Uncertainties in ERA-5 and UERRA reanalyses detected by adjusted radar precipitation - a regional study for the Czech Republic

Regional reanalysis constitute of potentially attractive new data source for many applications. They can offer added value benefiting from their higher spatial and temporal resolution. On the other hand, similarly as other data sources in regular network, reanalysis comes with uncertainties especially in the case of extremes.The monitoring capability of reanalysis is essential for their usage as the reference datasets for climate model validation as well as for hydrological models. In this contribution, we evaluate the agreement of precipitation between modern reanalysis products (Era5, Era5 Land, Harmonie and Mescan-Surfex; with resolution between 5.5 and 32 km) and observed data at different time scales, from annual to subdaily. Studied characteristics of precipitation are for instance annual cycle of precipitation amount and the number of wet days, diurnal cycle of precipitation, and extremes. The common period for all datasets is 2002 &#8211; 2018.Observed data used in this study are represented by adjusted radar-derived precipitation totals in 1km raster over the Czech Republic. The adjusted radar-derived precipitation totals are gained as follows. First, the radar-derived rain field is spatially adjusted to measurements from the rain gauges as a whole. For each day, the ratio between the mean 1-day precipitation total calculated from all rain gauges and the mean 1-day precipitation total estimated from the corresponding radar pixels is determined and used for a multiplication of radar-derived precipitation in every pixel of the radar domain. Second, the spatially adjusted radar-derived rain rates are locally adjusted in individual pixels based on the distance from the closest rain gauge, whereas the weight of the observed precipitation is decreasing with increasing distance to the given pixel. Adjusted daily precipitation total is then divided according to 10 min radar-derived estimates, from which the precipitation accumulations of longer duration are calculated.

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Evaluation of the Contribution of Deposited Precipitation

Advances in Meteorology ◽

10.1155/2015/472963 ◽

2015 ◽

Vol 2015 ◽

pp. 1-7

Author(s):

Jaroslav Fišák ◽

Miroslav Tesař

Keyword(s):

Czech Republic ◽

Automatic Device ◽

Main Topic ◽

Atmospheric Physics ◽

The Czech Republic ◽

Rain Gauges ◽

Weight Measurement ◽

Bohemian Forest ◽

The Mean ◽

Is Evaluation

Main topic of this study is evaluation of the contribution of deposited precipitation (DP) to the falling precipitation (FP) amount. An automatic device for DP weight measurement developed and produced at the Institute of Atmospheric Physics was used. The tipping bucket rain gauges were used for the FP measurement. Present paper summarizes the results of measurements of deposited and falling precipitation in three localities: Suchdol, Prague (capital of the Czech Republic), Poledník (Bohemian Forest), and Smĕdava (the Jizerské hory Mts.). Two later introduced stations are situated in the mountainous part of the Czech Republic. For each of mentioned stations the daily averages of the DP totals were determined by the values 0.074 mm for Suchdol, 0.112 mm for Poledník, and 0.103 mm for Smĕdava. Further the mean daily DP sums were evaluated for the days with the occurrence of this precipitation only by the values 0.136 mm, 0.276 mm, and 0.289 mm for the stations Suchdol, Poledník, and Smĕdava, respectively. Obtained results were compared with the findings published in the literature. In each of the stations the ratio between the deposited and falling precipitation was determined as well. For the Suchdol this ratio reached 95.2% in December 2013.

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Global Radiative Flux and Cloudiness Variability for the Period 1959–2010 in Belgium: A Comparison between Reanalyses and the Regional Climate Model MAR

Atmosphere ◽

10.3390/atmos9070262 ◽

2018 ◽

Vol 9 (7) ◽

pp. 262 ◽

Cited By ~ 4

Author(s):

Coraline Wyard ◽

Sébastien Doutreloup ◽

Alexandre Belleflamme ◽

Martin Wild ◽

Xavier Fettweis

Keyword(s):

Cloud Cover ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Regional Climate Models ◽

Horizontal Resolution ◽

Radiative Flux ◽

Added Value ◽

Historical Trends ◽

The Mean

The use of regional climate models (RCMs) can partly reduce the biases in global radiative flux (Eg↓) that are found in reanalysis products and global models, as they allow for a finer spatial resolution and a finer parametrisation of surface and atmospheric processes. In this study, we assess the ability of the MAR («Modèle Atmosphérique Régional») RCM to reproduce observed changes in Eg↓, and we investigate the added value of MAR with respect to reanalyses. Simulations were performed at a horizontal resolution of 5 km for the period 1959–2010 by forcing MAR with different reanalysis products: ERA40/ERA-interim, NCEP/NCAR-v1, ERA-20C, and 20CRV2C. Measurements of Eg↓ from the Global Energy Balance Archive (GEBA) and from the Royal Meteorological Institute of Belgium (RMIB), as well as cloud cover observations from Belgocontrol and RMIB, were used for the evaluation of the MAR model and the forcing reanalyses. Results show that MAR enables largely reducing the mean biases that are present in the reanalyses. The trend analysis shows that only MAR forced by ERA40/ERA-interim shows historical trends, which is probably because the ERA40/ERA-interim has a better horizontal resolution and assimilates more observations than the other reanalyses that are used in this study. The results suggest that the solar brightening observed since the 1980s in Belgium has mainly been due to decreasing cloud cover.

