Articles | Volume 14, issue 8
https://doi.org/10.5194/amt-14-5735-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-5735-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Aug 2021
Research article |
| 20 Aug 2021
| 20 Aug 2021
Interpreting estimated observation error statistics of weather radar measurements using the ICON-LAM-KENDA system
Yuefei Zeng
Meteorologisches Institut, Ludwig-Maximilians-Universität (LMU) München, Munich, Germany
Tijana Janjic
Meteorologisches Institut, Ludwig-Maximilians-Universität (LMU) München, Munich, Germany
Yuxuan Feng
CORRESPONDING AUTHOR
Meteorologisches Institut, Ludwig-Maximilians-Universität (LMU) München, Munich, Germany
Key Laboratory of Meteorological Disaster of Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China
Ulrich Blahak
Deutscher Wetterdienst, Offenbach, Germany
Alberto de Lozar
Deutscher Wetterdienst, Offenbach, Germany
Elisabeth Bauernschubert
Deutscher Wetterdienst, Offenbach, Germany
Klaus Stephan
Deutscher Wetterdienst, Offenbach, Germany
Jinzhong Min
Key Laboratory of Meteorological Disaster of Ministry of Education/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China
Related authors
Yongbo Zhou, Yubao Liu, Wei Han, Yuefei Zeng, Haofei Sun, and Peilong Yu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-12, https://doi.org/10.5194/amt-2024-12, 2024
Preprint under review for AMT
Short summary
Short summary
This study reported a method to evaluate the performance of the FY-4A visible instrument and to correct the systematic biases in the visible radiances. The method involves the equivalents derived from the forecasts of the CMA-MESO model using a fast forward operator. After applying the method, the biases in the observations were corrected and the Gaussianess of the observation errors was better respected. The findings facilitate the data assimilation of these data using conventional methods.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
Short summary
Short summary
The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Yuefei Zeng, Alberto de Lozar, Tijana Janjic, and Axel Seifert
Geosci. Model Dev., 14, 1295–1307, https://doi.org/10.5194/gmd-14-1295-2021, https://doi.org/10.5194/gmd-14-1295-2021, 2021
Short summary
Short summary
A new integrated mass-flux adjustment filter is introduced and examined with an idealized setup for convective-scale radar data assimilation. It is found that the new filter slightly reduces the accuracy of background and analysis states; however, it preserves the main structure of cold pools and primary mesocyclone properties of supercells. More importantly, it successfully diminishes the imbalance in the analysis considerably and improves the forecasts.
Yongbo Zhou, Yubao Liu, Wei Han, Yuefei Zeng, Haofei Sun, and Peilong Yu
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-12, https://doi.org/10.5194/amt-2024-12, 2024
Preprint under review for AMT
Short summary
Short summary
This study reported a method to evaluate the performance of the FY-4A visible instrument and to correct the systematic biases in the visible radiances. The method involves the equivalents derived from the forecasts of the CMA-MESO model using a fast forward operator. After applying the method, the biases in the observations were corrected and the Gaussianess of the observation errors was better respected. The findings facilitate the data assimilation of these data using conventional methods.
Hyunju Jung, Peter Knippertz, Yvonne Ruckstuhl, Robert Redl, Tijana Janjic, and Corinna Hoose
Weather Clim. Dynam., 4, 1111–1134, https://doi.org/10.5194/wcd-4-1111-2023, https://doi.org/10.5194/wcd-4-1111-2023, 2023
Short summary
Short summary
A narrow rainfall belt in the tropics is an important feature for large-scale circulations and the global water cycle. The accurate simulation of this rainfall feature has been a long-standing problem, with the reasons behind that unclear. We present a novel diagnostic tool that allows us to disentangle processes important for rainfall, which changes due to modifications in model. Using our diagnostic tool, one can potentially identify sources of uncertainty in weather and climate models.
Prabhakar Shrestha, Jana Mendrok, Velibor Pejcic, Silke Trömel, Ulrich Blahak, and Jacob T. Carlin
Geosci. Model Dev., 15, 291–313, https://doi.org/10.5194/gmd-15-291-2022, https://doi.org/10.5194/gmd-15-291-2022, 2022
Short summary
Short summary
The article focuses on the exploitation of radar polarimetry for model evaluation of stratiform precipitation. The model exhibited a low bias in simulated polarimetric moments at lower levels above the melting layer where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models in the forward operator to draw valid conclusions.
Silke Trömel, Clemens Simmer, Ulrich Blahak, Armin Blanke, Sabine Doktorowski, Florian Ewald, Michael Frech, Mathias Gergely, Martin Hagen, Tijana Janjic, Heike Kalesse-Los, Stefan Kneifel, Christoph Knote, Jana Mendrok, Manuel Moser, Gregor Köcher, Kai Mühlbauer, Alexander Myagkov, Velibor Pejcic, Patric Seifert, Prabhakar Shrestha, Audrey Teisseire, Leonie von Terzi, Eleni Tetoni, Teresa Vogl, Christiane Voigt, Yuefei Zeng, Tobias Zinner, and Johannes Quaas
Atmos. Chem. Phys., 21, 17291–17314, https://doi.org/10.5194/acp-21-17291-2021, https://doi.org/10.5194/acp-21-17291-2021, 2021
Short summary
Short summary
The article introduces the ACP readership to ongoing research in Germany on cloud- and precipitation-related process information inherent in polarimetric radar measurements, outlines pathways to inform atmospheric models with radar-based information, and points to remaining challenges towards an improved fusion of radar polarimetry and atmospheric modelling.
Stefan Geiss, Leonhard Scheck, Alberto de Lozar, and Martin Weissmann
Atmos. Chem. Phys., 21, 12273–12290, https://doi.org/10.5194/acp-21-12273-2021, https://doi.org/10.5194/acp-21-12273-2021, 2021
Short summary
Short summary
This study demonstrates the benefits of using both visible and infrared satellite channels to evaluate clouds in numerical weather prediction models. Combining these highly resolved observations provides significantly more and complementary information than using only infrared observations. The visible observations are particularly sensitive to subgrid water clouds, which are not well constrained by other observations.
Yuefei Zeng, Alberto de Lozar, Tijana Janjic, and Axel Seifert
Geosci. Model Dev., 14, 1295–1307, https://doi.org/10.5194/gmd-14-1295-2021, https://doi.org/10.5194/gmd-14-1295-2021, 2021
Short summary
Short summary
A new integrated mass-flux adjustment filter is introduced and examined with an idealized setup for convective-scale radar data assimilation. It is found that the new filter slightly reduces the accuracy of background and analysis states; however, it preserves the main structure of cold pools and primary mesocyclone properties of supercells. More importantly, it successfully diminishes the imbalance in the analysis considerably and improves the forecasts.
Yvonne Ruckstuhl, Tijana Janjić, and Stephan Rasp
Nonlin. Processes Geophys., 28, 111–119, https://doi.org/10.5194/npg-28-111-2021, https://doi.org/10.5194/npg-28-111-2021, 2021
Short summary
Short summary
The assimilation of observations using standard algorithms can lead to a violation of physical laws (e.g. mass conservation), which is shown to have a detrimental impact on the system's forecast. We use a neural network (NN) to correct this mass violation, using training data generated from expensive algorithms that can constrain such physical properties. We found that, in an idealized set-up, the NN can match the performance of these expensive algorithms at negligible computational costs.
Michael Weger, Bernd Heinold, Christa Engler, Ulrich Schumann, Axel Seifert, Romy Fößig, Christiane Voigt, Holger Baars, Ulrich Blahak, Stephan Borrmann, Corinna Hoose, Stefan Kaufmann, Martina Krämer, Patric Seifert, Fabian Senf, Johannes Schneider, and Ina Tegen
Atmos. Chem. Phys., 18, 17545–17572, https://doi.org/10.5194/acp-18-17545-2018, https://doi.org/10.5194/acp-18-17545-2018, 2018
Short summary
Short summary
The impact of desert dust on cloud formation is investigated for a major Saharan dust event over Europe by interactive regional dust modeling. Dust particles are very efficient ice-nucleating particles promoting the formation of ice crystals in clouds. The simulations show that the observed extensive cirrus development was likely related to the above-average dust load. The interactive dust–cloud feedback in the model significantly improves the agreement with aircraft and satellite observations.
