The growth phase of convective storms and their transition to maturity is investigated based on more than 100 cases selected from the years 2012–14 over central Europe. Dynamical growth properties as ...well as cloud-top glaciation and microphysical characteristics are derived from the SEVIRI imaging radiometer aboard the geostationary Meteosat satellites. In addition, onset and intensity of surface precipitation are related to growth and glaciation processes using observations from the radar network of the German Weather Service. The majority of analyzed cases shows a distinct maximum in cloud-top cooling rate, which is used here for temporal synchronization. Cloud growth spans a period of approximately half an hour. Glaciation rate indicators suggest that freezing 15 min prior to the maximum cooling plays an important role in invigorating convective updrafts through the release of latent heat. Smaller ice particles are found for larger cloud-top cooling, which provides observational evidence that ice particles form later and have less time to grow in stronger convective updrafts. Furthermore, maximum cloud-top height, anvil expansion rate, maximum precipitation intensity, and core size are found to be positively correlated. With respect to the onset of precipitation, this analysis shows a high probability that significant precipitation already occurs 30 min prior to maximum cloud-top cooling.
The realistic representation of low-level clouds, including their radiative effects, in atmospheric models remains challenging. A sensitivity study is presented to establish a conceptual approach for ...the evaluation of low-level clouds and their radiative impact in a highly resolved atmospheric model. Considering simulations for six case days, the analysis supports the notion that the properties of clouds more closely match the assumptions of the sub-adiabatic rather than the vertically homogeneous cloud model, suggesting its use as the basis for evaluation. For the considered cases, 95.7 % of the variance in cloud optical thickness is explained by the variance in the liquid water path, while the droplet number concentration and the sub-adiabatic fraction contribute only 3.5 % and 0.2 % to the total variance, respectively. A mean sub-adiabatic fraction of 0.45 is found, which exhibits strong inter-day variability. Applying a principal component analysis and subsequent varimax rotation to the considered set of nine properties, four dominating modes of variability are identified, which explain 97.7 % of the total variance. The first and second components correspond to the cloud base and top height, and to liquid water path, optical thickness, and cloud geometrical extent, respectively, while the cloud droplet number concentration and the sub-adiabatic fraction are the strongest contributors to the third and fourth components. Using idealized offline radiative transfer calculations, it is confirmed that the shortwave and longwave cloud radiative effects exhibit little sensitivity to the vertical structure of clouds. This reconfirms, based on an unprecedented large set of highly resolved vertical cloud profiles, that the cloud optical thickness and the cloud top and bottom heights are the main factors dominating the shortwave and longwave radiative effect of clouds and should be evaluated together with radiative fluxes using observations to attribute model deficiencies in the radiative fluxes to deficiencies in the representation of clouds. Considering the different representations of cloud microphysical processes in atmospheric models, the analysis has been further extended and the deviations between the radiative impact of the single- and double-moment schemes are assessed. Contrasting the shortwave cloud radiative effect obtained from the double-moment scheme to that of a single-moment scheme, differences of about ∼40 W m−2 and significant scatter are observed. The differences are attributable to a higher cloud albedo resulting from the high values of droplet number concentration in particular in the boundary layer predicted by the double-moment scheme, which reach median values of around ∼600 cm−3.
How organized is deep convection over Germany? Pscheidt, Ieda; Senf, Fabian; Heinze, Rieke ...
