scholarly journals Deployment of the C-band radar Poldirad on Barbados during EUREC<sup>4</sup>A

2021 ◽  
Author(s):  
Martin Hagen ◽  
Florian Ewald ◽  
Silke Groß ◽  
Lothar Oswald ◽  
David A. Farrell ◽  
...  
Keyword(s):  
Rain Rate ◽  
Radar Signal ◽  
Trade Wind ◽  
Cumulus Clouds ◽  
Radar Images ◽  
Shallow Cumulus ◽  
Maximum Range ◽  
Research Aircraft ◽  
Radar Measurements

Abstract. The German polarimetric C-band weather radar Poldirad (Polarization Diversity Radar) was deployed for the international field campaign EUREC4A (ElUcidating the RolE of Cloud-Circulation Coupling in ClimAte) on the island of Barbados. Poldirad was operated on Barbados from February until August 2020. Focus of the installation was monitoring clouds and precipitation in the trade wind region east of Barbados. Different scanning modes were used with a temporal sequence of 5 minutes and a maximum range of 375 km. In addition to built-in quality control performed by the radar signal processor, it was found that the copoloar correlation coefficient ρHV can be used to remove contamination of radar products by sea clutter. Radar images were available in real-time for all campaign participants and onboard of research aircraft. Examples of mesoscale precipitation patterns, rain rate accumulation, diurnal cycle, and vertical distribution are given to show the potential of the radar measurements for further studies on the life cycle of precipitating shallow cumulus clouds and other related aspects. Poldirad data from the EUREC4A campaign are available on the EUREC4A AERIS database: https://doi.org/10.25326/218 (Hagen et al., 2021a) for raw data and https://doi.org/10.25326/217 (Hagen et al., 2021b) for gridded data.

scholarly journals Deployment of the C-band radar Poldirad on Barbados during EUREC<sup>4</sup>A

2021 ◽  
Vol 13 (12) ◽  
pp. 5899-5914
Author(s):  
Martin Hagen ◽  
Florian Ewald ◽  
Silke Groß ◽  
Lothar Oswald ◽  
David A. Farrell ◽  
...  
Keyword(s):  
Rain Rate ◽  
Radar Signal ◽  
Trade Wind ◽  
Cumulus Clouds ◽  
Radar Images ◽  
Shallow Cumulus ◽  
Maximum Range ◽  
Research Aircraft ◽  
Radar Measurements

Abstract. The German polarimetric C-band weather radar Poldirad (Polarization Diversity Radar) was deployed for the international field campaign EUREC4A (Elucidating the role of clouds–circulation coupling in climate) on the island of Barbados where it was operated from February until August 2020. Focus of the installation was monitoring clouds and precipitation in the trade wind region east of Barbados. Different scanning modes were used with a temporal sequence of 5 min and a maximum range of 375 km. In addition to built-in quality control performed by the radar signal processor, it was found that the copoloar correlation coefficient ρHV can be used to remove contamination of radar products by sea clutter. Radar images were available in real time for all campaign participants and aboard research aircraft. Examples of mesoscale precipitation patterns, rain rate accumulation, diurnal cycle, and vertical distribution are given to show the potential of the radar measurements for further studies on the life cycle of precipitating shallow cumulus clouds and other related aspects. Poldirad data from the EUREC4A campaign are available on the EUREC4A AERIS database: https://doi.org/10.25326/218 (Hagen et al., 2021a) for raw data and https://doi.org/10.25326/217 (Hagen et al., 2021b) for gridded data.

scholarly journals The Role of Unresolved Clouds on Short-Range Global Horizontal Irradiance Predictability

2016 ◽  
Vol 144 (9) ◽  
pp. 3099-3107 ◽  
Author(s):  
Pedro A. Jiménez ◽  
Stefano Alessandrini ◽  
Sue Ellen Haupt ◽  
Aijun Deng ◽  
Branko Kosovic ◽  
...  
Keyword(s):  
Model Uncertainty ◽  
Short Range ◽  
Solar Model ◽  
Cumulus Clouds ◽  
High Quality ◽  
Ensemble Simulations ◽  
Shallow Cumulus ◽  
Implicit Model ◽  
Radiative Impacts

