimensional radiation schemes and poor representation of clouds. The underlying question addressed in this study is how large the NWP radiative bias is for shallow cumulus clouds and how it scales with various input parameters of radiation schemes, such as solar zenith angle, surface albedo, cloud cover and liquid water path. A set of radiative transfer calculations was carried out for a realistically evolving shallow cumulus cloud field stemming from a large-eddy simulation (LES). The benchmark experiments were performed on the highly resolved LES cloud scenes (25 m grid spacing) using a three-dimensional Monte Carlo radiation model. An absence of middle and high clouds is assumed above the shallow cumulus cloud layer. In order to imitate the poor representation of shallow cumulus in NWP models, cloud optical properties were horizontally averaged over the cloudy part of the boxes with dimensions comparable to NWP horizontal grid spacing (several kilometers), and the common δ-Eddington two-stream method with maximum-random overlap assumption for partial cloudiness was applied (denoted as the “1-D” experiment). The bias of the 1-D experiment relative to the benchmark was investigated in the solar and thermal parts of the spectrum, examining the vertical profile of heating rate within the cloud layer and the net surface flux. It is found that, during daytime and nighttime, the destabilization of the cloud layer in the benchmark experiment is artificially enhanced by an overestimation of the cooling at cloud top and an overestimation of the warming at cloud bottom in the 1-D experiment (a bias of about −15 K d−1 is observed locally for stratocumulus scenarios). This destabilization, driven by the thermal radiation, is maximized during nighttime, since during daytime the solar radiation has a stabilizing tendency. The daytime bias at the surface is governed by the solar fluxes, where the 1-D solar net flux overestimates (underestimates) the corresponding benchmark at low (high) Sun. The overestimation at low Sun (bias up to 80 % over land and ocean) is largest at intermediate cloud cover, while the underestimation at high Sun (bias up to −40 % over land and ocean) peaks at larger cloud cover (80 % and beyond). At nighttime, the 1-D experiment overestimates the amount of benchmark surface cooling with the maximal bias of about 50 % peaked at intermediate cloud cover. Moreover, an additional experiment was carried out by running the Monte Carlo radiation model in the independent column mode on cloud scenes preserving their LES structure (denoted as the “ICA” experiment). The ICA is clearly more accurate than the 1-D experiment (with respect to the same benchmark). This highlights the importance of an improved representation of clouds even at the resolution of today's regional (limited-area) numerical models, which needs to be considered if NWP radiative biases are to be efficiently reduced. All in all, this paper provides a systematic documentation of NWP radiative biases, which is a necessary first step towards an improved treatment of radiation–cloud interaction in atmospheric models.
Motivated in part by a potential application to modelling tropical cyclones in the Australian region, mean radiosonde soundings are determined for the three northern Australian stations, Willis Island, Darwin and Weipa, during the core months of the cyclone season (December–February). More than 8500 individual soundings are examined in 30-year datasets for Willis Island and Darwin (1980–2010) and a 15-year dataset for Weipa (1998–2013). These soundings are stratified into three groups according to the low-level wind direction (monsoon regime, easterly flow regime and the rest). The mean soundings for the monsoon regime (low-level winds in the sector west to north) are compared at the three stations and diurnal differences are investigated at stations with two soundings per day. The mean monsoon Willis Island sounding is compared also with the Dunion moist tropical (MT) sounding, which is frequently used as an environmental sounding in the numerical modelling of tropical cyclones. The Willis Island sounding is 1–3 °C warmer and somewhat drier than the Dunion MT sounding through the entire troposphere, although the relative humidity differences are relatively small (less than 5% at most observed levels). Idealized numerical simulations of tropical cyclone evolution are performed to assess the implications of using one thermodynamic sounding or another for tropical cyclones in the Australian region. The simulations highlight the importance of not only the environmental sounding for the intensification of model storms, but also the sea surface temperature combined with the sounding.
<p>The project RESCCCUE aims at addressing the climate change action in Slovenia. We started the project in the autumn of 2019 when we have brought together over 100 leading Slovenian scientists, comprising meteorologists, climatologists, oceanographers, physicists, biologists, chemists, geographers, and others. Together we wrote an open letter to the Slovenian government: &#8220;A request of Slovenian researchers to take immediate action on improving the climate change mitigation and adaptation policy&#8221;. The open letter received extensive media coverage, as well as provoked a reaction from the political authorities and served as a kick-off for various subsequent climate change communication activities. We therefore continued with multiple media outreach and communication events, both jointly as a team and individually. This included appearances on the radio and television, interviews for newspapers and magazines, social media platforms, and popular scientific talks. We have thereby demonstrated that values such as a team spirit, mutual help and collaboration are crucial for far-reaching actions. All in all, the project strives to advance climate literacy and science-based policy making in Slovenia. Additionally, we also promote research in meteorology and climatology to the Slovenian youth (public talks for schools, summer schools, seminars). Although the project has already proved successful in igniting nationwide debate on&#160; climate mitigation, RESCCCUE is a continuing, ongoing project. We are currently establishing an online platform called &#8220;Podnebnik&#8221; that will track climate action in Slovenia and allow an exchange of science-based views on climate change mitigation and adaptation. To do this, we have established connections with data scientists behind the very successful Slovenian Covid-19 tracker &#8220;Sledilnik&#8221; (sledilnik.org), and many other Slovenian agencies from the relevant fields, as well as other Slovenian scientists from across the globe. We firmly believe that this platform will help decision makers and the general public to understand the diversity of the climate change challenge and take meaningful climate action. Throughout the project we have developed valuable skills and experience in scientific communication. We hope that our project will inspire more scientists to engage in communication of climate change science and in debates on societal impacts of climate change.</p>