Quarterly journal of the Royal Meteorological Society,
July 2019 Part B, 2019-07-00, 20190701, Volume:
145, Issue:
723
Journal Article
Peer reviewed
Open access
Deep moist convection shows a tendency to organize into mesoscale structures. To be able to understand the potential effect of convective organization on the climate, one needs first to characterize ...organization. In this study, we systematically characterize the organizational state of convection over Germany based on two years of cloud‐top observations derived from the Meteosat Second Generation satellite and of precipitation cores detected by the German C‐band radar network. The organizational state of convection is characterized by commonly employed organization indices, which are mostly based on the object numbers, sizes and nearest‐neighbour distances. According to the organization index Iorg, cloud tops and precipitation cores are found to be in an organized state for 69% and 92% of the time, respectively. There is an increase in rainfall when the number of objects and their sizes increase, independently of the organizational state. Case‐studies of specific days suggest that convectively organized states correspond to either local multi‐cell clusters, with less numerous, larger objects close to each other, or to scattered clusters, with more numerous, smaller organized objects spread out over the domain. For those days, simulations are performed with the large‐eddy model ICON with grid spacings of 625, 312 and 156 m. Although the model underestimates rainfall and shows a too large cold cloud coverage, the organizational state is reasonably well represented without significant differences between the grid spacings.
Overview of the spatial distribution of cloud tops and precipitation cores for four days of deep convection over Germany. (a)–(d) Brightness temperature (BT) from Meteosat Second Generation, (e)–(h) synthetic BTs, (i)–(l) radar reflectivities from the Radolan RX product and (m)–(p) synthetic radar reflectivities. The synthetic datasets are generated by means of forward operators using ICON‐LEM simulation outputs with grid spacing of 156 m.
This study presents and evaluates several candidate approaches for downscaling observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) in order to increase the horizontal ...resolution of subsequent cloud optical thickness (τ) and effective droplet radius (reff) retrievals from the native ≈3km×3km spatial resolution of the narrowband channels to ≈1km×1km. These methods make use of SEVIRI's coincident broadband high-resolution visible (HRV) channel. For four example cloud fields, the reliability of each downscaling algorithm is evaluated by means of collocated 1 km×1 km MODIS radiances, which are reprojected to the horizontal grid of the HRV channel and serve as reference for the evaluation. By using these radiances, smoothed with the modulation transfer function of the native SEVIRI channels, as retrieval input, the accuracy at the SEVIRI standard resolution can be evaluated and an objective comparison of the accuracy of the different downscaling algorithms can be made. For the example scenes considered in this study, it is shown that neglecting high-frequency variations below the SEVIRI standard resolution results in significant random absolute deviations of the retrieved τ and reff of up to ≈14 and ≈6 µm, respectively, as well as biases. By error propagation, this also negatively impacts the reliability of the subsequent calculation of liquid water path (WL) and cloud droplet number concentration (ND), which exhibit deviations of up to ≈89gm-2 and ≈177cm-3, respectively. For τ, these deviations can be almost completely mitigated by the use of the HRV channel as a physical constraint and by applying most of the presented downscaling schemes. Uncertainties in retrieved reff at the native SEVIRI resolution are smaller, and the improvements from downscaling the observations are less obvious than for τ. Nonetheless, the right choice of downscaling scheme yields noticeable improvements in the retrieved reff. Furthermore, the improved reliability in retrieved cloud products results in significantly reduced uncertainties in derived WL and ND. In particular, one downscaling approach provides clear improvements for all cloud products compared to those obtained from SEVIRI's standard resolution and is recommended for future downscaling endeavors. This work advances efforts to mitigate impacts of scale mismatches among channels of multiresolution instruments on cloud retrievals.