The shortwave radiative impacts of unresolved cumulus clouds are investigated using 6-h ensemble simulations performed with the WRF-Solar Model and high-quality observations over the contiguous United States for a 1-yr period. The ensembles use the stochastic kinetic energy backscatter scheme (SKEBS) to account for implicit model uncertainty. Results indicate that parameterizing the radiative effects of both deep and shallow cumulus clouds is necessary to largely reduce (55%) a systematic overprediction of the global horizontal irradiance. Accounting for the model’s effective resolution is necessary to mitigate the underdispersive nature of the ensemble and provide meaningful quantification of the short-range prediction uncertainties.

scholarly journals Multilayer cloud conditions in trade wind shallow cumulus – confronting two ICON model derivatives with airborne observations

2020 ◽  
Vol 13 (11) ◽  
pp. 5757-5777
Author(s):  
Marek Jacob ◽  
Pavlos Kollias ◽  
Felix Ament ◽  
Vera Schemann ◽  
Susanne Crewell
Keyword(s):  
Sea Level ◽  
Liquid Water ◽  
Winter Season ◽  
Radar Signal ◽  
Trade Wind ◽  
Moist Convection ◽  
Cloud Detection ◽  
Lower Mode ◽  
Radar Observations ◽  
Shallow Cumulus

Abstract. Airborne remote sensing observations over the tropical Atlantic Ocean upstream of Barbados are used to characterize trade wind shallow cumulus clouds and to benchmark two cloud-resolving ICON (ICOsahedral Nonhydrostatic) model simulations at kilometer and hectometer scales. The clouds were observed by an airborne nadir-pointing backscatter lidar, a cloud radar, and a microwave radiometer in the tropical dry winter season during daytime. For the model benchmark, forward operators convert the model output into the observational space for considering instrument-specific cloud detection thresholds. The forward simulations reveal the different detection limits of the lidar and radar observations, i.e., most clouds with cloud liquid water content greater than 10−7 kg kg−1 are detectable by the lidar, whereas the radar is primarily sensitive to the “rain” category hydrometeors in the models and can detect even low amounts of rain. The observations reveal two prominent modes of cumulus cloud top heights separating the clouds into two layers. The lower mode relates to boundary layer convection with tops closely above the lifting condensation level, which is at about 700 m above sea level. The upper mode is driven by shallow moist convection, also contains shallow stratiform outflow anvils, and is closely related to the trade inversion at about 2.3 km above sea level. The two cumulus modes are sensed differently by the lidar and the radar observations and under different liquid water path (LWP) conditions. The storm-resolving model (SRM) at a kilometer scale barely reproduces the cloud modes and shows most cloud tops being slightly above the observed lower mode. The large-eddy model (LEM) at hectometer scale reproduces better the observed cloudiness distribution with a clear bimodal separation. We hypothesize that slight differences in the autoconversion parameterizations could have caused the different cloud development in the models. Neither model seems to account for in-cloud drizzle particles that do not precipitate down to the surface but generate a stronger radar signal even in scenes with low LWP. Our findings suggest that even if the SRM is a step forward for better cloud representation in climate research, the LEM can better reproduce the observed shallow cumulus convection and should therefore in principle better represent cloud radiative effects and water cycle.

scholarly journals On the imprint of the mesoscale organization of tradewind clouds at cloud base and below

2021 ◽  
Author(s):  
Sandrine Bony ◽  
Pierre-Etienne Brilouet ◽  
Patrick Chazette ◽  
Pierre Coutris ◽  
Julien Delanoë ◽  
...  
Keyword(s):  
Large Scale ◽  
Lower Troposphere ◽  
Cloud Base ◽  
Trade Wind ◽  
Tropical Atlantic ◽  
Lidar Measurements ◽  
Research Aircraft ◽  
Cloud Patterns