Hendrik Wouters, Matthias Demuzere, Ulrich Blahak, Krzysztof Fortuniak, Bino Maiheu, Johan Camps, Daniël Tielemans, and Nicole P. M. van Lipzig
Geosci. Model Dev., 9, 3027–3054, https://doi.org/10.5194/gmd-9-3027-2016, https://doi.org/10.5194/gmd-9-3027-2016, 2016
Short summary
Short summary
A methodology is presented for translating three-dimensional information of urban areas into land-surface parameters that can be easily employed in atmospheric modelling. As demonstrated with the COSMO-CLM model for a Belgian summer, it enables them to represent urban heat islands and their dependency on urban design with a low computational cost. It allows for efficiently incorporating urban information systems (e.g., WUDAPT) into climate change assessment and numerical weather prediction.
Y. Bao, J. Xu, A. M. Powell Jr., M. Shao, J. Min, and Y. Pan
Atmos. Meas. Tech., 8, 4231–4242, https://doi.org/10.5194/amt-8-4231-2015, https://doi.org/10.5194/amt-8-4231-2015, 2015
Short summary
Short summary
The regional GSI-WRF system is underestimating the observed temperature in the LT and overestimating in the UT and LS. The microwave (MW) data assimilation (DA) reduced the forecast bias from the MT to the LS within 30-hour forecasts, and the conventional (CON) DA kept a smaller forecast bias in the LT for 2-day forecasts.
The smallest bias in the humidity forecast occurred at the surface and in the UT. The DA experiments apparently reduced the bias from the LT to UT, especially for the IR DA.
A. Seifert, U. Blahak, and R. Buhr
Geosci. Model Dev., 7, 463–478, https://doi.org/10.5194/gmd-7-463-2014, https://doi.org/10.5194/gmd-7-463-2014, 2014
Related subject area
Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Atmospheric motion vector (AMV) error characterization and bias correction by leveraging independent lidar data: a simulation using an observing system simulation experiment (OSSE) and optical flow AMVs
Rotary-wing drone-induced flow – comparison of simulations with lidar measurements
Application of Doppler sodar in short-term forecasting of PM10 concentration in the air in Krakow (Poland)
Radiative closure tests of collocated hyperspectral microwave and infrared radiometers
Effects of clouds and aerosols on downwelling surface solar irradiance nowcasting and short-term forecasting
A comprehensive verification of the weather radar-based hail metrics POH and MESHS and a recalibration of POH using dense crowdsourced observations from Switzerland
Verification of parameterizations for clear sky downwelling longwave irradiance in the Arctic
Global evaluation of fast radiative transfer model coefficients for early meteorological satellite sensors
GPROF V7 and beyond: assessment of current and potential future versions of the GPROF passive microwave precipitation retrievals against ground radar measurements over the continental US and the Pacific Ocean
Assessing sampling and retrieval errors of GPROF precipitation estimates over the Netherlands
Comparisons and quality control of wind observations in a mountainous city using wind profile radar and the Aeolus satellite
On the use of routine airborne observations for evaluation and monitoring of satellite observations of thermodynamic profiles
Daily satellite-based sunshine duration estimates over Brazil: validation and intercomparison
Statistical assessment of a Doppler radar model of TKE dissipation rate for low Richardson numbers
Extended validation of Aeolus winds with wind-profiling radars in Antarctica and Arctic Sweden
The impact of Aeolus winds on near-surface wind forecasts over tropical ocean and high-latitude regions
Long-term validation of Aeolus L2B wind products at Punta Arenas, Chile, and Leipzig, Germany
Turbulence kinetic energy dissipation rate: assessment of radar models from comparisons between 1.3 GHz wind profiler radar (WPR) and DataHawk UAV measurements
The impacts of assimilating Aeolus horizontal line-of-sight winds on numerical predictions of Hurricane Ida (2021) and a mesoscale convective system over the Atlantic Ocean
Evaluation of tropospheric water vapour and temperature profiles retrieved from MetOp-A by the Infrared and Microwave Sounding scheme
Validation of the Aeolus L2B wind product with airborne wind lidar measurements in the polar North Atlantic region and in the tropics
An improved vertical correction method for the inter-comparison and inter-validation of integrated water vapour measurements
An assessment of reprocessed GPS/MET observations spanning 1995–1997
Turbulence parameters measured by the Beijing mesosphere–stratosphere–troposphere radar in the troposphere and lower stratosphere with three models: comparison and analyses
Comparison of planetary boundary layer height from ceilometer with ARM radiosonde data
Behavior and mechanisms of Doppler wind lidar error in varying stability regimes
Inter-comparison of atmospheric boundary layer (ABL) height estimates from different profiling sensors and models in the framework of HyMeX-SOP1
Evaluation of Aeolus L2B wind product with wind profiling radar measurements and numerical weather prediction model equivalents over Australia
Comparison of global UV spectral irradiance measurements between a BTS CCD-array and a Brewer spectroradiometer
Scan strategies for wind profiling with Doppler lidar – an large-eddy simulation (LES)-based evaluation
Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty
Modelling the spectral shape of continuous-wave lidar measurements in a turbulent wind tunnel
Three-way calibration checks using ground-based, ship-based, and spaceborne radars
Rainfall retrieval algorithm for commercial microwave links: stochastic calibration
Inter-comparison of wind measurements in the atmospheric boundary layer and the lower troposphere with Aeolus and a ground-based coherent Doppler lidar network over China
Towards operational multi-GNSS tropospheric products at GFZ Potsdam
Validation of Aeolus Level 2B wind products using wind profilers, ground-based Doppler wind lidars, and radiosondes in Japan
Monitoring the Tropospheric Monitoring Instrument (TROPOMI) short-wave infrared (SWIR) module instrument stability using desert sites
Evaluating the use of Aeolus satellite observations in the regional numerical weather prediction (NWP) model Harmonie–Arome
Validation of Aeolus winds using ground-based radars in Antarctica and in northern Sweden
Intercomparison review of IPWV retrieved from INSAT-3DR sounder, GNSS and CAMS reanalysis data
Sensitivity of Aeolus HLOS winds to temperature and pressure specification in the L2B processor
Airborne lidar observations of wind, water vapor, and aerosol profiles during the NASA Aeolus calibration and validation (Cal/Val) test flight campaign
Improved method of estimating temperatures at meteor peak heights
Error analyses of a multistatic meteor radar system to obtain a three-dimensional spatial-resolution distribution
Validation of wind measurements of two mesosphere–stratosphere–troposphere radars in northern Sweden and in Antarctica
Performance evaluation of multiple satellite rainfall products for Dhidhessa River Basin (DRB), Ethiopia
A 2-year intercomparison of continuous-wave focusing wind lidar and tall mast wind measurements at Cabauw
Using machine learning to model uncertainty for water vapor atmospheric motion vectors
Validation of pure rotational Raman temperature data from the Raman Lidar for Meteorological Observations (RALMO) at Payerne
Hai Nguyen, Derek Posselt, Igor Yanovsky, Longtao Wu, and Svetla Hristova-Veleva
Atmos. Meas. Tech., 17, 3103–3119, https://doi.org/10.5194/amt-17-3103-2024, https://doi.org/10.5194/amt-17-3103-2024, 2024
Short summary
Short summary
Accurate global wind estimation is crucial for weather prediction and environmental modeling. Our study investigates a method to refine atmospheric motion vectors (AMVs) by comparing them with high-precision active-sensor winds. Leveraging supervised learning, we discovered that using high-precision active-sensor data can significantly reduce biases in passive-sensor winds in addition to providing estimates of the wind errors, thereby improving their reliability.