Wildfire smoke is known as a highly absorptive aerosol type in the shortwave wavelength range. The absorption of sunlight by optically thick smoke layers results in heating of the ambient air. This ...heating is translated into self-lofting of the smoke up to more than 1 km in altitude per day. This study aims for a detailed analysis of tropospheric and stratospheric smoke lofting rates based on simulations and observations. The main goal is to demonstrate that radiative heating of intense smoke plumes is capable of lofting them from the lower and middle free troposphere (injection heights) up to the tropopause without the need of pyrocumulonimbus (pyroCb) convection. The further subsequent ascent within the lower stratosphere (caused by self-lofting) is already well documented in the literature. Simulations of absorbed solar radiation by smoke particles and resulting heating rates, which are then converted into lofting rates, are conducted by using the ECRAD (European Centre for Medium-Range Weather Forecasts Radiation) scheme. As input parameters thermodynamic profiles from CAMS (Copernicus Atmosphere Monitoring Service) reanalysis data, aerosol profiles from ground-based lidar observations, radiosonde potential temperature profiles, CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) aerosol measurements, and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth retrievals were used. The sensitivity analysis revealed that the lofting rate strongly depends on aerosol optical thickness (AOT), layer depth, layer height, and black carbon (BC) fraction. We also looked at the influence of different meteorological parameters such as cloudiness, relative humidity, and potential temperature gradient. To demonstrate the applicability of our self-lofting model, we compared our simulations with the lofting processes in the stratosphere observed with CALIOP after major pyroCb events (Canadian fires in 2017, Australian fires in 2019–2020). We analyzed long-term CALIOP observations of smoke layers and plumes evolving in the UTLS (upper troposphere and lower stratosphere) height region over Siberia and the adjacent Arctic Ocean during the summer season of 2019. Our results indicate that self-lofting contributed to the vertical transport of smoke. We hypothesize that the formation of a near-tropopause aerosol layer, observed with CALIOP, was the result of self-lofting processes because this is in line with the simulations. Furthermore, Raman-lidar-based aerosol typing (in Leipzig and the High Arctic) clearly indicated the dominance of smoke in the UTLS aerosol layer since August 2019, most probably also the result of smoke self-lofting.
The clear-sky radiative effect of aerosol-radiation interactions is of relevance for our understanding of the climate system. The influence of aerosol on the surface energy budget is of high interest ...for the renewable energy sector. In this study, the radiative effect is investigated in particular with respect to seasonal and regional variations for the region of Germany and the year 2015 at the surface and top of atmosphere using two complementary approaches.
The cloud droplet number concentration (Nd) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol‐cloud interactions. ...Current standard satellite retrievals do not operationally provide Nd, but it can be inferred from retrievals of cloud optical depth (τc) cloud droplet effective radius (re) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel‐level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. Nd uncertainty is dominated by errors in re, and therefore, improvements in re retrievals would greatly improve the quality of the Nd retrievals. Recommendations are made for how this might be achieved. Some existing Nd data sets are compared and discussed, and best practices for the use of Nd data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative Nd estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high‐quality ground‐based observations are examined.
Plain Language Summary
Clouds have a very large influence on weather and climate. It is thus a prime task for satellite‐ and ground‐based observations to measure clouds. For satellites and many other instruments this is done by remote sensing—radiation is measured, and knowledge about clouds is inferred. Liquid water clouds consist of numerous droplets of order of 10 μm in size. A key quantity that describes clouds is the number of droplets in a given volume or the droplet number concentration. However, satellite observations of droplet number concentration are only emerging, and the quality of these observations is poorly known. This review fulfills two tasks, namely, (1) to quantify how uncertain the current way to observe droplet number concentrations from satellite is and (2) to propose ways toward better approaches. It is concluded that the current way to obtain cloud droplet number concentration works for homogeneous stratus and stratocumulus clouds, with, however, a substantial error of around 50%. For cumulus clouds the observations are substantially worse. New avenues that are proposed for a better estimate of cloud droplet concentration exploit instruments that emit light (lidar) or microwaves (radar), and measure the reflected signal, or explore the polarization of light induced by clouds.
