scholarly journals Evaluating the Forecast Skill of a Hydrometeorological Modelling System in Greece

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 902
Author(s):  
George Varlas ◽  
Anastasios Papadopoulos ◽  
George Papaioannou ◽  
Elias Dimitriou
Keyword(s):  
Water Level ◽  
Flash Flood ◽  
Horizontal Resolution ◽  
Forecast Skill ◽  
Weather Research And Forecasting ◽  
Marine Research ◽  
Weather Forecasts ◽  
Flood Warning ◽  
Arw Model ◽  
Forecasting System

A hydrometeorological forecasting system has been operating at the Institute of Marine Biological Resources and Inland Waters (IMBRIW) of the Hellenic Centre for Marine Research (HCMR) since September 2015. The system consists of the Advanced Weather Research and Forecasting (WRF-ARW) model, the WRF-Hydro hydrological model, and the HEC-RAS hydraulic–hydrodynamic model. The system provides daily 120 h weather forecasts focusing on Greece (4 km horizontal resolution) and hydrological forecasts for the Spercheios and Evrotas rivers in Greece (100 m horizontal resolution), also providing flash flood inundation forecasts when needed (5 m horizontal resolution). The main aim of this study is to evaluate precipitation forecasts produced in a 4-year period (September 2015–August 2019) using measurements from meteorological stations across Greece. Water level forecasts for the Evrotas and Spercheios rivers were also evaluated using measurements from hydrological stations operated by the IMBRIW. Moreover, the forecast skill of the chained meteorological–hydrological–hydraulic operation of the system was investigated during a catastrophic flash flood in the Evrotas river. The results indicated that the system provided skillful precipitation and water level forecasts. The best evaluation results were yielded during rainy periods. They also demonstrated that timely flash flood forecasting products could benefit flood warning and emergency responses due to their efficiency and increased lead time.

scholarly journals Update of Early Warning Indicators of Flash Floods: A Case Study of Hunjiang District, Northeastern China

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 314 ◽  
Author(s):  
Meihong Ma ◽  
Jingnan Zhang ◽  
Huidong Su ◽  
Dacheng Wang ◽  
Zhongliang Wang
Keyword(s):  
Water Level ◽  
Early Warning ◽  
Flash Flood ◽  
Field Investigation ◽  
Northeastern China ◽  
Flood Peak ◽  
Flood Warning ◽  
Early Warning Indicators ◽  
Warning Indicators ◽  
Formula Method

The China flash flood investigation and evaluation database (CFFIED) covers important information needed for China’s flash flood warning. This paper uses a statistical induction method, inference formula method and standardized unit hydrograph method to explore its principle, characteristics, and key steps. Then based on the field investigation and the latest data on the flash flood, the Hunjiang District in northeastern China was selected as the research area. Firstly, three typical riverside villages, Xiangmo-1 and Sanchahe-3, Shangqing-4, were screened, and the flash flood warning indicators (e.g., water level, flow rate, critical rainfall) in the CFFIED were updated. Then, the maximum error of the flood peak, estimated by the inference formula method and the water level flow relationship method, is only 10.6%, which indicates that the predicted flood peak flow has high credibility and can check and identify the early warning index; the Manning formula is more accurate in calculating the water level flow relationship. However, the calculated ratio is lower and the roughness is higher, and the flow is smaller under the same water level. Finally, the updated flash flood warning indicators were obtained in the Hunjiang District, which improves the accuracy of the flash flood warning, and provides a reference for updating the early warning indicators in other areas.

Development and Testing of a Low-cost Water Level Sensor and a Mobile based Real-time Flood Warning System for the Flash Flood Prone North Eastern part of Bangladesh

2020 ◽  
Vol 10 ◽  
Author(s):  
Nova Ahmed ◽  
Md. Sirajul Islam ◽  
Sifat Kalam ◽  
Farzana Islam ◽  
Nabila Chowdhury ◽  
...  
Keyword(s):  
Water Level ◽  
Real Time ◽  
Flash Flood ◽  
Low Cost ◽  
Warning System ◽  
Outdoor Environment ◽  
Flood Warning ◽  
North Eastern ◽  
Flood Warning System ◽  
North Eastern Part