Liqin Jin, Mauro Ghirardelli, Jakob Mann, Mikael Sjöholm, Stephan Thomas Kral, and Joachim Reuder
Atmos. Meas. Tech., 17, 2721–2737, https://doi.org/10.5194/amt-17-2721-2024, https://doi.org/10.5194/amt-17-2721-2024, 2024
Short summary
Short summary
Three-dimensional wind fields can be accurately measured by sonic anemometers. However, the traditional mast-mounted sonic anemometers are not flexible in various applications, which can be potentially overcome by drones. Therefore, we conducted a proof-of-concept study by applying three continuous-wave Doppler lidars to characterize the complex flow around a drone to validate the results obtained by CFD simulations. Both methods show good agreement, with a velocity difference of 0.1 m s-1.
Ewa Agnieszka Krajny, Leszek Ośródka, and Marek Jan Wojtylak
Atmos. Meas. Tech., 17, 2451–2464, https://doi.org/10.5194/amt-17-2451-2024, https://doi.org/10.5194/amt-17-2451-2024, 2024
Short summary
Short summary
The use of sodar data to support an air quality forecasting system is encouraging.
The sodar model is a complement to forecasting methods because it is useful due to its simplicity and speed of calculations. It does not require emission data, for which it is difficult to quickly verify temporal and spatial variability.
The use of simple formulas of regression models in forecasting, while maintaining their multivariate nature, facilitates the optimisation of the prediction process.
Lei Liu, Natalia Bliankinshtein, Yi Huang, John R. Gyakum, Philip M. Gabriel, Shiqi Xu, and Mengistu Wolde
Atmos. Meas. Tech., 17, 2219–2233, https://doi.org/10.5194/amt-17-2219-2024, https://doi.org/10.5194/amt-17-2219-2024, 2024
Short summary
Short summary
We conducted a radiance closure experiment using a unique combination of two hyperspectral radiometers, one operating in the microwave and the other in the infrared. By comparing the measurements of the two hyperspectrometers to synthetic radiance simulated from collocated atmospheric profiles, we affirmed the proper performance of the two instruments and quantified their radiometric uncertainty for atmospheric sounding applications.
Kyriakoula Papachristopoulou, Ilias Fountoulakis, Alkiviadis F. Bais, Basil E. Psiloglou, Nikolaos Papadimitriou, Ioannis-Panagiotis Raptis, Andreas Kazantzidis, Charalampos Kontoes, Maria Hatzaki, and Stelios Kazadzis
Atmos. Meas. Tech., 17, 1851–1877, https://doi.org/10.5194/amt-17-1851-2024, https://doi.org/10.5194/amt-17-1851-2024, 2024
Short summary
Short summary
The upgraded systems SENSE2 and NextSENSE2 focus on improving the quality of solar nowcasting and forecasting. SENSE2 provides real-time estimates of solar irradiance across a wide region every 15 min. NextSENSE2 offers short-term forecasts of irradiance up to 3 h ahead. Evaluation with actual data showed that the instantaneous comparison yields the most discrepancies due to the uncertainties of cloud-related information and satellite versus ground-based spatial representativeness limitations.
Jérôme Kopp, Alessandro Hering, Urs Germann, and Olivia Martius
EGUsphere, https://doi.org/10.5194/egusphere-2024-729, https://doi.org/10.5194/egusphere-2024-729, 2024
Short summary
Short summary
We present a verification of two products based on weather radars to detect the presence of hail and estimate its size. Radar products are remote detection of hail, so they must be verified with ground-based observations. We use reports from users of the Swiss Weather Services phone app to do the verification. We found that the product estimating the presence of hail provides fair results but that it should be recalibrated, and that estimating the hail size with radar is more challenging.
Giandomenico Pace, Alcide di Sarra, Filippo Cali Quaglia, Virginia Ciardini, Tatiana Di Iorio, Antonio Iaccarino, Daniela Meloni, Giovanni Muscari, and Claudio Scarchilli
Atmos. Meas. Tech., 17, 1617–1632, https://doi.org/10.5194/amt-17-1617-2024, https://doi.org/10.5194/amt-17-1617-2024, 2024
Short summary
Short summary
This study investigates the performances of 17 formulas to determine the clear sky longwave downward irradiance in the Arctic environment. The formulas need to be tuned to the environmental conditions of the studied region and, to date, few of them have been developed and/or tested in the Arctic. The best formulas provide biases and root mean squared errors respectively smaller than 1 and 5 W m-2. We intend to use these results to estimate the longwave cloud radiative perturbation.
Bruna Barbosa Silveira, Emma Catherine Turner, and Jérôme Vidot
Atmos. Meas. Tech., 17, 1279–1296, https://doi.org/10.5194/amt-17-1279-2024, https://doi.org/10.5194/amt-17-1279-2024, 2024
Short summary
Short summary
A fast radiative transfer model, used to speed up the full spectral simulation of meteorological satellite channels in weather forecast models, is tested using 25 000 modelled atmospheres. The differences between calculations from the fast and the high-resolution reference models are examined for nine historic weather satellite instruments. The study confirms that a reduced set of 83 atmospheric profiles is robust enough to estimate the scale of the differences obtained from the larger sample.
Simon Pfreundschuh, Clément Guilloteau, Paula J. Brown, Christian D. Kummerow, and Patrick Eriksson
Atmos. Meas. Tech., 17, 515–538, https://doi.org/10.5194/amt-17-515-2024, https://doi.org/10.5194/amt-17-515-2024, 2024
Short summary
Short summary
The latest version of the GPROF retrieval algorithm that produces global precipitation estimates using observations from the Global Precipitation Measurement mission is validated against ground-based radars. The validation shows that the algorithm accurately estimates precipitation on scales ranging from continental to regional. In addition, we validate candidates for the next version of the algorithm and identify principal challenges for further improving space-borne rain measurements.
Linda Bogerd, Hidde Leijnse, Aart Overeem, and Remko Uijlenhoet
Atmos. Meas. Tech., 17, 247–259, https://doi.org/10.5194/amt-17-247-2024, https://doi.org/10.5194/amt-17-247-2024, 2024
Short summary
Short summary
Algorithms merge satellite radiometer data from various frequency channels, each tied to a different footprint size. We studied the uncertainty associated with sampling (over the Netherlands using 4 years of data) as precipitation is highly variable in space and time by simulating ground-based data as satellite footprints. Though sampling affects precipitation estimates, it doesn’t explain all discrepancies. Overall, uncertainties in the algorithm seem more influential than how data is sampled.
Hua Lu, Min Xie, Wei Zhao, Bojun Liu, Tijian Wang, and Bingliang Zhuang
Atmos. Meas. Tech., 17, 167–179, https://doi.org/10.5194/amt-17-167-2024, https://doi.org/10.5194/amt-17-167-2024, 2024
Short summary
Short summary
Observations of vertical wind in regions with complex terrain are essential, but they are always sparse and have poor representation. Data verification and quality control are conducted on the wind profile radar and Aeolus wind products in this study, trying to compensate for the limitations of wind field observations. The results shed light on the comprehensive applications of multi-source wind profile data in complicated terrain regions with sparse ground-based wind observations.
Timothy J. Wagner, Thomas August, Tim Hultberg, and Ralph A. Petersen
Atmos. Meas. Tech., 17, 1–14, https://doi.org/10.5194/amt-17-1-2024, https://doi.org/10.5194/amt-17-1-2024, 2024
Short summary
Short summary
Commercial passenger and freight aircraft need to know the temperature and pressure of the environments they fly through in order to safely operate. In this paper, we investigate how these observations can be used to evaluate and monitor the performance of satellite observations. Normally weather balloons are used for this, but in places like the United States there are many more airplane flights than weather balloon launches. This makes it much easier to compare them to satellites.
