ALBERT

Description: Large-scale afforestation is increasingly being considered as a negative emissions method for sequestering large quantities of atmospheric CO2. At the same time, regional weather modification methods, like cloud seeding, are being used to counteract increasing water scarcity in arid regions. Large-scale sustainable desert agroforestry plantations can contribute to climate change mitigation and can also be used to modify regional climate, particularly rainfall. Climate impacts from plantations need to be well understood before considering implementation. Typically, impact studies are attempted at continental or global scales and use coarse-resolution models, which suffer from severe systematic errors. This is highly problematic because decision makers should only countenance geoengineering schemes like global afforestation if impacts are understood on the regional scale. We posit the necessity of using high-resolution regional models with sophisticated representations of land–atmosphere feedback and vegetation. This approach allows for studying desert plantations and the process chain leading to climate modification. We demonstrate that large-scale plantations enhance regional clouds and rainfall and derive an index for predicting plantation impacts. Thus, desert plantations represent a unique environmental solution via predictable regional weather modification and carbon storage.

Description: The added value of global simulations on the convection-permitting (CP) scale is a subject of extensive research in the earth system science community. An increase in predictive skill can be expected due to advanced representations of feedbacks and teleconnections in the ocean–land–atmosphere system. However, the proof of this hypothesis by corresponding simulations is computationally and scientifically extremely demanding. We present a novel latitude-belt simulation from 57∘ S to 65∘ N using the Weather Research and Forecasting (WRF)-Noah-MP model system with a grid increment of 0.03∘ over a period of 5 months forced by sea surface temperature observations. In comparison to a latitude-belt simulation with 45 km resolution, at CP resolution the representation of the spatial-temporal scales and the organization of tropical convection are improved considerably. The teleconnection pattern is very close to that of the operational European Centre for Medium Range Weather Forecasting (ECMWF) analyses. The CP simulation is associated with an improvement of the precipitation forecast over South America, Africa, and the Indian Ocean and considerably improves the representation of cloud coverage along the tropics. Our results demonstrate a significant added value of future simulations on the CP scale up to the seasonal forecast range.

Description: We present the first measurement of the sensible heat flux (H) profile in the convective boundary layer (CBL) derived from the covariance of collocated vertical-pointing temperature rotational Raman lidar and Doppler wind lidar measurements. The uncertainties of the H measurements due to instrumental noise and limited sampling are also derived and discussed. Simultaneous measurements of the latent heat flux profile (L) and other turbulent variables were obtained with the combination of water-vapor differential absorption lidar (WVDIAL) and Doppler lidar. The case study uses a measurement example from the HOPE (HD(CP)2 Observational Prototype Experiment) campaign, which took place in western Germany in 2013 and presents a cloud-free well-developed quasi-stationary CBL. The mean boundary layer height zi was at 1230 m above ground level. The results show – as expected – positive values of H in the middle of the CBL. A maximum of (182±32) W m−2, with the second number for the noise uncertainty, is found at 0.5 zi. At about 0.7 zi, H changes sign to negative values above. The entrainment flux was (-62±27) W m−2. The mean sensible heat flux divergence in the observed part of the CBL above 0.3 zi was −0.28 W m−3, which corresponds to a warming of 0.83 K h−1. The L profile shows a slight positive mean flux divergence of 0.12 W m−3 and an entrainment flux of (214±36) W m−2. The combination of H and L profiles in combination with variance and other turbulent parameters is very valuable for the evaluation of large-eddy simulation (LES) results and the further improvement and validation of turbulence parameterization schemes.

Description: A new backscatter lidar forward operator was developed which is based on the distinct calculation of the aerosols' backscatter and extinction properties. The forward operator was adapted to the COSMO-ART ash dispersion simulation of the Eyjafjallajökull eruption in 2010. While the particle number concentration was provided as a model output variable, the scattering properties of each individual particle type were determined by dedicated scattering calculations. Sensitivity studies were performed to estimate the uncertainties related to the assumed particle properties. Scattering calculations for several types of non-spherical particles required the usage of T-matrix routines. Due to the distinct calculation of the backscatter and extinction properties of the models' volcanic ash size classes, the sensitivity studies could be made for each size class individually, which is not the case for forward models based on a fixed lidar ratio. Finally, the forward-modeled lidar profiles have been compared to automated ceilometer lidar (ACL) measurements both qualitatively and quantitatively while the attenuated backscatter coefficient was chosen as a suitable physical quantity. As the ACL measurements were not calibrated automatically, their calibration had to be performed using satellite lidar and ground-based Raman lidar measurements. A slight overestimation of the model-predicted volcanic ash number density was observed. Major requirements for future data assimilation of data from ACL have been identified, namely, the availability of calibrated lidar measurement data, a scattering database for atmospheric aerosols, a better representation and coverage of aerosols by the ash dispersion model, and more investigation in backscatter lidar forward operators which calculate the backscatter coefficient directly for each individual aerosol type. The introduced forward operator offers the flexibility to be adapted to a multitude of model systems and measurement setups.