Background: The North-Eastern part of Bangladesh is suffering from flash flood very frequently, causing colossal damage to life and properties, especially the vast croplands. A distributed sensing system can monitor the water level on a continuous basis to warn people near the riverbank beforehand and reduce the damage largely. However, the required communication infrastructure is not available in most of the remote rural areas in a developing country like Bangladesh. Objective: This study intends to develop a low-cost sensor based warning system, customizing to the Bangladesh context. Method: The system utilizes a low-cost ultrasound based sensor device, a lightweight mobile phone based server, low-cost IoT sensing nodes, and a central server for continuous monitoring of river stage data along with the provision of storage and long-term data analytics. Results: A flash flood warning system developed afterward with the sensors, mobile-based server, and appropriate webbased interfaces. The device was tested for some environmental conditions in the lab and deployed it later in the outdoor conditions for short-term periods. Conclusion: Overall, the warning system performed well in the lab as well as the outdoor environment, with the ability to detect water level at reasonable accuracy and transmit data to the server in real time. Some minor shortcomings still noted with the scope for improvements, which are in the way to improve further.

scholarly journals Verification of operational weather forecasts from the POSEIDON system across the Eastern Mediterranean

2009 ◽  
Vol 9 (4) ◽  
pp. 1299-1306 ◽  
Author(s):  
A. Papadopoulos ◽  
P. Katsafados
Keyword(s):  
Weather Forecasting ◽  
Eastern Mediterranean ◽  
Eastern Mediterranean Region ◽  
Horizontal Resolution ◽  
Marine Research ◽  
Weather Forecasts ◽  
High Resolution Analysis ◽  
Extended Area ◽  
Improved Model ◽  
New System

Abstract. The POSEIDON weather forecasting system became operational at the Hellenic Centre for Marine Research (HCMR) in October 1999. The system with its nesting capability provided 72-h forecasts in two different model domains, i.e. 25- and 10-km grid spacing. The lower-resolution domain covered an extended area that included most of Europe, Mediterranean Sea and N. Africa, while the higher resolution domain focused on the Eastern Mediterranean. A major upgrade of the system was recently implemented in the framework of the POSEIDON-II project (2005–2008). The aim was to enhance the forecasting skill of the system through improved model parameterization schemes and advanced numerical techniques for assimilating available observations to produce high resolution analysis fields. The configuration of the new system is applied on a horizontal resolution of 1/20°×1/20° (~5 km) covering the Mediterranean basin, Black Sea and part of North Atlantic providing up to 5-day forecasts. This paper reviews and compares the current with the previous weather forecasting systems at HCMR presenting quantitative verification statistics from the pre-operational period (from mid-November 2007 to October 2008). The statistics are based on verification against surface observations from the World Meteorological Organization (WMO) network across the Eastern Mediterranean region. The results indicate that the use of the new system can significantly improve the weather forecasts.

scholarly journals The research status of flash flood warning in China

2018 ◽  
Vol 246 ◽  
pp. 01072
Author(s):  
Zhao Keke ◽  
Peng Dingzhi ◽  
Gu Yu ◽  
Fan Chuting
Keyword(s):  
Water Level ◽  
Flash Flood ◽  
Warning System ◽  
Development Trend ◽  
Current Situation ◽  
Antecedent Soil Moisture ◽  
Physical Mechanisms ◽  
Flood Warning ◽  
Statistical Induction ◽  
Underlying Surface Conditions

The article discusses from the disaster mechanism of flash flood to the current situation of early warning system. The formation of flash flood is closely related to rainfall intensity, underlying surface conditions and antecedent soil moisture content, and analysis of the physical process of flash flood disasters is crucial for the study of flash flood warning. Flash flood disaster warning indexes are mainly divided into two types: rainfall warning index and water level warning index. Data-driven statistical induction method and hydro-hydraulic methods based on physical mechanisms are used to determine rainfall warning index; The water level warning index can be directly determined by the upstream and downstream corresponding water level method or by the disaster water level. And summed up the current situation and development trend of China's flash flood warning research.

scholarly journals Technical note: Lowermost-stratospheric moist bias in ECMWF IFS model diagnosed from airborne GLORIA observations during winter/spring 2016

2020 ◽  
Author(s):  
Wolfgang Woiwode ◽  
Andreas Dörnbrack ◽  
Inna Polichtchouk ◽  
Sören Johansson ◽  
Ben Harvey ◽  
...  
Keyword(s):  
Weather Forecast ◽  
Horizontal Resolution ◽  
Technical Note ◽  
Cold Bias ◽  
Air Masses ◽  
Weather Forecasts ◽  
Time Period ◽  
Forecasting System ◽  
Numerical Weather Forecast