&lt;p&gt;&lt;span&gt;Trade-wind clouds &lt;/span&gt;&lt;span&gt;can &lt;/span&gt;&lt;span&gt;exhibit &lt;/span&gt;&lt;span&gt;different&lt;/span&gt;&lt;span&gt; patterns of mesoscale organization. These patterns were observed during the EUREC&lt;/span&gt;&lt;sup&gt;&lt;span&gt;4&lt;/span&gt;&lt;/sup&gt;&lt;span&gt;A &lt;/span&gt;&lt;span&gt;(Elucidating the role of cloud-circulation coupling in climate) &lt;/span&gt;&lt;span&gt;field campaign that took place in Jan-Feb 2020 over the western tropical Atlantic near Barbados: &lt;/span&gt;&lt;span&gt;w&lt;/span&gt;&lt;span&gt;hile the HALO aircraft &lt;/span&gt;&lt;span&gt;was observing clouds from&lt;/span&gt; &lt;span&gt;above&lt;/span&gt;&lt;span&gt; and &lt;/span&gt;&lt;span&gt;was &lt;/span&gt;&lt;span&gt;characteri&lt;/span&gt;&lt;span&gt;z&lt;/span&gt;&lt;span&gt;ing&lt;/span&gt; &lt;span&gt;the &lt;/span&gt;&lt;span&gt;large-scale&lt;/span&gt;&lt;span&gt; environment&lt;/span&gt; &lt;span&gt;with&lt;/span&gt;&lt;span&gt; dropsondes&lt;/span&gt;&lt;span&gt;, the ATR-42 research aircraft was flying &lt;/span&gt;&lt;span&gt;in&lt;/span&gt;&lt;span&gt; the &lt;/span&gt;&lt;span&gt;lower troposphere&lt;/span&gt;&lt;span&gt;,&lt;/span&gt; &lt;span&gt;characteriz&lt;/span&gt;&lt;span&gt;ing&lt;/span&gt;&lt;span&gt; cloud&lt;/span&gt;&lt;span&gt;s &lt;/span&gt;&lt;span&gt;and turbulence &lt;/span&gt;&lt;span&gt;with horizontal radar-lidar measurements and in-situ &lt;/span&gt;&lt;span&gt;probes and &lt;/span&gt;&lt;span&gt;sensors&lt;/span&gt;&lt;span&gt;. &lt;/span&gt;&lt;span&gt;By&lt;/span&gt;&lt;span&gt; analyz&lt;/span&gt;&lt;span&gt;ing&lt;/span&gt; &lt;span&gt;these data &lt;/span&gt;&lt;span&gt;for different cloud patterns&lt;/span&gt;&lt;span&gt;, &lt;/span&gt;&lt;span&gt;we&lt;/span&gt; &lt;span&gt;investigate the &lt;/span&gt;&lt;span&gt;extent to which the &lt;/span&gt;&lt;span&gt;cloud&lt;/span&gt;&lt;span&gt; organization &lt;/span&gt;&lt;span&gt;i&lt;/span&gt;&lt;span&gt;s imprinted &lt;/span&gt;&lt;span&gt;in&lt;/span&gt;&lt;span&gt; cloud-base &lt;/span&gt;&lt;span&gt;properties &lt;/span&gt;&lt;span&gt;and&lt;/span&gt;&lt;span&gt; subcloud-layer &lt;/span&gt;&lt;span&gt;heterogeneities&lt;/span&gt;&lt;span&gt;. &lt;/span&gt;&lt;span&gt;The implications of our findings for understanding the roots of the mesoscale organization &lt;/span&gt;&lt;span&gt;of tradewind clouds&lt;/span&gt;&lt;span&gt; will be discussed.&lt;/span&gt;&lt;/p&gt;

Large-scale vertical motion and its influence on cloudiness

2020 ◽  
Author(s):  
Geet George ◽  
Bjorn Stevens ◽  
Sandrine Bony ◽  
Marcus Klingebiel
Keyword(s):  
Large Scale ◽  
Vertical Motion ◽  
Cumulus Clouds ◽  
Shallow Cumulus ◽  
Integrated Water Vapour ◽  
Thermodynamics And Dynamics ◽  
Lifting Condensation Level ◽  
The Impact ◽  
First Time

&lt;p&gt;This study uses measurements from the &lt;em&gt;Elucidating the Role of Clouds-Circulation Coupling in Climate&lt;/em&gt;, EUREC&lt;sup&gt;4&lt;/sup&gt;A and the second &lt;em&gt;Next-Generation Aircraft Remote Sensing for Validation&lt;/em&gt;, NARVAL2 campaigns to investigate the influence of large-scale environmental conditions on cloudiness. For the first time, these campaigns provide divergence measurements, making it possible to explore the impact of large-scale vertical motions on clouds. We attempt to explain the cloudiness through the varying thermodynamics and dynamics in the different environments.&amp;#160; For most of the NARVAL2 case-studies, cloudiness is poorly related to thermodynamical factors such as sea-surface temperature and lower tropospheric stability. Factors such as integrated water vapour and pressure velocity (&amp;#969;) at 500 hPa and 700 hPa can be used to distinguish between actively convecting and suppressed regions, but they are not useful in determining the variation in cloudiness among suppressed cases. We find that &amp;#969; in the boundary layer (up to &amp;#8764;2 km) has a more direct control on the low-level cloudiness in these regions, than that in the upper layers. We use a simplistic method to show that &amp;#969; at the lifting condensation level can be used to determine the cloud cover of shallow cumulus clouds. Thus, we argue that cloud schemes in models should not rely only on thermodynamical information, but also on dynamical predictors.&lt;/p&gt;

