Silke Trömel

The hot summer 2003 in Germany. Some preliminary results of a statistical time series analysis

A statistical analysis of the summer (June, July, and August) surface air temperature, time series 1761-2003, representative of Germany, is presented. Rank statistics, where the 2003 value (3.4 K above the 1961-1990 average) appears to be by far the maximum on record, are listed as well as trend values for the whole and defined subperiods including the contributions of the individual summer months. The warming detectable since approximately 1900/1920 shows a progressive structure with highest values in recent decades. The month of August contributes much more to this warming than the other summer months. A time-dependent probability analysis of the 2003 event reveals an increasing probability, especially in recent decades. However, even under these assumptions, the 2003 event is very extreme.

Backscatter Differential Phase—Estimation and Variability

On the basis of simulations and observations made with polarimetric radars operating at X, C, and S bands, the backscatter differential phase d has been explored; d has been identified as an important polarimetric variable that should not be ignored in precipitation estimations that are based on specific differential phase KDP, especially at shorter radar wavelengths. Moreover, d bears important information about the dominant size of raindrops and wet snowflakes in the melting layer. New methods for estimating d in rain and in the melting layer are suggested.The method for estimatingdin rain is based on a modifiedversion of the ‘‘ZPHI’’ algorithm and provides reasonably robust estimates of d and KDP in pure rain except in regions where the total measured differential phase FDP behaves erratically, such as areas affected by nonuniform beam filling or low signal-to-noise ratio. The method for estimating d in the melting layer results in reliable estimates of d in stratiform precipitation and requires azimuthal averaging of radial profiles of FDP at high antenna elevations. Comparisons with large disdrometer datasets collected in Oklahoma and Germany confirm a strong interdependence between d and differential reflectivity ZDR. Because d is immune to attenuation, partial beam blockage, and radar miscalibration, the strong correlation between ZDR and d is of interest for quantitative precipitation estimation:dandZDRare differently affected by the particle size distribution(PSD) and thus may complement each other for PSD moment estimation. Furthermore, the magnitude of d can be utilized as an important calibration parameter for improving microphysical models of the melting layer.

Quasi-Vertical Profiles—A New Way to Look at Polarimetric Radar Data

AbstractA 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 ZDR, cross-correlation coefficient ρhv, and differential phase ΦDP 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 l...

Use of Specific Attenuation for Rainfall Measurement at X-Band Radar Wavelengths. Part I: Radar Calibration and Partial Beam Blockage Estimation

In a two-part paper, radar rain-rate retrievals using specific attenuation A suggested by Ryzhkov et al. are thoroughly investigated. Continuous time series of overlapping measurements from two twin polarimetric X-band weather radars in Germany during the summers of 2011‐13 are used to analyze various aspects of rain-rate retrieval, including miscalibration correction, mitigation of ground clutter contamination and partial beam blockage (PBB), sensitivity to precipitation characteristics, and the temperature assumptions of the R(A) technique. In this paper, the relations inherent to the R(A) method are used to estimate radar reflectivity Z from A and compare it to the measured Z in order to estimate PBB and calibration offsets for both radars. The fields of Z estimated from A for both radars are consistent, and the differences between Z(A) and measured Z are in good agreement with the ones calculated using either consistency relations between reflectivity at horizontal polarization ZH, differential reflectivity ZDR ,a nd specific differential phase KDP in rain or a digital elevation model in the presence of PBB. In the analysis, the dependence of A on temperature appears to have minimal effects on the overall performance of the method. As expected, the difference between Z(A) and attenuation-corrected measured Z observations varies with rain type and exhibits a weak systematic dependency on rainfall intensity; thus, averaging over several rain events is required to obtain reliable estimates of the Z biases caused by radar miscalibration and PBB.

Investigations of Backscatter Differential Phase in the Melting Layer

Backscatter differential phase d within the melting layer has been identified as a reliably measurable but still underutilized polarimetric variable. Polarimetric radar observations at X band in Germany and S band in the United States are presented that show maximal observed d of 8.58 at X band but up to 708 at S band. Dual-frequency observations at X and C band in Germany and dual-frequency observations at C and S band in the United States are compared to explore the regional frequency dependencies of thed signature. Theoretical simulations based on usual assumptions aboutthe microphysical composition ofthe melting layer cannot reproduce the observed large values of d at the lower-frequency bands and also underestimate the enhancements in differential reflectivity ZDR and reductions in the cross-correlation coefficient rhy. Simulations using a two-layer T-matrix code and a simple model for the representation of accretion can, however, explain the pronounced d signatures at S and C bands in conjunction with small d at X band. The authors conclude that the d signature bears information about microphysical accretion and aggregation processes in the melting layer and the degree of riming of the snowflakes aloft.