Abstract. Numerical weather forecast systems like the ECMWF IFS (European Centre for Medium-Range Weather Forecasts – Integrated Forecasting System) are known to be affected by a moist bias in the extratropical lowermost stratosphere (LMS) which results in a systematic cold bias there. We use high spatial resolution water vapour measurements by the airborne 15 infrared limb-imager GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere) during the PGS (POLSTRACC/GW-LCYLCE-II/SALSA) campaign to study the LMS moist bias in ECMWF analyses and 12 h forecasts in the season from January to March 2016. Thereby, we exploit the 2-dimensional observational capabilities of GLORIA, when compared to in situ observations, and the higher vertical and horizontal resolution, when compared to satellite observations. Using GLORIA observations taken during five flights in the polar sub-vortex region around Scandinavia and Greenland, we 20 diagnose a systematic moist bias in the LMS peaking at +50 % at potential vorticity levels of 6 to 10 PVU. In the diagnosed time period, the moist bias reduces at the highest and driest air masses observed, but clearly persists at lower levels until mid-March. Sensitivity experiments with more frequent temporal output, lower horizontal resolution, and higher/lower vertical resolution, show the short-term forecasts to be practically insensitive to these parameters on time scales of

THE ECMWF MULTI-TASKING WEATHER PREDICTION MODEL

1991 ◽  
Vol 02 (01) ◽  
pp. 158-186 ◽  
Author(s):  
A.J. SIMMONS ◽  
D. DENT
Keyword(s):  
Weather Prediction ◽  
Atmospheric Model ◽  
Horizontal Resolution ◽  
General Introduction ◽  
Weather Forecasts ◽  
Operational Forecasting ◽  
Medium Range ◽  
Computational Aspects ◽  
Forecasting System ◽  
And Performance

A general introduction to numerical weather prediction is given. The development of the operational forecasting system of the European Centre for Medium-Range Weather Forecasts is summarized, and some results are presented illustrating sensitivity to the horizontal resolution of the atmospheric model, the factor which is most significant in determining computational needs. The spectral method used for the horizontal discretization is described, and computational aspects of its implementation on CRAY-1 and CRAY X-MP machines are discussed. The organization of the multi-tasking employed in the model is presented, and performance figures are given. There is a brief concluding discussion of some likely future developments in medium-range weather prediction.

scholarly journals The CAMS reanalysis of atmospheric composition

2019 ◽  
Vol 19 (6) ◽  
pp. 3515-3556 ◽  
Author(s):  
Antje Inness ◽  
Melanie Ades ◽  
Anna Agustí-Panareda ◽  
Jérôme Barré ◽  
Anna Benedictow ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Three Dimensional ◽  
Chemical Species ◽  
Horizontal Resolution ◽  
Atmospheric Composition ◽  
Reanalysis Dataset ◽  
Weather Forecasts ◽  
Forecasting System ◽  
Total Column

Abstract. The Copernicus Atmosphere Monitoring Service (CAMS) reanalysis is the latest global reanalysis dataset of atmospheric composition produced by the European Centre for Medium-Range Weather Forecasts (ECMWF), consisting of three-dimensional time-consistent atmospheric composition fields, including aerosols and chemical species. The dataset currently covers the period 2003–2016 and will be extended in the future by adding 1 year each year. A reanalysis for greenhouse gases is being produced separately. The CAMS reanalysis builds on the experience gained during the production of the earlier Monitoring Atmospheric Composition and Climate (MACC) reanalysis and CAMS interim reanalysis. Satellite retrievals of total column CO; tropospheric column NO2; aerosol optical depth (AOD); and total column, partial column and profile ozone retrievals were assimilated for the CAMS reanalysis with ECMWF's Integrated Forecasting System. The new reanalysis has an increased horizontal resolution of about 80 km and provides more chemical species at a better temporal resolution (3-hourly analysis fields, 3-hourly forecast fields and hourly surface forecast fields) than the previously produced CAMS interim reanalysis. The CAMS reanalysis has smaller biases compared with most of the independent ozone, carbon monoxide, nitrogen dioxide and aerosol optical depth observations used for validation in this paper than the previous two reanalyses and is much improved and more consistent in time, especially compared to the MACC reanalysis. The CAMS reanalysis is a dataset that can be used to compute climatologies, study trends, evaluate models, benchmark other reanalyses or serve as boundary conditions for regional models for past periods.

scholarly journals Numerical Simulation of Extreme Temperature (Heat Wave) in Bangladesh Using WRF-ARW Model