Maria Lívia L. M. Gava, Simone M. S. Costa, and Anthony C. S. Porfírio
Atmos. Meas. Tech., 16, 5429–5441, https://doi.org/10.5194/amt-16-5429-2023, https://doi.org/10.5194/amt-16-5429-2023, 2023
Short summary
Short summary
This study assesses the effectiveness of two geostationary satellite-based sunshine duration datasets over Brazil. Statistical parameters were used to evaluate the performance of the products. The results showed generally good agreement between satellite and ground observations, with some regional discrepancies. Overall, both satellite products offer reliable data for various applications, which benefit from their high spatial resolution and low time latency.
Hubert Luce, Lakshmi Kantha, and Hiroyuki Hashiguchi
Atmos. Meas. Tech., 16, 5091–5101, https://doi.org/10.5194/amt-16-5091-2023, https://doi.org/10.5194/amt-16-5091-2023, 2023
Short summary
Short summary
The potential ability of clear air radars to measure turbulence kinetic energy (TKE) dissipation rate ε in the atmosphere is a major asset of these instruments because of their continuous measurements. In the present work, we successfully tested the relevance of a model relating ε to the width of the Doppler spectrum peak and wind shear for shear-generated turbulence and we provide a physical interpretation of an empirical model in this context.
Sheila Kirkwood, Evgenia Belova, Peter Voelger, Sourav Chatterjee, and Karathazhiyath Satheesan
Atmos. Meas. Tech., 16, 4215–4227, https://doi.org/10.5194/amt-16-4215-2023, https://doi.org/10.5194/amt-16-4215-2023, 2023
Short summary
Short summary
We compared 2 years of wind measurements by the Aeolus satellite with winds from two wind-profiler radars in Arctic Sweden and coastal Antarctica. Biases are similar in magnitude to results from other locations. They are smaller than in earlier studies due to more comparison points and improved criteria for data rejection. On the other hand, the standard deviation is somewhat higher because of degradation of the Aeolus lidar.
Haichen Zuo and Charlotte Bay Hasager
Atmos. Meas. Tech., 16, 3901–3913, https://doi.org/10.5194/amt-16-3901-2023, https://doi.org/10.5194/amt-16-3901-2023, 2023
Short summary
Short summary
Aeolus is a satellite equipped with a Doppler wind lidar to detect global wind profiles. This study evaluates the impact of Aeolus winds on surface wind forecasts over tropical oceans and high-latitude regions based on the ECMWF observing system experiments. We find that Aeolus can slightly improve surface wind forecasts for the region > 60° N, especially from day 5 onwards. For other study regions, the impact of Aeolus is nearly neutral or limited, which requires further investigation.
Holger Baars, Joshua Walchester, Elizaveta Basharova, Henriette Gebauer, Martin Radenz, Johannes Bühl, Boris Barja, Ulla Wandinger, and Patric Seifert
Atmos. Meas. Tech., 16, 3809–3834, https://doi.org/10.5194/amt-16-3809-2023, https://doi.org/10.5194/amt-16-3809-2023, 2023
Short summary
Short summary
In 2018, the Aeolus satellite of the European Space Agency (ESA) was launched to improve weather forecasts through global measurements of wind profiles. Given the novel lidar technique onboard, extensive validation efforts have been needed to verify the observations. For this reason, we performed long-term validation measurements in Germany and Chile. We found significant improvement in the data products due to a new algorithm version and can confirm the general validity of Aeolus observations.
Hubert Luce, Lakshmi Kantha, Hiroyuki Hashiguchi, Dale Lawrence, Abhiram Doddi, Tyler Mixa, and Masanori Yabuki
Atmos. Meas. Tech., 16, 3561–3580, https://doi.org/10.5194/amt-16-3561-2023, https://doi.org/10.5194/amt-16-3561-2023, 2023
Short summary
Short summary
Doppler radars can be used to estimate turbulence kinetic energy dissipation rates in the atmosphere. The performance of various models is evaluated from comparisons between UHF wind profiler and in situ measurements with UAVs. For the first time, we assess a model supposed to be valid for weak stratification or strong shear conditions. This model provides better agreements with in situ measurements than the classical model based on the hypothesis of a stable stratification.
Chengfeng Feng and Zhaoxia Pu
Atmos. Meas. Tech., 16, 2691–2708, https://doi.org/10.5194/amt-16-2691-2023, https://doi.org/10.5194/amt-16-2691-2023, 2023
Short summary
Short summary
This study demonstrates the positive impacts of assimilating Aeolus Mie-cloudy and Rayleigh-clear near-real-time horizontal line-of-sight winds on the analysis and forecasts of Hurricane Ida (2021) and a mesoscale convective system associated with an African easterly wave using the mesoscale community Weather Research and Forecasting model and the NCEP Gridpoint Statistical Interpolation-based three-dimensional ensemble-variational hybrid data assimilation system.
Tim Trent, Richard Siddans, Brian Kerridge, Marc Schröder, Noëlle A. Scott, and John Remedios
Atmos. Meas. Tech., 16, 1503–1526, https://doi.org/10.5194/amt-16-1503-2023, https://doi.org/10.5194/amt-16-1503-2023, 2023
Short summary
Short summary
Modern weather satellites provide essential information on our lower atmosphere's moisture content and temperature structure. This measurement record will span over 40 years, making it a valuable resource for climate studies. This study characterizes atmospheric temperature and humidity profiles from a European Space Agency climate project. Using weather balloon measurements, we demonstrated the performance of this dataset was within the tolerances required for future climate studies.
Benjamin Witschas, Christian Lemmerz, Alexander Geiß, Oliver Lux, Uwe Marksteiner, Stephan Rahm, Oliver Reitebuch, Andreas Schäfler, and Fabian Weiler
Atmos. Meas. Tech., 15, 7049–7070, https://doi.org/10.5194/amt-15-7049-2022, https://doi.org/10.5194/amt-15-7049-2022, 2022
Short summary
Short summary
In August 2018, the first wind lidar Aeolus was launched into space and has since then been providing data of the global wind field. The primary goal of Aeolus was the improvement of numerical weather prediction. To verify the quality of Aeolus wind data, DLR performed four airborne validation campaigns with two wind lidar systems. In this paper, we report on results from the two later campaigns, performed in Iceland and the tropics.
Olivier Bock, Pierre Bosser, and Carl Mears
Atmos. Meas. Tech., 15, 5643–5665, https://doi.org/10.5194/amt-15-5643-2022, https://doi.org/10.5194/amt-15-5643-2022, 2022
Short summary
Short summary
Integrated water vapour measurements are often compared for the calibration and validation of instruments or techniques. Measurements made at different altitudes must be corrected to account for the vertical variation of water vapour. This paper shows that the widely used empirical correction model has severe limitations that are overcome using the proposed model. The method is applied to the inter-comparison of GPS and satellite microwave radiometer data in a tropical mountainous area.
Anthony J. Mannucci, Chi O. Ao, Byron A. Iijima, Thomas K. Meehan, Panagiotis Vergados, E. Robert Kursinski, and William S. Schreiner
Atmos. Meas. Tech., 15, 4971–4987, https://doi.org/10.5194/amt-15-4971-2022, https://doi.org/10.5194/amt-15-4971-2022, 2022
Short summary
Short summary
The Global Positioning System (GPS) radio occultation (RO) technique is a satellite-based method for producing highly accurate vertical profiles of atmospheric temperature and pressure. RO profiles are used to monitor global climate trends, particularly in that region of the atmosphere that includes the lower stratosphere. Two data sets spanning 1995–1997 that were produced from the first RO satellite are highly accurate and can be used to assess global atmospheric models.
