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We here inter-compare four different tracking algorithms by applying them onto the precipitation fields of an ensemble of convection-permitting regional climate models (cpRCMs) and on high-resolution observational datasets of precipitation. The domain covers the Alps and the northern Mediterranean and thus we here analyse heavy precipitation events, that are renowned for causing hydrological hazards. In this way, this study is both, an inter-comparison of tracking algorithms as well as an evaluation study of cpRCMs in the Lagrangian frame of reference. The tracker inter-comparison is performed by comparison of two case studies as well as of climatologies of cpRCMs and observations. We find that that all of the trackers produce qualitatively equal results concerning characteristic track properties. This means that, despite of quantitative differences, equivalent scientific conclusions would be drawn. This result suggests that all trackers investigated are reliable analysis tools of atmospheric research. With respect to the model ensemble evaluation, we find an encouraging performance of cpRCMs in comparison to radar-based observations. In particular prominent hotspots of heavy precipitation events are well-reproduced by the models. In general most characteristic properties of precipitation events have positive biases. Assuming the under-catchment of precipitation in observations in a domain of such complex orography, this result is to be expected. Only the mean area of tracks is underestimated, while their duration is overestimated. Mean precipitation rate is estimated well, while maximum precipitation rate is overestimated. Furthermore, geometrical and rain volume are overestimated. We find that models overestimate the occurrence of precipitation events over all mountain chains, whereas over plain terrain in summer precipitation events are seen underestimated. This suggests that, despite the convection-permitting resolution, thermally driven thunderstorms are either not triggered or their dynamics still under-resolved. Eventually we find that biases in the spatio-temporal properties of precipitation events appear reduced when evaluating cpRCMs against Doppler radar-based and rain gauge-adjusted observational datasets of comparable spatial resolution, strengthening their role in evaluation studies. [ABSTRACT FROM AUTHOR]

We investigate the effect of using convection-permitting models (CPMs) spanning a pan-European domain on the representation of precipitation distribution at a climatic scale. In particular we compare two 2.2 km models with two 12 km models run by ETH Zürich (ETH-12 km and ETH-2.2 km) and the Met-Office (UKMO-12 km and UKMO-2.2 km). The two CPMs yield qualitatively similar differences to the precipitation climatology compared to the 12 km models, despite using different dynamical cores and different parameterization packages. A quantitative analysis confirms that the CPMs give the largest differences compared to 12 km models in the hourly precipitation distribution in regions and seasons where convection is a key process: in summer across the whole of Europe and in autumn over the Mediterranean Sea and coasts. Mean precipitation is increased over high orography, with an increased amplitude of the diurnal cycle. We highlight that both CPMs show an increased number of moderate to intense short-lasting events and a decreased number of longer-lasting low-intensity events everywhere, correcting (and often over-correcting) biases in the 12 km models. The overall hourly distribution and the intensity of the most intense events is improved in Switzerland and to a lesser extent in the UK but deteriorates in Germany. The timing of the peak in the diurnal cycle of precipitation is improved. At the daily time-scale, differences in the precipitation distribution are less clear but the greater Alpine region stands out with the largest differences. Also, Mediterranean autumnal intense events are better represented at the daily time-scale in both 2.2 km models, due to improved representation of mesoscale processes. [ABSTRACT FROM AUTHOR]

B Correction to: Climate Dynamics b https://doi.org/10.1007/s00382-022-06555-z In this article the affiliation of the author Steven Chan has been changed from "School of Engineering, University of Newcastle, Callaghan, Australia" to "School of Engineering, Newcastle University, Newcastle-upon-Tyne, UK" The original article has been corrected. The original article can be found online at https://doi.org/10.1007/s00382-022-06555-z. [Extracted from the article]