Description: The HD(CP)2 Observational Prototype Experiment (HOPE) was performed as a major 2-month field experiment in Jülich, Germany, in April and May 2013, followed by a smaller campaign in Melpitz, Germany, in September 2013. HOPE has been designed to provide an observational dataset for a critical evaluation of the new German community atmospheric icosahedral non-hydrostatic (ICON) model at the scale of the model simulations and further to provide information on land-surface–atmospheric boundary layer exchange, cloud and precipitation processes, as well as sub-grid variability and microphysical properties that are subject to parameterizations. HOPE focuses on the onset of clouds and precipitation in the convective atmospheric boundary layer. This paper summarizes the instrument set-ups, the intensive observation periods, and example results from both campaigns. HOPE-Jülich instrumentation included a radio sounding station, 4 Doppler lidars, 4 Raman lidars (3 of them provide temperature, 3 of them water vapour, and all of them particle backscatter data), 1 water vapour differential absorption lidar, 3 cloud radars, 5 microwave radiometers, 3 rain radars, 6 sky imagers, 99 pyranometers, and 5 sun photometers operated at different sites, some of them in synergy. The HOPE-Melpitz campaign combined ground-based remote sensing of aerosols and clouds with helicopter- and balloon-based in situ observations in the atmospheric column and at the surface. HOPE provided an unprecedented collection of atmospheric dynamical, thermodynamical, and micro- and macrophysical properties of aerosols, clouds, and precipitation with high spatial and temporal resolution within a cube of approximately 10  ×  10  ×  10 km3. HOPE data will significantly contribute to our understanding of boundary layer dynamics and the formation of clouds and precipitation. The datasets have been made available through a dedicated data portal. First applications of HOPE data for model evaluation have shown a general agreement between observed and modelled boundary layer height, turbulence characteristics, and cloud coverage, but they also point to significant differences that deserve further investigations from both the observational and the modelling perspective.

Description: Measurements carried out by the University of Basilicata Raman lidar system (BASIL) are reported to demonstrate the capability of this instrument to characterise turbulent processes within the convective boundary layer (CBL). In order to resolve the vertical profiles of turbulent variables, high-resolution water vapour and temperature measurements, with a temporal resolution of 10 s and vertical resolutions of 90 and 30 m, respectively, are considered. Measurements of higher-order moments of the turbulent fluctuations of water vapour mixing ratio and temperature are obtained based on the application of autocovariance analyses to the water vapour mixing ratio and temperature time series. The algorithms are applied to a case study (11:30–13:30 UTC, 20 April 2013) from the High Definition Clouds and Precipitation for Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE), held in western Germany in the spring 2013. A new correction scheme for the removal of the elastic signal crosstalk into the low quantum number rotational Raman signal is applied. The noise errors are small enough to derive up to fourth-order moments for both water vapour mixing ratio and temperature fluctuations.To the best of our knowledge, BASIL is the first Raman lidar with a demonstrated capability to simultaneously retrieve daytime profiles of water vapour turbulent fluctuations up to the fourth order throughout the atmospheric CBL. This is combined with the capability of measuring daytime profiles of temperature fluctuations up to the fourth order. These measurements, in combination with measurements from other lidar and in situ systems, are important for verifying and possibly improving turbulence and convection parameterisation in weather and climate models at different scales down to the grey zone (grid increment  ∼  1 km; Wulfmeyer et al., 2016).For the considered case study, which represents a well-mixed and quasi-stationary CBL, the mean boundary layer height is found to be 1290 ± 75 m above ground level (a.g.l.). Values of the integral scale for water vapour and temperature fluctuations at the top of the CBL are in the range of 70–125 and 75–225 s, respectively; these values are much larger than the temporal resolution of the measurements (10 s), which testifies that the temporal resolution considered for the measurements is sufficiently high to resolve turbulent processes down to the inertial subrange and, consequently, to resolve the major part of the turbulent fluctuations. Peak values of all moments are found in the interfacial layer in the proximity of the top of the CBL. Specifically, water vapour and temperature second-order moments (variance) have maximum values of 0.29 g2 kg−2 and 0.26 K2; water vapour and temperature third-order moments have peak values of 0.156 g3 kg−3 and −0.067 K3, while water vapour and temperature fourth-order moments have maximum values of 0.28 g4 kg−4 and 0.24 K4. Water vapour and temperature kurtosis have values of  ∼  3 in the upper portion of the CBL, which indicate normally distributed humidity and temperature fluctuations. Reported values of the higher-order moments are in good agreement with previous measurements at different locations, thus providing confidence in the possibility of using these measurements for turbulence parameterisation in weather and climate models.In the determination of the temperature profiles, particular care was dedicated to minimise potential effects associated with elastic signal crosstalk on the rotational Raman signals. For this purpose, a specific algorithm was defined and tested to identify and remove the elastic signal crosstalk and to assess the residual systematic uncertainty affecting temperature measurements after correction. The application of this approach confirms that, for the present Raman lidar system, the crosstalk factor remains constant with time; consequently an appropriate assessment of its constant value allows for a complete removal of the leaking elastic signal from the rotational Raman lidar signals at any time (with a residual error on temperature measurements after correction not exceeding 0.18 K).