Ze Chen, Yufang Tian, Yinan Wang, Yongheng Bi, Xue Wu, Juan Huo, Linjun Pan, Yong Wang, and Daren Lü
Atmos. Meas. Tech., 15, 4785–4800, https://doi.org/10.5194/amt-15-4785-2022, https://doi.org/10.5194/amt-15-4785-2022, 2022
Short summary
Short summary
Small-scale turbulence plays a vital role in the vertical exchange of heat, momentum and mass in the atmosphere. There are currently three models that can use spectrum width data of MST radar to calculate turbulence parameters. However, few studies have explored the applicability of the three calculation models. We compared and analysed the turbulence parameters calculated by three models. These results can provide a reference for the selection of models for calculating turbulence parameters.
Damao Zhang, Jennifer Comstock, and Victor Morris
Atmos. Meas. Tech., 15, 4735–4749, https://doi.org/10.5194/amt-15-4735-2022, https://doi.org/10.5194/amt-15-4735-2022, 2022
Short summary
Short summary
The planetary boundary layer is the lowest part of the atmosphere. Its structure and depth (PBLHT) significantly impact air quality, global climate, land–atmosphere interactions, and a wide range of atmospheric processes. To test the robustness of the ceilometer-estimated PBLHT under different atmospheric conditions, we compared ceilometer- and radiosonde-estimated PBLHTs using multiple years of U.S. DOE ARM measurements at various ARM observatories located around the world.
Rachel Robey and Julie K. Lundquist
Atmos. Meas. Tech., 15, 4585–4622, https://doi.org/10.5194/amt-15-4585-2022, https://doi.org/10.5194/amt-15-4585-2022, 2022
Short summary
Short summary
Our work investigates the behavior of errors in remote-sensing wind lidar measurements due to turbulence. Using a virtual instrument, we measured winds in simulated atmospheric flows and decomposed the resulting error. Dominant error mechanisms, particularly vertical velocity variations and interactions with shear, were identified in ensemble data over three test cases. By analyzing the underlying mechanisms, the response of the error behavior to further varying flow conditions may be projected.
Donato Summa, Fabio Madonna, Noemi Franco, Benedetto De Rosa, and Paolo Di Girolamo
Atmos. Meas. Tech., 15, 4153–4170, https://doi.org/10.5194/amt-15-4153-2022, https://doi.org/10.5194/amt-15-4153-2022, 2022
Short summary
Short summary
The evolution of the atmospheric boundary layer height (ABLH) has an important impact on meteorology. However, the complexity of the phenomena occurring within the ABL and the influence of advection and local accumulation processes often prevent an unambiguous determination of the ABLH. The paper reports results from an inter-comparison effort involving different sensors and techniques to measure the ABLH. Correlations between the ABLH and other atmospheric variables are also assessed.
Haichen Zuo, Charlotte Bay Hasager, Ioanna Karagali, Ad Stoffelen, Gert-Jan Marseille, and Jos de Kloe
Atmos. Meas. Tech., 15, 4107–4124, https://doi.org/10.5194/amt-15-4107-2022, https://doi.org/10.5194/amt-15-4107-2022, 2022
Short summary
Short summary
The Aeolus satellite was launched in 2018 for global wind profile measurement. After successful operation, the error characteristics of Aeolus wind products have not yet been studied over Australia. To complement earlier validation studies, we evaluated the Aeolus Level-2B11 wind product over Australia with ground-based wind profiling radar measurements and numerical weather prediction model equivalents. The results show that the Aeolus can detect winds with sufficient accuracy over Australia.
Carmen González, José M. Vilaplana, José A. Bogeat, and Antonio Serrano
Atmos. Meas. Tech., 15, 4125–4133, https://doi.org/10.5194/amt-15-4125-2022, https://doi.org/10.5194/amt-15-4125-2022, 2022
Short summary
Short summary
Monitoring ultraviolet (UV) radiation is important since it can have harmful effects on the biosphere. Array spectroradiometers are increasingly used to measure UV as they are more versatile than scanning spectroradiometers. In this study, the long-term performance of the BTS-2048-UV-S-WP array spectroradiometer was assessed. The results show that the BTS can reliably measure both the UV index and UV radiation in the 300–360 nm range. Moreover, the BTS was stable and showed no seasonal behavior.
Charlotte Rahlves, Frank Beyrich, and Siegfried Raasch
Atmos. Meas. Tech., 15, 2839–2856, https://doi.org/10.5194/amt-15-2839-2022, https://doi.org/10.5194/amt-15-2839-2022, 2022
Short summary
Short summary
Lidars can measure the wind profile in the lower part of the atmosphere, provided that the wind field is horizontally uniform and does not change during the time of the measurement. These requirements are mostly not fulfilled in reality, and the lidar wind measurement will thus hold a certain error. We investigate different strategies for lidar wind profiling using a lidar simulator implemented in a numerical simulation of the wind field. Our findings can help to improve wind measurements.
Katherine E. Lukens, Kayo Ide, Kevin Garrett, Hui Liu, David Santek, Brett Hoover, and Ross N. Hoffman
Atmos. Meas. Tech., 15, 2719–2743, https://doi.org/10.5194/amt-15-2719-2022, https://doi.org/10.5194/amt-15-2719-2022, 2022
Short summary
Short summary
Winds that are crucial to weather forecasting derived from two different techniques – tracking satellite images (AMVs) and direct measurement of molecular and aerosol motions by Doppler lidar (Aeolus satellite winds) – are compared. We find that AMVs and Aeolus winds are highly correlated. Aeolus Mie-cloudy winds have great potential value as a comparison standard for AMVs. Larger differences are found in the Southern Hemisphere related to higher wind speed and higher vertical variation in wind.
Marijn Floris van Dooren, Anantha Padmanabhan Kidambi Sekar, Lars Neuhaus, Torben Mikkelsen, Michael Hölling, and Martin Kühn
Atmos. Meas. Tech., 15, 1355–1372, https://doi.org/10.5194/amt-15-1355-2022, https://doi.org/10.5194/amt-15-1355-2022, 2022
Short summary
Short summary
The remote sensing technique lidar is widely used for wind speed measurements for both industrial and academic applications. Lidars can measure wind statistics accurately but cannot fully capture turbulent fluctuations in the high-frequency range, since they are partly filtered out. This paper therefore investigates the turbulence spectrum measured by a continuous-wave lidar and analytically models the lidar's measured spectrum with a Lorentzian filter function and a white noise term.
Alain Protat, Valentin Louf, Joshua Soderholm, Jordan Brook, and William Ponsonby
Atmos. Meas. Tech., 15, 915–926, https://doi.org/10.5194/amt-15-915-2022, https://doi.org/10.5194/amt-15-915-2022, 2022
Short summary
Short summary
This study uses collocated ship-based, ground-based, and spaceborne radar observations to validate the concept of using the GPM spaceborne radar observations to calibrate national weather radar networks to the accuracy required for operational severe weather applications such as rainfall and hail nowcasting.
Wagner Wolff, Aart Overeem, Hidde Leijnse, and Remko Uijlenhoet
Atmos. Meas. Tech., 15, 485–502, https://doi.org/10.5194/amt-15-485-2022, https://doi.org/10.5194/amt-15-485-2022, 2022
Short summary
Short summary
The existing infrastructure for cellular communication is promising for ground-based rainfall remote sensing. Rain-induced signal attenuation is used in dedicated algorithms for retrieving rainfall depth along commercial microwave links (CMLs) between cell phone towers. This processing is a source of many uncertainties about input data, algorithm structures, parameters, CML network, and local climate. Application of a stochastic optimization method leads to improved CML rainfall estimates.
