The environment of precipitating shallow cumulus convection

Quantitative estimates of precipitation in a typical undisturbed trade wind region are derived from 2 months of radar reflectivity data and compared to the meteorological environment determined from soundings, surface flux, and airborne-lidar data. Shallow precipitation was ubiquitous, covering on average about 2% of the region and contributing to at least half of the total precipitation. Echo fractions on the scale of the radar domain range between 0% and 10% and vary greatly within a period from a few hours to a day. Variability in precipitation relates most strongly to variability in humidity and the zonal wind speed, although greater inversion heights and deeper clouds are also evident at times of more rain. The analysis herein suggests that subtle fluctuations in both the strength of the easterlies and in subsidence play a major role in regulating humidity and hence precipitation, even within a given meteorological regime (here, the undisturbed trades). [References: 45

Continuous Single-Column Model Evaluation at a Permanent Meteorological Supersite

Uncertainties in numerical predictions of weather and climate are often linked to the representation of unresolved processes that act relatively quickly compared to the resolved general circulation. These processes include turbulence, convection, clouds, and radiation. Single-column model (SCM) simulation of idealized cases and the subsequent evaluation against large-eddy simulation (LES) results has become an often used and relied on method to obtain insight at process level into the behavior of such parameterization schemes; benefits of SCM simulation are the enhanced model transparency and the high computational efficiency. Although this approach has achieved demonstrable success, some shortcomings have been identified; among these, i) the statistical significance and relevance of single idealized case studies might be questioned and ii) the use of observational datasets has been relatively limited. A recently initiated project named the Royal Netherlands Meteorological Institute (KNMI) Parameterization Testbed (KPT) is part of a general move toward a more statistically significant process-level evaluation, with the purpose of optimizing the identification of problems in general circulation models that are related to parameterization schemes. The main strategy of KPT is to apply continuous long-term SCM simulation and LES at various permanent meteorological sites, in combination with comprehensive evaluation against observations at multiple time scales. We argue that this strategy enables the reproduction of typical long-term mean behavior of fast physics in large-scale models, but it still preserves the benefits of single-case studies (such as model transparency). This facilitates the tracing and understanding of errors in parameterization schemes, which should eventually lead to a reduction of related uncertainties in numerical predictions of weather and climate

Overlap Statistics of Cumuliform Boundary-Layer Cloud Fields in Large-Eddy Simulations

Overlap statistics of cumuliform boundary-layer clouds are studied using large-eddy simulations at high resolutions. The cloud overlap is found to be highly inefficient, due to the typical irregularity of cumuliform clouds over a wide range of scales. The detection of such inefficient overlap is enabled in this study by i) applying fine enough discretizations and ii) by limiting the analysis to exclusively cumuliform boundary-layer cloud fields. It is argued that these two factors explain the differences with some previous studies on cloud overlap. In contrast, good agreement exists with previously reported observations of cloud overlap as derived from lidar measurements of liquid water clouds at small cloud covers. Various candidate functional forms are fitted to the results, suggesting that an inverse linear function is most successful in reproducing the observed behavior. The sensitivity of cloud overlap to various aspects is assessed, reporting a minimal or non-systematic dependence on discretization and vertical wind-shear, as opposed to a strong case-dependence, the latter probably reflecting differences in the cloud size distribution. Finally, calculations with an offline radiation scheme suggest that accounting for the inefficient overlap in cumuliform cloud fields in a general circulation model can change the top-of-atmosphere short-wave cloud radiative forcing by −20 to −40 W m−2, depending on vertical discretization. This corresponds to about 50 to 100% of the typical values in areas of persistent shallow cumulus, respectively

Overlap Statistics of Cumuliform Boundary-Layer Cloud Fields in Large-Eddy Simulations