Three different resolution (50, 12, and 1.5 km) regional climate model simulations are compared in terms of their ability to simulate moderate and high daily precipitation events over the southern United Kingdom. The convection-permitting 1.5-km simulation is carried out without convective parametrisation. As in previous studies, increasing resolution (especially from 50 to 12 km) is found to improve the representation of orographic precipitation. The 50-km simulation underestimates mean precipitation over the mountainous region of Wales, and event intensity tends to be too weak; this bias is reduced in both the 12- and 1.5-km simulations for both summer and winter. In south-east England lowlands where summer extremes are mostly convective, increasing resolution does not necessary lead to an improvement in the simulation. For the 12-km simulation, simulated daily extreme events are overly intense. Even though the average intensity of summer daily extremes is improved in the 1.5-km simulation, this simulation has a poorer mean bias with too many events exceeding high thresholds. Spatial density and clustering of summer extremes in south-east England are poorly simulated in both the 12- and 1.5-km simulations. In general, we have not found any clear evidence to show that the 1.5-km simulation is superior to the 12-km simulation, or vice versa at the daily level. [ABSTRACT FROM AUTHOR]

We present an analysis of the seasonal, subseasonal, and diurnal variability of rainfall from COAPS Land-Atmosphere Regional Reanalysis for the Southeast at 10-km resolution (CLARReS10). Most of our assessment focuses on the representation of summertime subseasonal and diurnal variability. Summer precipitation in the Southeast United States is a particularly challenging modeling problem because of the variety of regional-scale phenomena, such as sea breeze, thunderstorms and squall lines, which are not adequately resolved in coarse atmospheric reanalyses but contribute significantly to the hydrological budget over the region. We find that the dynamically downscaled reanalyses are in good agreement with station and gridded observations in terms of both the relative seasonal distribution and the diurnal structure of precipitation, although total precipitation amounts tend to be systematically overestimated. The diurnal cycle of summer precipitation in the downscaled reanalyses is in very good agreement with station observations and a clear improvement both over their 'parent' reanalyses and over newer-generation reanalyses. The seasonal cycle of precipitation is particularly well simulated in the Florida; this we attribute to the ability of the regional model to provide a more accurate representation of the spatial and temporal structure of finer-scale phenomena such as fronts and sea breezes. Over the northern portion of the domain summer precipitation in the downscaled reanalyses remains, as in the 'parent' reanalyses, overestimated. Given the degree of success that dynamical downscaling of reanalyses demonstrates in the simulation of the characteristics of regional precipitation, its favorable comparison to conventional newer-generation reanalyses and its cost-effectiveness, we conclude that for the Southeast United states such downscaling is a viable proxy for high-resolution conventional reanalysis. [ABSTRACT FROM AUTHOR]

This study assesses the regional-scale summer precipitation produced by the dynamical downscaling of analyzed large-scale fields. The main goal of this study is to investigate how much the regional model adds smaller scale precipitation information that the large-scale fields do not resolve. The modeling region for this study covers the southeastern United States (Florida, Georgia, Alabama, South Carolina, and North Carolina) where the summer climate is subtropical in nature, with a heavy influence of regional-scale convection. The coarse resolution (2.5° latitude/longitude) large-scale atmospheric variables from the National Center for Environmental Prediction (NCEP)/DOE reanalysis (R2) are downscaled using the NCEP/Environmental Climate Prediction Center regional spectral model (RSM) to produce precipitation at 20 km resolution for 16 summer seasons (1990-2005). The RSM produces realistic details in the regional summer precipitation at 20 km resolution. Compared to R2, the RSM-produced monthly precipitation shows better agreement with observations. There is a reduced wet bias and a more realistic spatial pattern of the precipitation climatology compared with the interpolated R2 values. The root mean square errors of the monthly R2 precipitation are reduced over 93% (1,697) of all the grid points in the five states (1,821). The temporal correlation also improves over 92% (1,675) of all grid points such that the domain-averaged correlation increases from 0.38 (R2) to 0.55 (RSM). The RSM accurately reproduces the first two observed eigenmodes, compared with the R2 product for which the second mode is not properly reproduced. The spatial patterns for wet versus dry summer years are also successfully simulated in RSM. For shorter time scales, the RSM resolves heavy rainfall events and their frequency better than R2. Correlation and categorical classification (above/near/below average) for the monthly frequency of heavy precipitation days is also significantly improved by the RSM. [ABSTRACT FROM AUTHOR]