scholarly journals Multi-layer Cloud Conditions in Trade Wind Shallow Cumulus – Confronting Models with Airborne Observations

2020 ◽  
Author(s):  
Marek Jacob ◽  
Pavlos Kollias ◽  
Felix Ament ◽  
Vera Schemann ◽  
Susanne Crewell
Keyword(s):  
Sea Level ◽  
Liquid Water ◽  
Winter Season ◽  
Radar Signal ◽  
Trade Wind ◽  
Moist Convection ◽  
Cloud Detection ◽  
Lower Mode ◽  
Radar Observations ◽  
Shallow Cumulus

Abstract. Airborne remote sensing observations over the tropical Atlantic Ocean upstream of Barbados are used to characterize trade wind shallow cumulus clouds and to benchmark two cloud-resolving ICON (ICOsahedral Nonhydrostatic) model simulations at kilo- and hectometer scales. The clouds were observed by an airborne nadir pointing backscatter lidar, a cloud radar, and a microwave radiometer in the tropical dry winter season during daytime. For the model benchmark, forward operators convert the model data into the observational space for considering instrument specific cloud detection thresholds. The forward simulations reveal the different detection limits of the lidar and radar observations, i.e., most clouds with cloud liquid water content greater than 10−7 kg/kg are detectable by the lidar, whereas the radar is primarily sensitive to the rain-category hydrometeors in the models and can detect even low amounts of rain. The observations reveal two prominent modes of cumulus cloud top heights separating the clouds into two layers. The lower mode relates to boundary layer convection with tops closely above the lifted condensation level, which is at about 700 m above sea level. The upper mode is driven by shallow moist convection, also contains shallow outflow anvils, and is closely related to the trade inversion at about 2.3 km above sea level. The two cumulus modes are reflected differently by the lidar and the radar observations and under different liquid water path (LWP) conditions. The storm-resolving model (SRM) at kilometer scale reproduces the cloud modes barely and shows the most cloud tops slightly above the observed lower mode. The large-eddy model (LEM) at hectometer scale reproduces better the observed cloudiness distribution with a clear bimodal separation. We hypothesize that slight differences in the autoconversion parametrizations could have caused the different cloud development in the models. Neither model seems to account for in-cloud drizzle particles that do not precipitate down to the surface but generate a stronger radar signal even in scenes with low LWP. Our findings suggest that even if the SRM is a step forward for better cloud representation in climate research, the LEM can better reproduce the observed shallow cumulus convection and should therefore in principle represent cloud radiative effects and water cycle better.

scholarly journals Horizontal geometry of trade-wind cumuli – aircraft observations from shortwave infrared imager versus radar profiler

2021 ◽  
Author(s):  
Henning Dorff ◽  
Heike Konow ◽  
Felix Ament
Keyword(s):  
High Resolution ◽  
Size Distribution ◽  
Wind Field ◽  
Trade Wind ◽  
Size Spectrum ◽  
Lower Sensitivity ◽  
Cumulus Clouds ◽  
Research Aircraft ◽  
Shortwave Infrared ◽  
Along Track

