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We perform simulations with the WRF regional climate model at 12 and 3 km grid resolution for the current and future climates over Central Europe and evaluate their added value with a focus on the daily cycle and frequency distribution of rainfall and the relation between extreme precipitation and air temperature. First, a 9 year period of ERA-Interim driven simulations is evaluated against observations; then global climate model runs (MPI-ESM-LR RCP4.5 scenario) are downscaled and analyzed for three 12-year periods: a control, a mid-of-century and an end-of-century projection. The higher resolution simulations reproduce both the diurnal cycle and the hourly intensity distribution of precipitation more realistically compared to the 12 km simulation. Moreover, the observed increase of the temperature–extreme precipitation scaling from the Clausius–Clapeyron (C–C) scaling rate of ~ 7% K−1 to a super-adiabatic scaling rate for temperatures above 11 °C is reproduced only by the 3 km simulation. The drop of the scaling rates at high temperatures under moisture limited conditions differs between sub-regions. For both future scenario time spans both simulations suggest a slight decrease in mean summer precipitation and an increase in hourly heavy and extreme precipitation. This increase is stronger in the 3 km runs. Temperature–extreme precipitation scaling curves in the future climate are projected to shift along the 7% K−1 trajectory to higher peak extreme precipitation values at higher temperatures. The curves keep their typical shape of C–C scaling followed by super-adiabatic scaling and a drop-off at higher temperatures due to moisture limitation.

The potential utilization of specific attenuation A for rainfall estimation, mitigation of partial beam blockage, and radar networking is investigated. The R(A) relation is less susceptible to the variability of drop size distributions than traditional rainfall algorithms based on radar reflectivity Z, differential reflectivity ZDR, and specific differential phase KDP in a wide range of rain intensity. Specific attenuation is estimated from the radial profile of the measured Z and the total span of the differential phase using the ZPHI method. Since the estimated A is immune to reflectivity biases caused by radar miscalibration, attenuation, partial beam blockage, and wet radomes, rain retrieval from R(A) is also immune to the listed factors. The R(A) method was tested at X band using data collected by closely located radars in Germany and at S band for polarimetrically upgraded Weather Surveillance Radar-1988 Doppler (WSR-88D) radars in the United States. It is demonstrated that the two adjacent X-band radars—one of which is miscalibrated and another which is affected by partial beam blockage—produce almost indistinguishable fields of rain rate. It is also shown that the R(A) method yields robust estimates of rain rates and rain totals at S band, where specific attenuation is vanishingly small. The X- and S-band estimates of rainfall obtained from R(A) are in good agreement with gauges.

This sensitivity study investigates the impact of the spatial scales of land use, soil moisture and orography patterns on land–atmosphere exchange fluxes, domain-wide averages and meteorologic conditions in convection-permitting RCM simulations. We perform five WRF RCM simulations, each with the same 3 km resolution atmospheric setup but different combinations of coarsely resolved (12 km) land use and soil type, initial soil moisture and orography for the heat-wave summer 2003 over central Europe. Our results indicate that a coarser-resolved orography significantly alters the flow over and around mountain ridges such as the Alps and impact the large-scale flow pattern. The smoothed mountain ridges result in weaker Föhn effects and in enhanced locally generated convective precipitation patterns, peaking earlier in the afternoon. In comparison, the impact of a coarser-resolved land use is smaller and mainly related to changes in the overall spatial fraction of a land use, rather than to the loss of heterogeneity of the different land use types on the scale analyzed here. Albeit, even small changes in the initial soil moisture (both spatial averages and local differences) have a higher potential to affect the overall simulation results, although this might also depend on the land surface model. Overall, effects induced by the coarsely resolved land surface properties are small compared to the differences between simulations with 3 km and 12 km grid spacings of the atmosphere.