Overlap statistics of cumuliform boundary-layer clouds are studied using large-eddy simulations at high resolutions. The cloud overlap is found to be highly inefficient, due to the typical irregularity of cumuliform clouds over a wide range of scales. The detection of such inefficient overlap is enabled in this study by i) applying fine enough discretizations and ii) by limiting the analysis to exclusively cumuliform boundary-layer cloud fields. It is argued that these two factors explain the differences with some previous studies on cloud overlap. In contrast, good agreement exists with previously reported observations of cloud overlap as derived from lidar measurements of liquid water clouds at small cloud covers. Various candidate functional forms are fitted to the results, suggesting that an inverse linear function is most successful in reproducing the observed behavior. The sensitivity of cloud overlap to various aspects is assessed, reporting a minimal or non-systematic dependence on discretization and vertical wind-shear, as opposed to a strong case-dependence, the latter probably reflecting differences in the cloud size distribution. Finally, calculations with an offline radiation scheme suggest that accounting for the inefficient overlap in cumuliform cloud fields in a general circulation model can change the top-of-atmosphere short-wave cloud radiative forcing by −20 to −40 W m−2, depending on vertical discretization. This corresponds to about 50 to 100% of the typical values in areas of persistent shallow cumulus, respectively

KNMI EUCLIPSE Policy Brief

Policy brief on implications of the project results on the climate decision making process. 54 month

Evaluation of the bulk mass flux formulation using large eddy simulations

In this study, bulk mass flux formulations for turbulent fluxes are evaluated for shallow and deep convection using large-eddy simulation data. The bulk mass flux approximation neglects two sources of variability: the inter-object variability due to differences between the average properties of different cloud objects, and the intra-object variability due to perturbations within each cloud object. Using a simple cloud-environment decomposition, the inter-object and intra-object contributions to the heat flux are comparable in magnitude with that from the bulk mass flux approximation, but do not share a similar vertical distribution, and so can not be parameterized with a rescaling method. A down-gradient assumption is also not appropriate to parameterize the neglected flux contributions because a non-negligible part is associated with non-local buoyant structures. A spectral analysis further suggests the presence of fine structures within the clouds. These points motivate investigations in which the vertical transports are decomposed based on the distribution of vertical velocity. As a result, a ``core-cloak" conceptual model is proposed to improve the representation of total vertical fluxes, comprised of a strong and a weak draft for both the updrafts and downdrafts. It is shown that the ``core-cloak" representation can well capture the magnitude and vertical distribution of heat and moisture fluxes for both shallow and deep convection

Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands

Meteorological fields calculated by numerical weather prediction (NWP) models drive offline chemical transport models (CTMs) to solve the transport, chemical reactions, and atmospheric interaction over the geographical domain of interest. HARMONIE (HIRLAM ALADIN Research on Mesoscale Operational NWP in Euromed) is a state-of-the-art non-hydrostatic NWP community model used at several European weather agencies to forecast weather at the local and/or regional scale. In this work, the HARMONIE WINS50 (cycle 43 cy43) reanalysis dataset at a resolution of 0.025° × 0.025° covering an area surrounding the North Sea for the years 2019–2021 was coupled offline to the LOTOS-EUROS (LOng-Term Ozone Simulation-EURopean Operational Smog model, v2.2.002) CTM. The impact of using either meteorological fields from HARMONIE or from ECMWF on LOTOS-EUROS simulations of NO2 has been evaluated against ground-level observations and TROPOMI tropospheric NO2 vertical columns. Furthermore, the difference between crucial meteorological input parameters such as the boundary layer height and the vertical diffusion coefficient between the hydrostatic ECMWF and non-hydrostatic HARMONIE data has been studied, and the vertical profiles of temperature, humidity, and wind are evaluated against meteorological observations at Cabauw in The Netherlands. The results of these first evaluations of the LOTOS-EUROS model performance in both configurations are used to investigate current uncertainties in air quality forecasting in relation to driving meteorological parameters and to assess the potential for improvements in forecasting pollution episodes at high resolutions based on the HARMONIE NWP model.</p