Abstract. This study elaborates how aircraft-based horizontal geometries of trade-wind cumulus clouds differ whether a one-dimensional (1D) profiler or a two-dimensional (2D) imager is used. While nadir profiling devices are limited to 1D realisation of the cloud transect size with limited representativeness of horizontal cloud extension, 2D imagers enhance our perspectives by mapping the horizontal cloud field. Both require high-resolution to detect the lower end of the cloud size spectrum. In this regard, the payload aboard the High Altitude and Long Range Research Aircraft (HALO) achieves a comparison and also a synergy of both measurement systems. Using the NARVAL-II campaign, we combine HALO observations from a 35.2 GHz cloud and precipitation radar (1D) and from the hyperspectral 2D imager specMACS, having a 30 times higher along-track resolution and compare their cloud masks. We examine cloud size distributions in terms of sensitivity to sample size, resolution and the considered field of view (2D or 1D). This specifies impacts on horizontal cloud sizes derived from the across-track perspective of the high-resolution imager in comparison to the radar curtain. We assess whether and how the trade-wind field amplifies uncertainties in cloud geometry observations along 1D transects through directional cloud elongation. Our findings reveal that each additional dimension, no matter of the device, causes a significant increase of observed clouds. The across-track field yields the highest increase in the cloud sample. The radar encounters difficulties to characterize the trade-wind cumuli size distribution. More than 60 % of clouds are subgrid scale for the radar. While the radar cannot resolve clouds shorter than 200 m and has a lower sensitivity, the amount of small invisible clouds leads to deviations in the size distribution. Double power law characteristics in the imager based cloud size distribution do not occur in radar observations. Along-track measurements do not necessarily cover the predominant cloud extent and inferred geometries lack of representativeness. Trade-wind cumuli show horizontal patterns similar to ellipses with a mean aspect ratio of 3 : 2. Instead of circular estimations based on the 1D transect, elliptic fits maintain the cloud area size distribution. Increasing wind speed tends to stretch clouds more and tilts them into the wind field, which makes transect measurements more representative along this axis.

Simulating the synergy of microwave radiometer and differential absorption radar for advancing water vapor profiling in cloudy trade-wind conditions

2021 ◽  
Author(s):  
Sabrina Schnitt ◽  
Ulrich Löhnert ◽  
René Preusker
Keyword(s):  
Water Vapor ◽  
Information Content ◽  
Microwave Radiometer ◽  
Cloud Layer ◽  
Radar Signal ◽  
Trade Wind ◽  
Dual Frequency ◽  
Differential Absorption ◽  
Radar Measurements ◽  
Retrieval Errors

&lt;p&gt;Continuous, high vertical resolution water vapor profile measurements are key for advancing the understanding of how clouds interact with their environment through convection, precipitation and circulation processes.&amp;#160; Yet, current ground-based observation systems are limited by low temporal resolution in the case of soundings, signal saturation at cloud base in the case of optical sensors, or too coarse vertical resolution in the case of passive microwave measurements. Overcoming the limitations of each single sensor, we assess the synergistic benefits of combining ground-based microwave radiometer (MWR) and the novel Differential Absorption Radar technique, based on synthetic measurements generated for typical trade wind conditions as observed during the EUREC&lt;sup&gt;4&lt;/sup&gt;A field study.&lt;/p&gt;&lt;p&gt;Based on the single and multiple cloud layer conditions observed at Barbados Cloud Observatory, we use the passive and active microwave transfer model PAMTRA to generate synthetic measurements of the K-band MWR channels, as well as for a G-band dual-frequency radar instrument operating at frequencies of 167 and 174.8 GHz.&amp;#160; The synthetic brightness temperatures and radar dual-frequency ratios are combined in an optimal estimation framework to retrieve the absolute humidity profile. Varying the observation vector setup, the synergy benefits are assessed by comparing the synergistic information content (Degrees of Freedom for Signal, DFS) and retrieval errors to the respective single-instrument configuration, and by evaluating the retrieved profile using the initial sounding profile.&lt;/p&gt;&lt;p&gt;In single-cloud conditions, the total synergistic retrieval information content increases by more than one DFS compared to a MWR-only retrieval. While the radar measurements dominate the retrieval below and throughout the cloud layer, the MWR drives the retrieval above the cloud layer. The synergy further enhances the information content above the cloud layer by up to 15% compared to the MWR-only retrieval, accompanied by decreased retrieval errors of up to 10%. Cases of a shallow cloud layer topped by a stratiform outflow confirm the identified patterns. The radar measurements further increase the information content between the cloud layers by up to 25%. In this case, the results suggest an improved partitioning of the water vapor amount below and above the trade inversion.&amp;#160;&lt;/p&gt;&lt;p&gt;Current G-band radar signal attenuation in moist tropical conditions are expected to reduce the feasible synergy potential in a real application. Yet, increased radar signal sensitivities, adjusted frequency pairs, or drier atmospheric conditions motivate the application of this synergy concept to real measurements for advancing ground-based water vapor profiling in cloudy conditions.&lt;/p&gt;

scholarly journals Shallow Cumulus Mixing and Subcloud-Layer Responses to Variations in Aerosol Loading