Songhua Wu, Kangwen Sun, Guangyao Dai, Xiaoye Wang, Xiaoying Liu, Bingyi Liu, Xiaoquan Song, Oliver Reitebuch, Rongzhong Li, Jiaping Yin, and Xitao Wang
Atmos. Meas. Tech., 15, 131–148, https://doi.org/10.5194/amt-15-131-2022, https://doi.org/10.5194/amt-15-131-2022, 2022
Short summary
Short summary
During the VAL-OUC campaign, we established a coherent Doppler lidar (CDL) network over China to verify the Level 2B (L2B) products from Aeolus. By the simultaneous wind measurements with CDLs at 17 stations, the L2B products from Aeolus are compared with those from CDLs. To our knowledge, the VAL-OUC campaign is the most extensive so far between CDLs and Aeolus in the lower troposphere for different atmospheric scenes. The vertical velocity impact on the HLOS retrieval from Aeolus is evaluated.
Karina Wilgan, Galina Dick, Florian Zus, and Jens Wickert
Atmos. Meas. Tech., 15, 21–39, https://doi.org/10.5194/amt-15-21-2022, https://doi.org/10.5194/amt-15-21-2022, 2022
Short summary
Short summary
The assimilation of GNSS data in weather models has a positive impact on the forecasts. The impact is still limited due to using only the GPS zenith direction parameters. We calculate and validate more advanced tropospheric products from three satellite systems: the US American GPS, Russian GLONASS and European Galileo. The quality of all the solutions is comparable; however, combining more GNSS systems enhances the observations' geometry and improves the quality of the weather forecasts.
Hironori Iwai, Makoto Aoki, Mitsuru Oshiro, and Shoken Ishii
Atmos. Meas. Tech., 14, 7255–7275, https://doi.org/10.5194/amt-14-7255-2021, https://doi.org/10.5194/amt-14-7255-2021, 2021
Short summary
Short summary
The first space-based Doppler wind lidar on board the Aeolus satellite was launched on 22 August 2018 to obtain global horizontal wind profiles. In this study, wind profilers, ground-based coherent Doppler wind lidars, and GPS radiosondes were used to validate the quality of Aeolus Level 2B wind products over Japan during three different periods. The results show that Aeolus can measure the horizontal winds over Japan accurately.
Tim A. van Kempen, Filippo Oggionni, and Richard M. van Hees
Atmos. Meas. Tech., 14, 6711–6722, https://doi.org/10.5194/amt-14-6711-2021, https://doi.org/10.5194/amt-14-6711-2021, 2021
Short summary
Short summary
Validation of the instrument stability of the TROPOMI-SWIR module is done by monitoring a group of very stable and remote locations in the Saharan and Arabian deserts. These results confirm the excellent stability and lack of degradation of the TROPOMI-SWIR module derived from the internal calibration sources. The method was done for the first time on a spectrometer in the short-wave infrared and ensures TROPOMI-SWIR can be used for atmospheric research for years to come.
Susanna Hagelin, Roohollah Azad, Magnus Lindskog, Harald Schyberg, and Heiner Körnich
Atmos. Meas. Tech., 14, 5925–5938, https://doi.org/10.5194/amt-14-5925-2021, https://doi.org/10.5194/amt-14-5925-2021, 2021
Short summary
Short summary
In this paper we study the impact of using wind observations from the Aeolus satellite, which provides wind speed profiles globally, in our numerical weather prediction system using a regional model covering the Nordic countries. The wind speed profiles from Aeolus are assimilated by the model, and we see that they have an impact on both the model analysis and forecast, though given the relatively few observations available the impact is often small.
Evgenia Belova, Sheila Kirkwood, Peter Voelger, Sourav Chatterjee, Karathazhiyath Satheesan, Susanna Hagelin, Magnus Lindskog, and Heiner Körnich
Atmos. Meas. Tech., 14, 5415–5428, https://doi.org/10.5194/amt-14-5415-2021, https://doi.org/10.5194/amt-14-5415-2021, 2021
Short summary
Short summary
Wind measurements from two radars (ESRAD in Arctic Sweden and MARA at the Indian Antarctic station Maitri) are compared with lidar winds from the ESA satellite Aeolus, for July–December 2019. The aim is to check if Aeolus data processing is adequate for the sunlit conditions of polar summer. Agreement is generally good with bias in Aeolus winds < 1 m/s in most circumstances. The exception is a large bias (7 m/s) when the satellite has crossed a sunlit Antarctic ice cap before passing MARA.
Ramashray Yadav, Ram Kumar Giri, and Virendra Singh
Atmos. Meas. Tech., 14, 4857–4877, https://doi.org/10.5194/amt-14-4857-2021, https://doi.org/10.5194/amt-14-4857-2021, 2021
Short summary
Short summary
We performed an intercomparison of seasonal and annual studies of retrievals of integrated precipitable water vapor (IPWV) carried out by INSAT-3DR satellite-borne infrared radiometer sounding and CAMS reanalysis data with ground-based Indian GNSS data. The magnitude and sign of the bias of INSAT-3DR and CAMS with respect to GNSS IPWV differs from station to station and season to season. A statistical evaluation of the collocated data sets was done to improve day-to-day weather forecasting.
Matic Šavli, Vivien Pourret, Christophe Payan, and Jean-François Mahfouf
Atmos. Meas. Tech., 14, 4721–4736, https://doi.org/10.5194/amt-14-4721-2021, https://doi.org/10.5194/amt-14-4721-2021, 2021
Short summary
Short summary
The ESA's Aeolus satellite wind retrieval is provided through a series of processors. It depends on the temperature and pressure specification, which, however, are not measured by the satellite. The numerical weather predicted values are used instead, but these are erroneous. This article studies the sensitivity of the wind retrieval by introducing errors in temperature and pressure. This has been found to be small for Aeolus but is expected to be more crucial for future missions.
Kristopher M. Bedka, Amin R. Nehrir, Michael Kavaya, Rory Barton-Grimley, Mark Beaubien, Brian Carroll, James Collins, John Cooney, G. David Emmitt, Steven Greco, Susan Kooi, Tsengdar Lee, Zhaoyan Liu, Sharon Rodier, and Gail Skofronick-Jackson
Atmos. Meas. Tech., 14, 4305–4334, https://doi.org/10.5194/amt-14-4305-2021, https://doi.org/10.5194/amt-14-4305-2021, 2021
Short summary
Short summary
This paper demonstrates the Doppler Aerosol WiNd (DAWN) lidar and High Altitude Lidar Observatory (HALO) measurement capabilities across a range of atmospheric conditions, compares DAWN and HALO measurements with Aeolus satellite Doppler wind lidar to gain an initial perspective of Aeolus performance, and discusses how atmospheric dynamic processes can be resolved and better understood through simultaneous observations of wind, water vapour, and aerosol profile observations.
Emranul Sarkar, Alexander Kozlovsky, Thomas Ulich, Ilkka Virtanen, Mark Lester, and Bernd Kaifler
Atmos. Meas. Tech., 14, 4157–4169, https://doi.org/10.5194/amt-14-4157-2021, https://doi.org/10.5194/amt-14-4157-2021, 2021
Short summary
Short summary
The biasing effect in meteor radar temperature has been a pressing issue for the last 2 decades. This paper has addressed the underlying reasons for such a biasing effect on both theoretical and experimental grounds. An improved statistical method has been developed which allows atmospheric temperatures at around 90 km to be measured with meteor radar in an independent way such that any subsequent bias correction or calibration is no longer required.
Wei Zhong, Xianghui Xue, Wen Yi, Iain M. Reid, Tingdi Chen, and Xiankang Dou
Atmos. Meas. Tech., 14, 3973–3988, https://doi.org/10.5194/amt-14-3973-2021, https://doi.org/10.5194/amt-14-3973-2021, 2021
Evgenia Belova, Peter Voelger, Sheila Kirkwood, Susanna Hagelin, Magnus Lindskog, Heiner Körnich, Sourav Chatterjee, and Karathazhiyath Satheesan
Atmos. Meas. Tech., 14, 2813–2825, https://doi.org/10.5194/amt-14-2813-2021, https://doi.org/10.5194/amt-14-2813-2021, 2021
Short summary
Short summary
We validate horizontal wind measurements at altitudes of 0.5–14 km made with atmospheric radars: ESRAD located near Kiruna in the Swedish Arctic and MARA at the Indian research station Maitri in Antarctica, by comparison with radiosondes, the regional model HARMONIE-AROME and the ECMWF ERA5 reanalysis. Good agreement was found in general, and radar bias and uncertainty were estimated. These radars are planned to be used for validation of winds measured by lidar by the ESA satellite Aeolus.