Use of Specific Attenuation for Rainfall Measurement at X-Band Radar Wavelengths. Part II: Rainfall Estimates and Comparison with Rain Gauges

AbstractIn a series of two papers, rain-rate retrievals based on specific attenuation A at radar X-band wavelength using the R(A) method presented by Ryzhkov et al. are thoroughly investigated. Continuous time series of overlapping measurements from two polarimetric X-band weather radars in Germany during the summers of 2011–13 are used to analyze various aspects of the method, like miscalibration correction, ground clutter contamination, partial beam blockage (PBB), sensitivity to precipitation characteristics, and sensitivity to temperature assumptions in the retrievals. In Part I of the series, the relations inherent to the R(A) method were used to calculate radar reflectivity Z from specific attenuation and it was compared with measured reflectivity to estimate PBB and calibration errors for both radars. In this paper, R(A) rain estimates are compared to R(Z) and R(KDP) retrievals using specific phase shift KDP. PBB and calibration corrections derived in Part I made the R(Z) rainfall estimates almost ...

Initial phase of the Hans-Ertel Centre for Weather Research - A virtual centre at the interface of basic and applied weather and climate research

The Hans-Ertel Centre for Weather Research is a network of German universities, research institutes and the German Weather Service (Deutscher Wetterdienst, DWD). It has been established to trigger and intensify basic research and education on weather forecasting and climate monitoring. The performed research ranges from nowcasting and short-term weather forecasting to convective-scale data assimilation, the development of parameterizations for numerical weather prediction models, climate monitoring and the communication and use of forecast information. Scientific findings from the network contribute to better understanding of the life-cycle of shallow and deep convection, representation of uncertainty in ensemble systems, effects of unresolved variability, regional climate variability, perception of forecasts and vulnerability of society. Concrete developments within the research network include dual observation-microphysics composites, satellite forward operators, tools to estimate observation impact, cloud and precipitation system tracking algorithms, large-eddy-simulations, a regional reanalysis and a probabilistic forecast test product. Within three years, the network has triggered a number of activities that include the training and education of young scientists besides the centres core objective of complementing DWDs internal research with relevant basic research at universities and research institutes. The long term goal is to develop a self-sustaining research network that continues the close collaboration with DWD and the national and international research community.

HErZ: The German Hans-Ertel Centre for Weather Research

AbstractIn 2011, the German Federal Ministry of Transport, Building and Urban Development laid the foundation of the Hans-Ertel Centre for Weather Research [Hans-Ertel-Zentrum fur Wetterforschung (HErZ)] in order to better connect fundamental meteorological research and teaching at German universities and atmospheric research centers with the needs of the German national weather service Deutscher Wetterdienst (DWD). The concept for HErZ was developed by DWD and its scientific advisory board with input from the entire German meteorological community. It foresees core research funding of about €2,000,000 yr−1 over a 12-yr period, during which time permanent research groups must be established and DWD subjects strengthened in the university curriculum. Five priority research areas were identified: atmospheric dynamics and predictability, data assimilation, model development, climate monitoring and diagnostics, and the optimal use of information from weather forecasting and climate monitoring for the benefit ...

Using Microwave Backhaul Links to Optimize the Performance of Algorithms for Rainfall Estimation and Attenuation Correction

The variability in raindrop size distributions and attenuation effects are the two major sources of uncertainty in radar-based quantitative precipitation estimation (QPE) even when dual-polarization radars are used. New methods are introduced to exploit the measurements by commercial microwave radio links to reduce the uncertainties in both attenuation correction and rainfall estimation. The ratio a of specific attenuation A and specific differential phase KDP is the key parameter used in attenuation correction schemes and the recently introducedR(A) algorithm. It is demonstratedthat the factora can be optimized using microwave links at Ku band oriented along radar radials with an accuracy of about 20%‐30%. The microwave links with arbitrary orientation can be utilized to optimize the intercepts in the R(KDP) and R(A) relations with an accuracy of about25%.TheperformanceofthesuggestedmethodsistestedusingthepolarimetricC-bandradaroperated bytheGermanWeatherServiceonMountHohenpeissenberginsouthernGermanyandtworadiallyoriented Ku-band microwave links from Ericsson GmbH.

A generalized method of time series decomposition into significant components including probability assessments of extreme events and application to observational German precipitation data

The analysis of climate variability realized in time series of observational data needs adequate statistical methods. In particular, it is important to estimate reliably significant structured components like the annual cycle, trends, the episodic component and extreme events including variations of these components. In this issue estimators are called reliable, if a priori assumed statistical assumptions are fulfilled. However, climate change concerns not only the mean value of meteorological variables, but all parameters of any related frequency distribution. In consequence, a generalized time series decomposition technique is presented allowing a free choice of the underlying probability density function (PDF). The signal (structured components like trends etc.) is detected in two instead of one parameter of a PDF, which can be chosen without any further restriction. So, the scale parameter of any PDF is no longer seen as a constant but rather affected by a deterministic process. The trend and seasonal component reflected in both parameters under consideration are estimated simultaneously in a modified stepwise regression. To deal also with superposed polynomial components and extreme events an iterative procedure is applied that converges to robust estimates of all the components. In particular, the method allows a consistent decomposition of precipitation time series into a statistical and a deterministic component. It arises, that in the special case of 132 time series of monthly precipitation totals 1901-2000, from German stations, the interpretation as a realization of a Gumbel-distributed random variable with time-dependent scale and location parameter reveals a complete analytical description of the time series. In addition to the detection of the components mentioned above, now it is possible to quantify the probability of exceeding optional upper or lower thresholds, respectively, for any time step of the observation period.