A novel methodology is introduced for processing and presenting polarimetric data collected by weather surveillance radars. It involves azimuthal averaging of radar reflectivity Z , differential reflectivity Z DR , cross-correlation coefficient ρ hv , and differential phase Φ DP at high antenna elevation, and presenting resulting quasi-vertical profiles (QVPs) in a height-versus-time format. Multiple examples of QVPs retrieved from the data collected by S-, C-, and X-band dual-polarization radars at elevations ranging from 6.4° to 28° illustrate advantages of the QVP technique. The benefits include an ability to examine the temporal evolution of microphysical processes governing precipitation production and to compare polarimetric data obtained from the scanning surveillance weather radars with observations made by vertically looking remote sensors, such as wind profilers, lidars, radiometers, cloud radars, and radars operating on spaceborne and airborne platforms. Continuous monitoring of the melting layer and the layer of dendritic growth with high vertical resolution, and the possible opportunity to discriminate between the processes of snow aggregation and riming, constitute other potential benefits of the suggested methodology.

The performance of the laser-optical Particle Size Velocity (PARSIVEL) disdrometer is evaluated to determine the characteristics of falling snow. PARSIVEL’s measuring principle is reexamined to detect its limitations and pitfalls when applied to solid precipitation. This study uses snow observations taken during the Canadian Cloudsat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Validation Project (C3VP) campaign, when two PARSIVEL instruments were collocated with a single two-dimensional disdrometer (2-DVD), which allows more detailed observation of snowflakes. When characterizing the snowflake size, PARSIVEL instruments inherently retrieve only one size parameter, which is approximately equal to the widest horizontal dimension (more accurately with large snowflakes) and that has no microphysical meaning. Unlike for raindrops, the equivolume PARSIVEL diameter—the PARSIVEL output variable—has no physical counterpart for snowflakes. PARSIVEL’s fall velocity measurement may not be accurate for a single snowflake particle. This is due to the internally assumed relationship between horizontal and vertical snow particle dimensions. The uncertainty originates from the shape-related factor, which tends to depart more and more from unity with increasing snowflake sizes and can produce large errors. When averaging over a large number of snowflakes, the correction factor is size dependent with a systematic tendency to an underestimation of the fall speed (but never exceeding 20%). Compared to a collocated 2-DVD for long-lasting events, PARSIVEL seems to overestimate the number of small snowflakes and large particles. The disagreement between PARSIVEL and 2-DVD snow measurements can only be partly ascribed to PARSIVEL intrinsic limitations (border effects and sizing problems), but it has to deal with the difficulties and drawbacks of both instruments in fully characterizing snow properties.

Knowing the freeze-thaw (FT) state of the land surface is essential for many aspects of weather forecasting, climate, hydrology, and agriculture. Microwave L-band emission contains rather direct information about the FT-state because of its impact on the soil dielectric constant, which determines microwave emissivity and the optical depth profile. However, current L-band-based FT algorithms need reference values to distinguish between frozen and thawed soil, which are often not well known. We present a new FT-state-detection algorithm based on the daily variation of the H-polarized brightness temperature of the SMAP L3c FT global product for the northern hemisphere, which is available from 2015 to 2021. Exploiting the daily variation signal allows for a more reliable state detection, particularly during the transition periods, when the near-surface soil layer may freeze and thaw on sub-daily time scales. The new algorithm requires no reference values; its results agree with the SMAP FT state product by up to 98% in summer and up to 75% in winter. Compared to the FT state inferred indirectly from the 2-m air temperature and collocated soil temperature at 0–7 cm of the ERA5-land reanalysis, the new FT algorithm has a similar performance to the SMAP FT product. The most significant differences occur over the midlatitudes, including the Tibetan plateau and its downstream area. Here, daytime surface heating may lead to daily FT transitions, which are not considered by the SMAP FT state product but are correctly identified by the new algorithm. The new FT algorithm suggests a 15 days earlier start of the frozen-soil period than the ERA5-land’s estimate. This study is expected to extend the L-band microwave remote sensing data for improved FT detection.