Gizachew Kabite Wedajo, Misgana Kebede Muleta, and Berhan Gessesse Awoke
Atmos. Meas. Tech., 14, 2299–2316, https://doi.org/10.5194/amt-14-2299-2021, https://doi.org/10.5194/amt-14-2299-2021, 2021
Short summary
Short summary
Satellite rainfall estimates (SREs) are alternative data sources for data-scarce basins. However, the accuracy of the products is plagued by multiple sources of errors. Therefore, SREs should be evaluated for particular basins before being used for other applications. The results of the study showed that CHIRPS2 and IMERG6 estimated rainfall and predicted hydrologic simulations well for Dhidhessa River Basin, which shows remote sensing technology could improve hydrologic studies.
Steven Knoop, Fred C. Bosveld, Marijn J. de Haij, and Arnoud Apituley
Atmos. Meas. Tech., 14, 2219–2235, https://doi.org/10.5194/amt-14-2219-2021, https://doi.org/10.5194/amt-14-2219-2021, 2021
Short summary
Short summary
Doppler wind lidars are laser-based remote sensing instruments that measure the wind up to a few hundred metres or even a few kilometres. Their data can improve weather models and help forecasters. To investigate their accuracy and required meteorological conditions, we have carried out a 2-year measurement campaign of a wind lidar at our Cabauw test site and made a comparison with cup anemometers and wind vanes at several levels in a 213 m tall meteorological mast.
Joaquim V. Teixeira, Hai Nguyen, Derek J. Posselt, Hui Su, and Longtao Wu
Atmos. Meas. Tech., 14, 1941–1957, https://doi.org/10.5194/amt-14-1941-2021, https://doi.org/10.5194/amt-14-1941-2021, 2021
Short summary
Short summary
Wind-tracking algorithms produce atmospheric motion vectors (AMVs) by tracking satellite observations. Accurately characterizing the uncertainties in AMVs is essential in assimilating them into data assimilation models. We develop a machine-learning-based approach for error characterization which involves Gaussian mixture model clustering and random forest using a simulation dataset of water vapor, AMVs, and true winds. We show that our method improves on existing AMV error characterizations.
Giovanni Martucci, Francisco Navas-Guzmán, Ludovic Renaud, Gonzague Romanens, S. Mahagammulla Gamage, Maxime Hervo, Pierre Jeannet, and Alexander Haefele
Atmos. Meas. Tech., 14, 1333–1353, https://doi.org/10.5194/amt-14-1333-2021, https://doi.org/10.5194/amt-14-1333-2021, 2021
Short summary
Short summary
This article presents a validation of 1.5 years of pure rotational temperature data measured by the Raman lidar RALMO installed at the MeteoSwiss station of Payerne. The statistical results are in terms of bias and standard deviation with respect to two well-established radiosounding systems. The statistics are divided into daytime (bias = 0.28 K, SD = 0.62±0.03 K) and nighttime (bias = 0.29 K, SD = 0.66±0.06 K). The lidar temperature profiles are applied to cloud supersaturation studies.
Cited articles
Aksoy, A., Dowell, D. C., and Snyder, C.: A multiscale comparative assessment of the ensemble Kalman filter for assimilation of radar observations. Part I: Storm-scale analyses, Mon. Weather Rev., 137, 1805–1824, 2009. a
Baldlauf, M., Seifert, A.,
Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational
convective-scale numerical weather prediciton with the COSMO model:
description and sensitivities, Mon. Weather Rev., 139, 3887–3905,
2011. a
Bick, T., Simmer, C., Trömel, S., Wapler, K., Stephan, K., Blahak, U., Zeng, Y., and Potthast, R.: Assimilation of 3D-Radar Reflectivities with an Ensemble Kalman Filter on the Convective Scale, Q. J. Roy. Meteor. Soc., 142, 1490–1504, 2016. a
Caumont, O., Ducrocq, V., Wattrelot, E., Jaubert, G., and Pradier-Vabre, S.: 1D + 3DVar assimilation of radar reflectivity data: a proof of concept, Tellus, 62, 173–187, 2010. a
Chambon, P., Zhang, S. Q., Arthur, S. Q., Hou, Y., Zupanski, M., and Cheung, S.: Assessing the impact of pre-GPM microwave precipitation observations in the Goddard WRF ensemble data assimilation system, Q. J. Roy. Meteor. Soc., 140, 1219–1235, 2014. a
Doviak, R. J. and Zrnic, D. S.: Doppler Radar and Weather Observations, vol. 2, Academic Press, Inc., San Diego, 1993. a
Fujita, T., Seko, H., Kawabata, T.,
Ikuta, Y., Sawada, K., Hotta, D., and Kunii, M.: Variational Data Assimilation
with Spatial and Temporal Observation Error Correlations of Doppler Radar
Radial Winds, in: Working Group on Numerical Experimentation. Report No. 50.WCRP Report No.12/2020, WMO, Geneva, Switzerland, 2020. a
Gaspari, G. and Cohn, S. E.: Construction of correlation functions in two and three dimensions, Q. J. Roy. Meteor. Soc., 125, 723–757, 1999. a
Gastaldo, T., Poli, V., Marsigli, C., Cesari, D., Alberoni, P. P., and Paccagnella, T.: Assimilation of radar reflectivity volumes in a pre-operational framework, Q. J. Roy. Meteor. Soc., 147, 1031–1054, https://doi.org/10.1002/qj.3957, early View, 2021. a
Geer, A. J. and Bauer, P.: Observation errors in all-sky data assimilation, Q. J. Roy. Meteor. Soc., 137, 2024–2037, 2011. a
Gustafsson, N., Janjić, T., Schraff, C., Leuenberger, D., Weissman, M., Reich, H., Brousseau, P., Montmerle, T., Wattrelot, E., Bucanek, A., Mile, M., Hamdi, R., Lindskog, M., Barkmeijer, J., Dahlbom, M., Macpherson, B., Ballard, S., Inverarity, G., Carley, J., Alexander, C., Dowell, D., Liu, S., Ikuta, Y., and Fujita, T.: Survey of data assimilation methods for convective-scale numerical weather prediction at operational centres, Q. J. Roy. Meteor. Soc., pp. 1218–1256, 2018. a
Hawkness-Smith, L. and Simonin, D.: Radar reflectivity assimilation using hourly cycling 4D-Var in the Met Office Unified Model, Q. J. Roy. Meteor. Soc., 147, 1516–1538, 2021. a
Hollingsworth, A. and Lonnberg, P.: The statistical structure of short-range forecast errors as determined from radiosonde data. Part 1: the wind field, Tellus, 38, 111–136, 1986. a
Hunt, B. R., Kostelich, E. J., and Szunyogh, I.: Efficient data assimilation for Spatiotemporal Chaos: a Local Ensemble Transform Kalman Filter, Physica D, 230, 112–126, 2007. a
Kouroupaki, V.: Investigating radar reflectivity uncertainty in data assimilation for high impact weather prediction, Master's thesis, University of Reading, UK, 2019. a
Lange, H., Craig, G. C., and Janjić, T.: Characterizing noise and spurious convection in convective data assimilation, Q. J. Roy. Meteor. Soc., 143, 3060–3069, 2017. a
Lin, Y., Farley, R. D., and Orville, H. D.: Bulk parameterization of the snow field in a cloud model, J. Clim. Appl. Meteorol., 22, 1065–1092, 1983. a
Liu, Z. Q. and Rabier, F.: The interaction between model resolution observation resolution and observation density in data assimilation, Q. J. Roy. Meteor. Soc., 128, 1367–1386, 2002. a