Key Points
Satellite cloud droplet concentration uncertainties of 78% for pixel‐level retrievals and 54% for 1 by 1 degree retrievals are estimated
The effective radius retrieval is the most important aspect for improvement, and more in situ evaluation is needed
Potential improvements using passive and active satellite, and ground‐based instruments are discussed
Quantifying the role of clouds in the earth's radiation budget is essential for improving our understanding of the drivers and feedback mechanisms of climate change. This holds in particular for the ...Arctic, the region currently undergoing the most rapid changes. This region, however, also poses significant challenges to remote-sensing retrievals of clouds and radiative fluxes, introducing large uncertainties in current climate data records. In particular, low-level stratiform clouds are common in the Arctic but are, due to their low altitude, challenging to observe and characterize with remote-sensing techniques. The availability of reliable ground-based observations as reference is thus of high importance. In the present study, radiative transfer simulations using state-of-the-art ground-based remote sensing of clouds are contrasted with surface radiative flux measurements to assess their ability to constrain the cloud radiative effect. Cloud radar, lidar, and microwave radiometer observations from the PS106 cruise in the Arctic marginal sea ice zone in summer 2017 were used to derive cloud micro- and macrophysical properties by means of the instrument synergy approach of Cloudnet. Closure of surface radiative fluxes can only be achieved by a realistic representation of the low-level liquid-containing clouds in the radiative transfer simulations. The original, most likely erroneous, representation of these low-level clouds in the radiative transfer simulations led to errors in the cloud radiative effect of 54 W m−2. In total, the proposed method could be applied to 11 % of the observations. For the data, where the proposed method was utilized, the average relative error decreased from 109 % to 37 % for the simulated solar and from 18 % to 2.5 % for the simulated terrestrial downward radiative fluxes at the surface. The present study highlights the importance of jointly improving retrievals for low-level liquid-containing clouds which are frequently encountered in the high Arctic, together with observational capabilities both in terms of cloud remote sensing and radiative flux observations. Concrete suggestions for achieving these goals are provided.
The spatiotemporal evolution of warm convective cloud fields over central Europe is investigated on the basis of 30 cases using observations from the Spinning Enhanced Visible and Infrared Imager ...(SEVIRI) on board the geostationary Meteosat platforms. Cloud fields are tracked in successive satellite images using cloud motion vectors. The time-lagged autocorrelation is calculated for spectral reflectance and cloud property fields using boxes of 16 × 16 pixels and adopting both Lagrangian and Eulerian perspectives. The 0.6-μm reflectance, cloud optical depth, and water path show a similar characteristic Lagrangian decorrelation time of about 30 min. In contrast, significantly lower decorrelation times are observed for the cloud effective radius and droplet density. It is shown that the Eulerian decorrelation time can be decomposed into an advective component and a convective component using the spatial autocorrelation function. In an Eulerian frame cloud fields generally decorrelate faster than in a Lagrangian one. The Eulerian decorrelation time contains contributions from the spatial decorrelation of the cloud field advected by the horizontal wind. Atypical spatial decorrelation length of 7 km is observed, which suggests that sampling of SEVIRI observations is better in the temporal domain than in the spatial domain when investigating small-scale convective clouds. An along-track time series of box-averaged cloud liquid water path is derived and compared with the time series that would be measured at a fixed location. Supported by previous results, it is argued that this makes it possible to discriminate between local changes such as condensation and evaporation on the one hand and advective changes on the other hand.
To estimate the global co-variability between mineral dust aerosol and cloud glaciation, we combined an aerosol model reanalysis with satellite retrievals of cloud thermodynamic phase. We used the ...CALIPSO-GOCCP product from the A-Train satellite constellation to assess whether clouds are composed of liquid or ice and the MACC reanalysis to estimate the dust mixing ratio in the atmosphere. Night-time retrievals within a temperature range from +3 to −42 ∘C for the period 2007–2010 were included. The results confirm that the cloud thermodynamic phase is highly dependent on temperature and latitude. However, at middle and high latitudes, at equal temperature and within narrow constraints for humidity and static stability, the average frequency of fully glaciated clouds increases by +5 to +10 % for higher mineral dust mixing ratios. The discrimination between humidity and stability regimes reduced the confounding influence of meteorology on the observed relationship between dust and cloud ice. Furthermore, for days with similar mixing ratios of mineral dust, the cloud ice occurrence frequency in the Northern Hemisphere was found to be higher than in the Southern Hemisphere at −30 ∘C but lower at −15 ∘C. This contrast may suggest a difference in the susceptibility of cloud glaciation to the presence of dust. Based on previous studies, the differences at −15 ∘C could be explained by higher feldspar fractions in the Southern Hemisphere, while the higher freezing efficiency of clay minerals in the Northern Hemisphere may explain the differences at −30 ∘C.
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