The HD(CP)2 Observational Prototype Experiment HOPE – An Overview

Abstract

<p><strong>Abstract.</strong> The "HD(CP)<sup>2</sup> 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. <br><br> 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. <br><br> 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 km<sup>3</sup>. 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.</p>

Quantifying the Impact of Subsurface‐Land Surface Physical Processes on the Predictive Skill of Subseasonal Mesoscale Atmospheric Simulations

“…The metrics need also to address the particular weather situations and impacts under scrutiny (e.g., drought forecasting or flood monitoring). While the analyzed time period covers a range of different weather conditions, as also documented in Macke et al (), the present study should be extended to different seasons and years to corroborate the strong influence of the large‐scale synoptic weather conditions via the lateral boundary forcing on the model configuration‐specific results. Moreover, the role of more slowly evolving components of the terrestrial system like the groundwater water table on weather forecasting at the subseasonal range should be investigated over regions and situations with stronger land‐atmosphere coupling conditions (i.e., hot spots).…”

“…The unique observational data set used in this study combines observations from continuous monitoring and from intense observation periods (IOPs) conducted under specific weather conditions (e.g., clear skies, boundary layer clouds, or precipitation‐developing clouds) performed during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP) 2 ) Observational Prototype Experiment (HOPE) between April and May 2013 (Macke et al, ). Different weather situations, which varied from several warm and cold front passages interrupted by a few high‐pressure systems with high‐level cirrus clouds at the beginning of the campaign and more low‐level convective clouds at the end, were covered by the 2‐month period; see Table 3 in Macke et al () for a summary of the atmospheric conditions during the IOPs. The field campaigns were supported by the Transregional Collaborative Research Centre (Simmer et al, ), the Terrestrial Environmental Observatories (Zacharias et al, ), the Juelich Observatory for Cloud Evolution (JOYCE; Loehnert et al, ), and the HD(CP) 2 project (Heinze et al, ).…”

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications

“…In particular, the analysis of irradiance fields with high spatial resolutions requires measurements from a dense network of observation sites, such as the high-quality data set collected during the HOPE campaign (Macke and HOPE-Team, 2014] and Madhavan, Kalisch, and Macke 2014;Figure7-2, bottom). Measurements with more than 90 photodiode pyranometers distributed throughout an area of 10 km by 10 km close to Jülich in Germany where taken from April to July 2013.…”

Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers

“…During the HOPE Melpitz campaign (May-July 2015; Macke et al, 2016), two EKO ML-020VM pyranometers were operated in close proximity, using a sun tracker and shading to obtain the diffuse radiation from one of the instruments, and to study this aspect in more detail.…”