Milan, M., Macpherson, B., Tubbs, R., Dow, G., Inverarity, G., Mittermaier, M., Halloran, G., Kelly, G., Li, D., Maycock, A., Payne, T., Piccolo, C., Stewart, L., and Wlasak, M.: Hourly 4D-Var in the Met Office UKV operational forecast model, Q. J. Roy. Meteor. Soc., 146, 1281–1301, 2020. a
Montmerle, T. and Faccani, C.: Mesoscale assimilation of radial velocities from Doppler radars in a preoperational framework, Mon. Weather Rev., 137, 1939–1953, 2009. a
Prill, F.: DWD ICON Tools Documentation, Deutscher Wetterdienst (DWD), available at:
https://wiki.c2sm.ethz.ch/pub/MODELS/ICONDwdIconTools/doc_icontools.pdf (last access: 19 August 2021), 2014. a
Raschendorfer, M.: The new turbulence parametrization of LM, COSMO-Newsletter, 1, 89–97, 2001. a
Reichle, R. H., Walker, R. D., Koster, R. D., and Houser, P. R.: Extended versus ensemble Kalman filtering for land data assimilation, J. Hydrometeorol., 3, 728–740, 2002. a
Reinhardt, T. and Seifert, A.: A three-category ice scheme for LMK, COSMO-Newsletter, 6, 115–120, 2006. a
Ruckstuhl, Y. M. and Janjić, T.: Combined state-parameter estimation with the LETKF for convective-scale weather forecasting, Mon. Weather Rev., 148, 1607–1628, 2020. a
Russ, J.: The Image Processing Handbook, CRC Press, Boca Raton, USA, 2006. a
Simmer, C., Adrian, G., Jones, S., Wirth, V., Göber, M., Hohenegger, C., Janjić, T., Keller, J., Ohlwein, C., Seifert, A., Trömel, S., Ulbrich, T., Wapler, K., Weissmann, M., Keller, J., Masbou, M., Meilinger, S., Riß, N., Schomburg, A., Vormann, A., and Weingärtner, C.: HErZ – The German Hans-Ertel Centre for Weather Research, B. Am. Meteorol. Soc., 97, 1057–1068, 2016. a
Simonin, D., Waller, J. A., Ballard, S. P., Dance, S. L., and Nichols, N. K.: A pragmatic strategy for implementing spatially correlated observation errors in an operational system: An application to Doppler radial winds, Q. J. Roy. Meteor. Soc., 145, 2772–2790, 2019. a
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in large-scale models, Mon. Weather Rev., 117, 1779–1799, 1989. a
Waller, J., Dance, S., and Nichols, N.: On diagnosing observation-error statistics with local ensemble data assimilation, Q. J. Roy. Meteor. Soc., 143, 2677–2686, 2017. a
Waller, J. A., Ballard, S. P., Dance, S. L., Kelly, G., Nichols, N. K., and Simonin, D.: Diagnosing horizontal and inter-channelobservation error correlations for SEVIRI observations using observation-minus-background and observation-minus-analysis statistics, Remote Sens.-Basel, 8, 581, https://doi.org/10.3390/rs8070581, 2016a. a, b, c
Waller, J. A., Dance, S. L., and Nichols, N. K.: Theoretical insight into diagnosing observation error correlations using observation-minus-background and observation-minus-analysis statistics, Q. J. Roy. Meteor. Soc., 142, 418–431, 2016b. a
Waller, J. A., Simonin, D., Dance, S. L., Nichols, N. K., and Ballard, S. P.: Diagnosing Observation Error Correlations for Doppler Radar Radial Winds in the Met Office UKV Model Using Observation-Minus-Background and Observation-Minus-Analysis Statistics, Mon. Weather Rev., 144, 3533–3551, 2016c. a, b, c, d, e
Waller, J. A., Dance, S. L., and Lean, H. W.: Evaluating errors due to unresolved scales in convection permitting numerical weather prediction, Q. J. Roy. Meteor. Soc., 147, 2657–2669, https://doi.org/10.1002/qj.4043, 2021. a
Wang, Y. and Wang, X.: Direct Assimilation of Radar Reflectivity without Tangent Linear and Adjoint of the Nonlinear Observation Operator in the GSI-Based EnVar System: Methodology and Experiment with the 8 May 2003 Oklahoma City Tornadic Supercell, Mon. Weather Rev., 145, 1447–1471, 2017. a
Wattrelot, E., Montmerle, T., and Guerrero, C.: Evolution of the assimilation of radar data in the AROME model at convective scale, in: Proceedings of the seventh European conference on radar in meteorology and hydrology, 25–29 June 2012, Toulouse, France, 1–6, available at: http://www.meteo.fr/cic/meetings/2012/ERAD/extended_abs/NWP_401_ext_abs.pdf (last access: 19 August 2021), 2012. a
Wedi, N. P.: Increasing horizontal resolution in numerical weather prediction and climate simulations: illusion or panacea?, Philos. T. Roy. Soc. A, 372, 20130289, https://doi.org/10.1098/rsta.2013.0289, 2014. a
Weissmann, M., Göber, M., Hohenegger, C., Janjić, T., Keller, J., Ohlwein, C., Seifert, A., Trömel, S., Ulbrich, T., Wapler, K., Bollmeyer, C., and Deneke, H.: Initial phase of the Hans-Ertel Centre for Weather Research – A virtual centre at the interface of basic and applied weather and climate research, Meteorol. Z., 23, 193–208, 2014. a
Werner, M.: A New Radar Data Post-Processing Quality Control Workflow for
the DWD Weather Radar Network, in: Proceedings of the eighth European conference on radar in meteorology and hydrology, 1–5 September 2014, Garmisch-Partenkirchen, Germany, 1–9, available at: http://www.pa.op.dlr.de/erad2014/programme/ExtendedAbstracts/079_Werner.pdf (last access: 19 August 2021), 2014. a
Xue, M., Jung, Y., and Zhang, G.: Error modeling of simulated reflectivity observations for ensemble Kalman filter assimilation of convective storms, Geophys. Res. Lett., 148, L10802, https://doi.org/10.1029/2007GL029945, 2007. a
Zeng, Y.: Efficient Radar Forward Operator for Operational Data Assimilation within the COSMO-model, PhD dissertation, Karlsruhe Insititute of Technology, 2013. a
Zeng, Y., Janjic, T., de Lozar, A., Welzbacher, C. A., Blahak, U., and Seifert, A.: Assimilating radar radial wind and reflectivity data in an idealized setup of the COSMO-KENDA system, Atmos. Res., 249, 105282, https://doi.org/10.1016/j.atmosres.2020.105282, 2021a. a, b, c, d
Zeng, Y., de Lozar, A., Janjic, T., and Seifert, A.: Applying a new integrated mass-flux adjustment filter in rapid update cycling of convective-scale data assimilation for the COSMO model (v5.07), Geosci. Model Dev., 14, 1295–1307, https://doi.org/10.5194/gmd-14-1295-2021, 2021b. a, b
Zhang, F., Snyder, C., and Sun, J.: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter, Mon. Weather Rev., 132, 1238–1253, 2004. a
Short summary
Observation errors (OEs) of radar measurements are correlated. The Desroziers method has been often used to estimate statistics of OE in data assimilation. However, the resulting statistics consist of contributions from different sources and are difficult to interpret. Here, we use an approach based on samples for truncation error to approximate the representation error due to unresolved scales and processes (RE) and compare its statistics with OE statistics estimated by the Desroziers method.
Observation errors (OEs) of radar measurements are correlated. The Desroziers method has been...