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Characteristics of rainfall events in regional climate model simulations for the Czech Republic

Hydrology and Earth System Sciences ◽

10.5194/hess-21-963-2017 ◽

2017 ◽

Vol 21 (2) ◽

pp. 963-980 ◽

Cited By ~ 5

Author(s):

Vojtěch Svoboda ◽

Martin Hanel ◽

Petr Máca ◽

Jan Kyselý

Keyword(s):

Czech Republic ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Rainfall Event ◽

Spatial Average ◽

Total Precipitation ◽

Rainfall Events ◽

The Czech Republic ◽

Simulated Event

Abstract. Characteristics of rainfall events in an ensemble of 23 regional climate model (RCM) simulations are evaluated against observed data in the Czech Republic for the period 1981–2000. Individual rainfall events are identified using the concept of minimum inter-event time (MIT) and only heavy events (15 % of events with the largest event depths) during the warm season (May–September) are considered. Inasmuch as an RCM grid box represents a spatial average, the effects of areal averaging of rainfall data on characteristics of events are investigated using the observed data. Rainfall events from the RCM simulations are then compared to those from the at-site and area-average observations. Simulated number of heavy events and seasonal total precipitation due to heavy events are on average represented relatively well despite the higher spatial variation compared to observations. RCM-simulated event depths are comparable to the area-average observations, while event durations are overestimated and other characteristics related to rainfall intensity are significantly underestimated. The differences between RCM-simulated and at-site observed rainfall event characteristics are in general dominated by the biases of the climate models rather than the areal-averaging effect. Most of the rainfall event characteristics in the majority of the RCM simulations show a similar altitude-dependence pattern as in the observed data. The number of heavy events and seasonal total precipitation due to heavy events increase with altitude, and this dependence is captured better by the RCM simulations with higher spatial resolution.

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Cascade Use of Wood in the Czech Republic

Forests ◽

10.3390/f11060681 ◽

2020 ◽

Vol 11 (6) ◽

pp. 681

Author(s):

Róbert Babuka ◽

Andrea Sujová ◽

Václav Kupčák

Keyword(s):

Czech Republic ◽

Input Data ◽

Statistical Data ◽

Added Value ◽

Specific Situation ◽

The Czech Republic ◽

Wood Volume ◽

Primary Processing ◽

Wood Processing ◽

Input Method

Research Highlights: One of the priorities of the European Commission is to build up an effective circular economy based on recycling and multiple use of materials. Wood biomass is a renewable raw material and can be used several times in a cascading sequence. Each country has a unique situation regarding the availability and utilization of wood sources. Background and Objectives: The objective of this study was to analyze wood flow in the Czech Republic using the cascading principle of biomass use. The specific situation in the Czech Republic lies in a lack of valid and reliable input data from official statistics. Therefore, the reverse input method was applied. Materials and Methods: Input data analyses of roundwood sources and foreign trade were based on official statistical data. The calculation of raw wood volume consumption in primary processing was performed based on the data after our own correction and recalculation. It was then possible to build up a basic model of multi-stage cascade wood use. The input volume of roundwood was divided among all types of primary processing production using conversion factors. Results: Cascading use of wood (CUW) showed the level of efficiency of the resource. Official statistical input data and the reversed input data regarding raw wood volume entering wood processing revealed differences at a level of 27%. The overall CUW in the Czech Republic indicates a high rate of wood use in primary processing with low added value and in generating energy. Conclusions: The reverse input method reveals the real situation of wood consumption irrespective of the level of official statistical data. It is suitable to apply in an environment of incomplete or incorrect input data. CUW in Czechia showed an opportunity for increasing the efficiency of wood utilization. The structure of wood use needs to be optimized towards creating greater added value.