We present the results of a unique, parallel scaling study using a 3-D variably saturated flow problem including land surface processes that ranges from a single processor to a maximum number of 16,384 processors. In the applied finite difference framework and for a fixed problem size per processor, this results in a maximum number of approximately 8 × 10(9) grid cells (unknowns). Detailed timing information shows that the applied simulation platform ParFlow exhibits excellent parallel efficiency. This study demonstrates that regional scale hydrologic simulations on the order of 10(3) km2 are feasible at hydrologic resolution (approximately 10(0)–10(1) m laterally, 10−2–10−1 m vertically) with reasonable computation times, which has been previously assumed to be an intractable computational problem.

One-third of the Earth’s land surface experiences seasonal freezing and thawing. Freezing-thawing transitions strongly impact land-atmosphere interactions and, thus, also the lower atmosphere above such areas. Observations of two L-band satellites, the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) missions, provide flags that characterize surfaces as either frozen or not frozen. However, both state transitions—freezing and thawing (FT)—are continuous and complex processes in space and time. Especially in the L-band, which has penetration depths of up to tens of centimeters, the brightness temperature ( T B ) may be generated by a vertically-mixed profile of different FT states, which cannot be described by the current version of the Community Microwave Emission Model (CMEM). To model such complex state transitions, we extended CMEM in Fresnel mode with an FT component by allowing for (1) a varying fraction of an open water surface on top of the soil, and (2) by implementing a temporal FT phase transition delay based on the difference between the soil surface temperature and the soil temperature at 2.5 cm depth. The extended CMEM (CMEM-FT) can capture the T B progression from a completely frozen to a thawed state of the contributing layer as observed by the L-band microwave radiometer ELBARA-III installed at the Maqu station at the northeastern margin of the Tibetan Plateau. The extended model improves the correlation between the observations and CMEM simulations from 0.53/0.45 to 0.85/0.85 and its root-mean-square-error from 32/25 K to 20/15 K for H/V-polarization during thawing conditions. Yet, CMEM-FT does still not simulate the freezing transition sufficiently.

This study presents a first analysis of precipitation and related microphysical processes observed by three polarimetric X-band Doppler radars (BoXPol, JuXPol and KiXPol) in conjunction with a ground-based network of disdrometers, rain gauges and vertically pointing micro rain radars (MRRs) during the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) during April and May 2013 in Germany. While JuXPol and KiXPol were continuously observing the central HOPE area near Forschungszentrum Jülich at a close distance, BoXPol observed the area from a distance of about 48.5 km. MRRs were deployed in the central HOPE area and one MRR close to BoXPol in Bonn, Germany. Seven disdrometers and three rain gauges providing point precipitation observations were deployed at five locations within a 5 km  ×  5 km region, while three other disdrometers were collocated with the MRR in Bonn. The daily rainfall accumulation at each rain gauge/disdrometer location estimated from the three X-band polarimetric radar observations showed very good agreement. Accompanying microphysical processes during the evolution of precipitation systems were well captured by the polarimetric X-band radars and corroborated by independent observations from the other ground-based instruments.

The international field campaign called the Convective and Orographically-induced Precipitation Study (COPS) took place from June to August 2007 in southwestern Germany/eastern France. The overarching goal of COPS is to advance the quality of forecasts of orographically-induced convective precipitation by four-dimensional observations and modeling of its life cycle. COPS was endorsed as one of the Research and Development Projects of the World Weather Research Program (WWRP), and combines the efforts of institutions and scientists from eight countries. A strong collaboration between instrument principal investigators and experts on mesoscale modeling has been established within COPS. In order to study the relative importance of large-scale and small-scale forcing leading to convection initiation in low mountains, COPS is coordinated with a one-year General Observations Period in central Europe, the WWRP Forecast Demonstration Project MAP D-PHASE, and the first summertime European THORPEX Regional Campaign. Furthermore, the Atmospheric Radiation Measurement program Mobile Facility operated in the central COPS observing region for nine months in 2007. The article describes the scientific preparation of this project and the design of the observation systems. COPS will rest on three pillars: A unique synergy of observing systems, the next-generation high-resolution mesoscale models with improved model physics, and advanced data assimilation and ensemble prediction systems. These tools will be used to separate and to quantify errors in quantitative precipitation forecasting as well as to study the predictability of convective precipitation.