2020 ◽  
pp. 44-54
Author(s):  
Md. Abdul Aziz ◽  
M. A. Samad ◽  
M. R. Hasan ◽  
M. N. U. Bhuiyan ◽  
M. A. K. Mallik
Keyword(s):  
Heat Wave ◽  
Mesoscale Model ◽  
Extreme Temperature ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Sea Level Pressure ◽  
Heat Wave Event ◽  
Arw Model ◽  
Wave Event

Every year Bangladesh experiences different types of natural hazards and heat wave is one of them. In the present study, an advanced high-resolution Weather Research and Forecasting (WRF-ARW) numerical mesoscale model is used to simulate a severe heat wave event occurred during April over Bangladesh and eastern part of India. The model is integrated for 6 days starting from UTC of 19 April to UTC of 24 April 2016, on a single domain of 10 km horizontal resolution. For validation of the model performance, the model simulated results of temperature at 2 m height, relative humidity (RH), mean sea level pressure (MSLP) at UTC of 6 days are compared with the BMD observed data. And the results indicate that the model is able to simulate the occurrence of the heat wave event with 6 days over Bangladesh.

scholarly journals Evaluation of the Impacts of Assimilating the TAMDAR Data on 12/4 km Grid WRF-Based RTFDDA Simulations over the CONUS

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Yongxin Zhang ◽  
Yubao Liu ◽  
Thomas Nipen
Keyword(s):  
Wind Speed ◽  
Data Assimilation ◽  
Real Time ◽  
Mean Squared Error ◽  
Meteorological Data ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Squared Error ◽  
Forecasting System ◽  
Four Dimensional Data Assimilation

An analysis of the impacts of assimilating the Tropospheric Airborne Meteorological Data Report (TAMDAR) data with the Weather Research and Forecasting- (WRF-) real-time four-dimensional data assimilation (RTFDDA) and forecasting system over the Contiguous US (CONUS) is presented. The impacts of the horizontal resolution increase from 12 km to 4 km on the WRF-RTFDDA simulations are also examined in conjunction with the TAMDAR data impacts. The assimilation of the TAMDAR data reduces the root mean squared error of the moisture field predictions and increases the correlation between the predictions and the observations for both domains with 12 km and 4 km grid spacings. The TAMDAR data reduce the model dry biases in the middle and lower levels by adding moisture at those levels. Assimilating the TAMDAR data improves temperature predictions at middle to high levels and wind speed predictions at all levels especially for the 12 km domain. Increasing the horizontal resolution from 12 km to 4 km results in significantly larger impacts on surface variables than assimilating the TAMDAR data.

scholarly journals Toward Improved Convection-Allowing Ensembles: Model Physics Sensitivities and Optimizing Probabilistic Guidance with Small Ensemble Membership

2010 ◽  
Vol 25 (1) ◽  
pp. 263-280 ◽  
Author(s):  
Craig S. Schwartz ◽  
John S. Kain ◽  
Steven J. Weiss ◽  
Ming Xue ◽  
David R. Bright ◽  
...  
Keyword(s):  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Lateral Boundary Condition ◽  
Ensemble Forecasts ◽  
University Of Oklahoma ◽  
Probabilistic Forecasts ◽  
Arw Model ◽  
Pbl Scheme ◽  
High Precipitation ◽  
The University

Abstract During the 2007 NOAA Hazardous Weather Testbed Spring Experiment, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma produced a daily 10-member 4-km horizontal resolution ensemble forecast covering approximately three-fourths of the continental United States. Each member used the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) model core, which was initialized at 2100 UTC, ran for 33 h, and resolved convection explicitly. Different initial condition (IC), lateral boundary condition (LBC), and physics perturbations were introduced in 4 of the 10 ensemble members, while the remaining 6 members used identical ICs and LBCs, differing only in terms of microphysics (MP) and planetary boundary layer (PBL) parameterizations. This study focuses on precipitation forecasts from the ensemble. The ensemble forecasts reveal WRF-ARW sensitivity to MP and PBL schemes. For example, over the 7-week experiment, the Mellor–Yamada–Janjić PBL and Ferrier MP parameterizations were associated with relatively high precipitation totals, while members configured with the Thompson MP or Yonsei University PBL scheme produced comparatively less precipitation. Additionally, different approaches for generating probabilistic ensemble guidance are explored. Specifically, a “neighborhood” approach is described and shown to considerably enhance the skill of probabilistic forecasts for precipitation when combined with a traditional technique of producing ensemble probability fields.

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