2014 ◽  
Vol 71 (7) ◽  
pp. 2581-2603 ◽  
Author(s):  
Robert B. Seigel
Keyword(s):  
Potential Temperature ◽  
Domain Size ◽  
Aerosol Concentration ◽  
Trade Wind ◽  
Cold Pool ◽  
Cumulus Clouds ◽  
Core Mass ◽  
Shallow Cumulus ◽  
Rise Rate ◽  
Cloud Cores

Abstract The sensitivity of lightly precipitating trade wind shallow cumulus to both aerosol concentration and domain size is investigated using large-eddy simulations (LESs). The mean states of liquid water potential temperature, total water, and velocity field exhibit negligible change between all LES runs, offering the perfect opportunity to investigate microphysical–dynamical interactions solely due to variations in aerosol concentration and not changes in meteorology. As aerosol concentration increases, two cloud population responses are found: 1) cloud and cloud-core widths decrease while their strength increases and 2) cloud and core numbers increase. The narrowing of the polluted clouds is caused by enhanced evaporation rates surrounding the cloud cores, which in turn shrinks the diameter of the cumulus toroidal circulation. The more narrow toroidal circulation in polluted clouds has a faster rise rate and imparts weaker dynamical entrainment on the cloud cores, resulting in stronger clouds as aerosol concentration increases. The reduction in cloud number for more pristine conditions occurs from greater cold pool coverage, reducing the likelihood of subcloud-layer thermals reaching their lifting condensation level. The increase in cloud number as aerosol concentration increases is compensated by narrower and stronger clouds, resulting in a cumulus-core mass flux that appears to be unaffected by aerosol concentration variability. For the weakly precipitating case studied here, the trends in the response of the cumulus clouds to aerosol concentration are found to be insensitive to domain size.

scholarly journals Cloud Droplet Growth in Shallow Cumulus Clouds Considering 1D and 3D Thermal Radiative Effects

2018 ◽  
Author(s):  
Carolin Klinger ◽  
Graham Feingold ◽  
Takanobu Yamaguchi
Keyword(s):  
Thermal Radiation ◽  
Rain Rate ◽  
Cloud Droplet ◽  
Large Eddy Simulations ◽  
Droplet Growth ◽  
Radiative Effects ◽  
Cumulus Clouds ◽  
Shallow Cumulus ◽  
Large Eddy ◽  
Thermal Cooling

Abstract. The effect of 1D and 3D thermal radiation on cloud droplet growth in shallow cumulus clouds is investigated using large eddy simulations with size resolved cloud microphysics. A two step approach is used for separating microphysical effects from dynamical feedbacks. In step one, an offline parcel model with bin resolved microphysics is used where cloud droplets are grown along previously recorded Lagrangian trajectories. It is shown that thermal heating and cooling rates can enhance droplet growth and rain production. Droplets grow to larger size bins in the 10–30 μm radius range. The main effect in terms of rain production arises from recirculating parcels, where a small number of droplets is exposed to strong thermal cooling at cloud edge. These recirculating parcels, comprising about 6–7 % of all parcels investigated, make up 45 % of the accumulated rain rate for the no radiation simulation and up to 60 % when 3D radiative effects are considered. The effect of 3D thermal radiation on rain production is stronger than that of 1D thermal radiation. 3D thermal radiation can enhance the rain rate up to 40 % compared to standard droplet growth without radiative effects in this idealized framework. In the second stage, fully coupled large eddy simulations show that dynamical effects are stronger than microphysical effects, as far as the production of rain is concerned. 3D thermal radiative effects again exceed 1D thermal radiative effects. Small amounts of rain are produced in more clouds (over a larger area of the domain) when thermal radiation is applied to microphysics. The dynamical feedback is shown to be an enhanced cloud circulation with stronger subsiding shells at the cloud edges due to thermal cooling, and stronger updraft velocities in the cloud center. It is shown that an evaporation-circulation feedback reduces the amount of rain produced in simulations where 3D thermal radiation is applied to microphysics and dynamics, in comparison where 3D thermal radiation is only applied to dynamics.

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