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Uncovering the shortcomings of a weather typing method

Hydrology and Earth System Sciences ◽

10.5194/hess-24-2671-2020 ◽

2020 ◽

Vol 24 (5) ◽

pp. 2671-2686 ◽

Cited By ~ 1

Author(s):

Els Van Uytven ◽

Jan De Niel ◽

Patrick Willems

Keyword(s):

Statistical Downscaling ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Precipitation Amount ◽

Winter Season ◽

Added Value ◽

Typing Method ◽

Weather Typing ◽

Precipitation Changes

Abstract. In recent years many methods for statistical downscaling of the precipitation climate model outputs have been developed. Statistical downscaling is performed under general and method-specific (structural) assumptions but those are rarely evaluated simultaneously. This paper illustrates the verification and evaluation of the downscaling assumptions for a weather typing method. Using the observations and outputs of a global climate model ensemble, the skill of the method is evaluated for precipitation downscaling in central Belgium during the winter season (December to February). Shortcomings of the studied method have been uncovered and are identified as biases and a time-variant predictor–predictand relationship. The predictor–predictand relationship is found to be informative for historical observations but becomes inaccurate for the projected climate model output. The latter inaccuracy is explained by the increased importance of the thermodynamic processes in the precipitation changes. The results therefore question the applicability of the weather typing method for the case study location. Besides the shortcomings, the results also demonstrate the added value of the Clausius–Clapeyron relationship for precipitation amount scaling. The verification and evaluation of the downscaling assumptions are a tool to design a statistical downscaling ensemble tailored to end-user needs.

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Changes in TRMM Rainfall due to the Orbit Boost Estimated from Buoy Rain Gauge Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech2082.1 ◽

2007 ◽

Vol 24 (9) ◽

pp. 1598-1607 ◽

Cited By ~ 25

Author(s):

Jeremy D. DeMoss ◽

Kenneth P. Bowman

Keyword(s):

Sampling Error ◽

Tropical Rainfall Measuring Mission ◽

Rain Gauge ◽

Rain Gauge Data ◽

Rain Gauges ◽

Rate Dependent ◽

Wide Range ◽

The Mean ◽

Microwave Imager ◽

Trmm Microwave Imager

Abstract During the first three-and-a-half years of the Tropical Rainfall Measuring Mission (TRMM), the TRMM satellite operated at a nominal altitude of 350 km. To reduce drag, save maneuvering fuel, and prolong the mission lifetime, the orbit was boosted to 403 km in August 2001. The change in orbit altitude produced small changes in a wide range of observing parameters, including field-of-view size and viewing angles. Due to natural variability in rainfall and sampling error, it is not possible to evaluate possible changes in rainfall estimates from the satellite data alone. Changes in TRMM Microwave Imager (TMI) and the precipitation radar (PR) precipitation observations due to the orbit boost are estimated by comparing them with surface rain gauges on ocean buoys operated by the NOAA/Pacific Marine Environment Laboratory (PMEL). For each rain gauge, the bias between the satellite and the gauge for pre- and postboost time periods is computed. For the TMI, the satellite is biased ∼12% low relative to the gauges during the preboost period and ∼1% low during the postboost period. The mean change in bias relative to the gauges is approximately 0.4 mm day−1. The change in TMI bias is rain-rate-dependent, with larger changes in areas with higher mean precipitation rates. The PR is biased significantly low relative to the gauges during both boost periods, but the change in bias from the pre- to postboost period is not statistically significant.

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Investigation of Discrepancies in Satellite Rainfall Estimates over Ethiopia

Journal of Hydrometeorology ◽

10.1175/jhm-d-13-0111.1 ◽

2014 ◽

Vol 15 (6) ◽

pp. 2347-2369 ◽

Cited By ~ 31

Author(s):

Matthew P. Young ◽

Charles J. R. Williams ◽

J. Christine Chiu ◽

Ross I. Maidment ◽

Shu-Hua Chen

Keyword(s):