Description: Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

Description: The "HD(CP)2 Observational Prototype Experiment" (HOPE) was executed as a major 2-month field experiment in Jülich, Germany, performed in April and May 2013, followed by a smaller campaign in Melpitz, Germany in September 2013. HOPE has been designed to provide a critical evaluation of the new German community atmospheric Icosahedral non-hydrostatic (ICON) model at the scale of the model simulations and further to provide information on land-surface-atmospheric boundary layer exchange, cloud and precipitation processes as well as on sub-grid variability and microphysical properties that are subject to parameterizations. HOPE focuses on the onset of clouds and precipitation in the convective atmospheric boundary layer. The paper summarizes the instrument set-ups, the intensive observation periods as well as example results from both campaigns. HOPE-Jülich instrumentation included a radio sounding station, 4 Doppler lidars, 4 Raman lidars (3, 3, and 4 of these provide temperature, water vapor, and particle backscatter data, respectively), 1 water vapour differential absorption lidar, 3 cloud radars, 5 microwave radiometers, 3 rain radars, 6 sky imagers, 99 pyranometers, and 5 Sun photometers operated in synergy at different supersites. The HOPE-Melpitz campaign combined ground-based remote sensing of aerosols and clouds with helicopter- and balloon-based in-situ observations in the atmospheric column and at the surface. HOPE provided an unprecedented collection of atmospheric dynamical, thermodynamical, and micro- and macrophysical properties of aerosols, clouds and precipitation with high spatial and temporal resolution within a cube of approximately 10 × 10 × 10 km3. HOPE data will significantly contribute to our understanding of boundary layer dynamics and the formation of clouds and precipitation. The datasets are made available through a dedicated data portal.

Description: Measurements carried out by the University of BASILicata Raman lidar system (BASIL) are reported to demonstrate the capability of this instrument to characterize turbulent processes within the convective boundary layer (CBL). In order to resolve the vertical profiles of turbulent variables, high resolution water vapour and temperature measurements, with a temporal resolution of 10 s and a vertical resolution of 90 m and 30 m, respectively, are considered. Measurements of higher-order moments of the turbulent fluctuations of water vapour mixing ratio and temperature are obtained based on the application of auto-covariance analyses to the water vapour mixing ratio and temperature time series. The algorithms are applied to a case study (11:30–13:30 UTC, 20 April 2013) from the High Definition Clouds and Precipitation for Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE), held in Western Germany in the spring 2013. A new correction scheme for the elastic-signal leakage in the low-quantum number rotational Raman signal is applied. The noise errors are small enough to derive up to fourth-order moments for both water vapour mixing ratio and temperature fluctuations. To the best of our knowledge, BASIL is the first Raman lidar with a demonstrated capability to simultaneously retrieve daytime profiles of water vapour turbulent fluctuations up to the fourth order throughout the atmospheric CBL, this capability being combined with the one to also measure daytime profiles of temperature fluctuations up to the fourth order. For the considered case study, which represents a well-mixed and quasi-stationary CBL, the mean boundary layer height is found to be 1290 ± 77 m a.g.l. Values of the integral scale for water vapour and temperature fluctuations at the top of the CBL are in the range of 70–125 s and 75–225 s, respectively; these values are much larger than the temporal resolution of the measurements (10 s), which testifies that the temporal resolution considered for the measurements is sufficiently high to resolve turbulence processes down to the inertial sub-range and consequently resolve the major part of the turbulent fluctuations. Peak values of all moments are found in the interfacial layer in the proximity of the top of the CBL. Specifically, water vapour and temperature second-order moment (variance) has a maximum value of 0.29 g2 kg−2 and 0.26 K2, respectively, water vapour and temperature third-order moment has a peak value of 0.156 g3 kg−3 and −0.067 K3, respectively, while water vapour and temperature fourth-order moment has a maximum value of 0.28 g4 kg−4 and 0.24 K4, respectively. Water vapour and temperature kurtosis have values of ~ 3 in the entrainment zone, which indicate normally distributed humidity and temperature fluctuations. Reported values of the higher-order moments result to be in good agreement with previous measurements at different locations, thus providing confidence on the possibility to use them for turbulence parameterization in weather and climate models. In the determination of the temperature profiles, particular care was dedicated to minimize potential effects associated with elastic signal leakage in the rotational Raman signals. For this purpose, a specific algorithm was defined and tested to identify and remove signal leakages and to assess the residual systematic uncertainty affecting temperature measurements after correction. The application of this approach confirms that for the present Raman lidar system the leakage factor keeps constant with time, and consequently an appropriate assessment of its constant value allows for a complete removal of the leaking elastic signal from the rotational Raman lidar signals at any time (with a residual error on temperature measurements after correction not exceeding 0.16 K).