Abstract. The interaction between radiation and clouds represents a source of uncertainty in numerical weather prediction (NWP) due to both intrinsic problems of one-dimensional radiation schemes and poor representation of clouds. The underlying question addressed in this study is how large is the NWP radiative bias for shallow cumulus clouds and how does it scale with various input parameters of radiation schemes, such as solar zenith angle, surface albedo, cloud cover and liquid water path. A set of radiative transfer calculations was carried out for a realistically evolving shallow cumulus cloud field stemming from a large-eddy simulation (LES). The benchmark experiments were performed on the highly-resolved LES cloud scenes using a three-dimensional Monte Carlo radiation model. An absence of middle and high cloud is assumed above the shallow cumulus cloud layer. In order to imitate poor representation of shallow cumulus in NWP models, cloud optical properties were horizontally averaged over the cloudy part of the boxes with dimensions comparable to NWP horizontal grid spacing (several km) and the common δ-Eddington two-stream method with maximum-random overlap assumption for partial cloudiness was applied (denoted as 1-D experiment). The bias of the 1-D experiment relative to the benchmark was investigated in the solar and thermal part of the spectrum, examining the vertical profile of heating rate within the cloud layer and net surface flux. It is found that during daytime and nighttime, the destabilization of the cloud layer in the benchmark experiment is artifically enhanced by an overestimation of the cooling at cloud top and an overestimation of the warming at cloud bottom in the 1-D experiment (bias of about −15 K day−1 is observed locally for stratocumulus scenarios). This destabilization, driven by the thermal radiation, is maximized during nighttime, since during daytime the solar radiation has a stabilizing tendency. The daytime bias at the surface is governed by the solar fluxes, where the 1-D solar net flux overestimates (underestimates) the corresponding benchmark at low (high) sun. The overestimation at low sun (bias up to 80 % over land and ocean) is largest at intermediate cloud cover, while underestimation at high sun (bias up to −40 % over land and ocean) is peaked at larger cloud cover (80 % and beyond). At nighttime, the 1-D experiment overestimates the amount of benchmark surface cooling with the maximal bias of about 50 % peaked at intermediate cloud cover. Moreover, an additional experiment was carried out by running the Monte Carlo radiation model in the independent column mode on cloud scenes preserving their LES structure (denoted as ICA experiment). The ICA is predominantly more accurate than the 1-D experiment (with respect to the same benchmark). This highlights the importance of an improved representation of clouds even at the resolution of today's regional (limited-area) numerical models, which needs to be considered if NWP radiative biases are to be efficiently reduced. All in all, this paper provides a systematic documentation of NWP radiative biases, which is a necessary first step towards an improved treatment of radiation–cloud interaction in atmospheric models.
The interaction between radiation and clouds represents a persistent source of uncertainty in numerical weather and climate prediction. Clouds are inherently complex meteorological phenomena, appearing in an immense variety of geometrical shapes and exhibiting highly variable degrees of heterogeneity. A physically consistent and computationally efficient coupling of three-dimensional cloud structures with the solar and thermal radiative field thereby remains one of the greatest challenges in the atmospheric science community. The present thesis aims to make progress towards an improved treatment of the unresolved cloud-radiation interchange for both regional and global modeling applications.
The first dissertation objective is to quantify the radiative bias in regional models for a realistically evolving shallow cumulus cloud field. The bias dependence on various input parameters of radiation schemes such as solar zenith angle, surface albedo, cloud cover and liquid water path is examined. Nighttime and daytime biases within the cloud-layer and at the surface are thoroughly investigated and evaluated against a high-resolution three-dimensional benchmark computation. The focus is laid on quantifying the regional-scale model bias arising from two chief shortcomings. First, the poor representation of unresolved cloudiness, which is normally approximated as a series of horizontally homogeneous partially cloudy layers. Second, the intrinsic constraint of one-dimensional radiation schemes, employing merely two streams for capturing the upward and downward radiative flux, but entirely neglecting the grid- and subgrid-scale horizontal photon flow. Since it is unclear which error source is dominant at the scale of regional modeling where these multiple issues intersect, the bias stemming from the latter drawback is simultaneously assessed. The principal findings highlight the importance of an improved cloud representation even at the regional scale.
The second dissertation objective is to advance the cloud-radiation interaction parameterization in coarse-resolution global models, focusing on the issues related to misrepresentation of cloud horizontal inhomogeneity. This subject is tackled with the state-of-the-art Tripleclouds radiative solver, the fundamental feature of which is the inclusion of the optically thicker and thinner cloud fraction. The research challenge is to optimally set the pair of cloud condensates characterizing the two cloudy regions and the corresponding geometrical split of layer cloudiness. A diverse cloud field data set was collected for the analysis, comprising case studies of cumulus, stratocumulus, cirrus and cumulonimbus. The primary goal is to test the validity of global cloud variability estimate along with various condensate distribution assumptions. More sophisticated parameterizations are subsequently explored, optimizing the treatment of overcast as well as extremely heterogeneous cloudiness. The radiative diagnostics including atmospheric heating rate and net surface flux are for the first time consistently studied using the Tripleclouds method. The performance of Tripleclouds mostly significantly surpasses the conventional calculation on horizontally homogeneous cloudiness. The effect of horizontal photon transport is further quantified. The overall conclusions are intrinsically different for each particular cloud type examined, encouraging endeavors to enhance the use of cloud regime dependent methodologies in next-generation atmospheric models.
The major technical effort undertaken within the scope of this work was the design of the classic two-stream radiation scheme supporting homogeneous partial cloudiness and its subsequent extension to incorporate the Tripleclouds concept. Both algorithms were implemented in the libRadtran radiative library, promoted to be utilized for further unraveling of key scientific mysteries related to cloud-radiation interplay.