Daily Rainfall ◽

Tropical Rainfall Measuring Mission ◽

Rain Gauge ◽

Rainfall Amount ◽

Shallow Convection ◽

Rain Gauges ◽

The Mean ◽

Satellite Rainfall ◽

Convective Cells ◽

Rainfall Estimates

Abstract Tropical Applications of Meteorology Using Satellite and Ground-Based Observations (TAMSAT) rainfall estimates are used extensively across Africa for operational rainfall monitoring and food security applications; thus, regional evaluations of TAMSAT are essential to ensure its reliability. This study assesses the performance of TAMSAT rainfall estimates, along with the African Rainfall Climatology (ARC), version 2; the Tropical Rainfall Measuring Mission (TRMM) 3B42 product; and the Climate Prediction Center morphing technique (CMORPH), against a dense rain gauge network over a mountainous region of Ethiopia. Overall, TAMSAT exhibits good skill in detecting rainy events but underestimates rainfall amount, while ARC underestimates both rainfall amount and rainy event frequency. Meanwhile, TRMM consistently performs best in detecting rainy events and capturing the mean rainfall and seasonal variability, while CMORPH tends to overdetect rainy events. Moreover, the mean difference in daily rainfall between the products and rain gauges shows increasing underestimation with increasing elevation. However, the distribution in satellite–gauge differences demonstrates that although 75% of retrievals underestimate rainfall, up to 25% overestimate rainfall over all elevations. Case studies using high-resolution simulations suggest underestimation in the satellite algorithms is likely due to shallow convection with warm cloud-top temperatures in addition to beam-filling effects in microwave-based retrievals from localized convective cells. The overestimation by IR-based algorithms is attributed to nonraining cirrus with cold cloud-top temperatures. These results stress the importance of understanding regional precipitation systems causing uncertainties in satellite rainfall estimates with a view toward using this knowledge to improve rainfall algorithms.

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Still too little, too late? Ten years of growth hormone therapy baseline data from the NordiNet® International Outcome Study

Journal of Pediatric Endocrinology and Metabolism ◽

10.1515/jpem-2017-0489 ◽

2018 ◽

Vol 31 (5) ◽

pp. 521-532 ◽

Cited By ~ 3

Author(s):

Michel Polak ◽

Daniel Konrad ◽

Birgitte Tønnes Pedersen ◽

Gediminas Puras ◽

Marta Šnajderová

Keyword(s):

Growth Hormone ◽

Czech Republic ◽

Standard Deviation Score ◽

Outcome Study ◽

Gh Treatment ◽

The Czech Republic ◽

Serbia And Montenegro ◽

The Mean ◽

Late Start ◽

The Uk

AbstractBackground:We investigated time trends in age, gender, growth hormone (GH) dose and height standard deviation score (SDS) in children with GH deficiency (GHD), born small for gestational age (SGA) or with Turner syndrome (TS) starting GH treatment.Methods:Data were obtained from children enrolled in the NordiNet®International Outcome Study (IOS) between 2006 and 2015 in the Czech Republic, France, Germany, Serbia and Montenegro (all indications), and Switzerland and the UK (GHD only). Trends were analyzed by linear regression. Patients were divided by age into early-, medium- or late-start groups in three different time periods.Results:Approximately one-third of children starting treatment for GHD were girls, with no apparent increase in proportion over time. The mean baseline age for starting treatment decreased significantly (p<0.001) for both GHD and SGA in the Czech Republic and Germany. In the other countries studied, over 40% of children started treatment for GHD and SGA late (girls >10, boys >11 years) between 2013 and 2015. The mean baseline GH doses were largely within recommended ranges for GHD and SGA, but below the lowest recommended starting dose for TS in almost every year since 2011 except in France.Conclusions:Approximately one-third of children starting treatment for GHD were girls. Between 2013 and 2015, more than 40% of children started treatment for GHD and SGA late except in Germany and the Czech Republic. TS patients received below-recommended doses. These results highlight the need for earlier identification of short stature in children, particularly girls, and for dose optimization in TS.

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Comparison of the growth pattern of black walnut (Juglans nigra L.) in two riparian forests in the region of South Moravia, Czech Republic

Journal of Forest Science ◽

10.17221/61/2010-jfs ◽

2011 ◽

Vol 57 (No. 3) ◽

pp. 107-113 ◽

Cited By ~ 1

Author(s):

L. Šálek ◽

P. Hejcmanová

Keyword(s):

Czech Republic ◽

Growth Pattern ◽

Tree Height ◽

Management Plan ◽

Black Walnut ◽

Riparian Forests ◽

Juglans Nigra ◽

The Czech Republic ◽

The Mean ◽

South Moravia

The black walnut (Juglans nigra L.), an introduced species into the Czech Republic, is planted for its production of valuable timber. A systematic study of the black walnut growth rate at different localities and consequently the creation of standard volume tables under Central European conditions therefore appear to be of high relevance. The aim of our study was to reveal the black walnut growth pattern in its pure stands in two riparian forests along the Morava and Svratka River (Strážnice locality and Židlochovice locality, respectively). To describe and to compare relationships among diameter at breast height (dbh), tree height and age, we used a forest management plan and measured 573 and 670 trees in pure sample stands at Strážnice and Židlochovice, respectively. We found out that the measured mean DBH and mean height were consistently higher in Strážnice, however the relationships of DBH to height, age to DBH, and age to height showed the same pattern at both localities. The mean heights of trees were 16.3, 24.1, 28.7, 31.9, and 34.5 m in 20, 40, 60, 80, and 100 year age classes and were consistently taller in comparison with other, mainly European, regions. Therefore our results suggest the high potential of black walnut in timber production in riparian forests in the Czech Republic, mainly in the South Moravian region.

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