scholarly journals Overview of the first HyMeX Special Observation Period over Italy: observations and model results

2013 ◽  
Vol 10 (9) ◽  
pp. 11643-11710 ◽  
Author(s):  
R. Ferretti ◽  
E. Pichelli ◽  
S. Gentile ◽  
I. Maiello ◽  
D. Cimini ◽  
...  
Keyword(s):  
Central Italy ◽  
Weather Forecast ◽  
Heavy Precipitation ◽  
Western Mediterranean ◽  
Target Area ◽  
Weather Forecasts ◽  
Weather Events ◽  
North Eastern ◽  
Forecast Models ◽  
Observation Period

Abstract. During the first Hymex campaign (5 September–6 November 2012) referred to as Special Observation Period (SOP-1), dedicated to heavy precipitation events and flash floods in Western Mediterranean, three Italian hydro-meteorological monitoring sites were activated: Liguria-Tuscany, North-Eastern Italy and Central Italy. The extraordinary deployment of advanced instrumentation, including instrumented aircrafts, and the use of several different operational weather forecast models has allowed an unprecedented monitoring and analysis of high impact weather events around the Italian hydro-meteorological sites. This activity has seen the strict collaboration between the Italian scientific and operational communities. In this paper, an overview of the Italian organization during the SOP-1 is provided, and selected Intensive Observation Periods (IOPs) are described. A significant event for each Italian target area is chosen for this analysis: IOP2 (12–13 September 2012) in North-Eastern Italy, IOP13 (15–16 October 2012) in Central Italy and IOP19 (3–5 November 2012) in Liguria and Tuscany. For each IOP the meteorological characteristics, together with special observations and weather forecasts, are analyzed with the aim of highlighting strengths and weaknesses of the forecast modeling systems. Moreover, using one of the three events, the usefulness of different operational chains is highlighted.

scholarly journals Overview of the first HyMeX Special Observation Period over Italy: observations and model results

2014 ◽  
Vol 18 (5) ◽  
pp. 1953-1977 ◽  
Author(s):  
R. Ferretti ◽  
E. Pichelli ◽  
S. Gentile ◽  
I. Maiello ◽  
D. Cimini ◽  
...  
Keyword(s):  
Prediction Models ◽  
Hydrological Cycle ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Central Italy ◽  
Weather Forecast ◽  
Western Mediterranean ◽  
Target Area ◽  
Northeastern Italy ◽  
Observation Period

Abstract. The Special Observation Period (SOP1), part of the HyMeX campaign (Hydrological cycle in the Mediterranean Experiments, 5 September–6 November 2012), was dedicated to heavy precipitation events and flash floods in the western Mediterranean, and three Italian hydro-meteorological monitoring sites were identified: Liguria–Tuscany, northeastern Italy and central Italy. The extraordinary deployment of advanced instrumentation, including instrumented aircrafts, and the use of several different operational weather forecast models, including hydrological models and marine models, allowed an unprecedented monitoring and analysis of high-impact weather events around the Italian hydro-meteorological sites. This activity has seen strong collaboration between the Italian scientific and operational communities. In this paper an overview of the Italian organization during SOP1 is provided, and selected Intensive Observation Periods (IOPs) are described. A significant event for each Italian target area is chosen for this analysis: IOP2 (12–13 September 2012) in northeastern Italy, IOP13 (15–16 October 2012) in central Italy and IOP19 (3–5 November 2012) in Liguria and Tuscany. For each IOP the meteorological characteristics, together with special observations and weather forecasts, are analyzed with the aim of highlighting strengths and weaknesses of the forecast modeling systems, including the hydrological impacts. The usefulness of having different weather forecast operational chains characterized by different numerical weather prediction models and/or different model set up or initial conditions is finally shown for one of the events (IOP19).

scholarly journals How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Positive Impact ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Time Data ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Wind Lidar ◽  
Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

scholarly journals Scientific motivation for ADM/Aeolus mission

2018 ◽  
Vol 176 ◽  
pp. 02008
Author(s):  
Erland Källén
Keyword(s):  
Weather Forecast ◽  
Weather Forecasts ◽  
Weather And Climate ◽  
Medium Range ◽  
Forecast Models ◽  
Tropical Areas ◽  
Global Coverage ◽  
Wind Lidar ◽  
Wind Profiles

The ADM/Aeolus wind lidar mission will provide a global coverage of atmospheric wind profiles. Atmospheric wind observations are required for initiating weather forecast models and for predicting and monitoring long term climate change. Improved knowledge of the global wind field is widely recognised as fundamental to advancing the understanding and prediction of weather and climate. In particular over tropical areas there is a need for better wind data leading to improved medium range (3-10 days) weather forecasts over the whole globe.

scholarly journals IMPLEMENTASI BACKPROPAGATION NEURAL NETWORK DALAM PRAKIRAAN CUACA DI DAERAH BALI SELATAN

2016 ◽  
Vol 5 (4) ◽  
pp. 126 ◽  
Author(s):  
I MADE DWI UDAYANA PUTRA ◽  
G. K. GANDHIADI ◽  
LUH PUTU IDA HARINI
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Learning Algorithm ◽  
Weather Forecast ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Artificial Neural Network Method ◽  
Artificial Neural ◽  
Hidden Layer ◽  
Backpropagation Learning

Weather information has an important role in human life in various fields, such as agriculture, marine, and aviation. The accurate weather forecasts are needed in order to improve the performance of various fields. In this study, use artificial neural network method with backpropagation learning algorithm to create a model of weather forecasting in the area of ??South Bali. The aim of this study is to determine the effect of the number of neurons in the hidden layer and to determine the level of accuracy of the method of artificial neural network with backpropagation learning algorithm in weather forecast models. Weather forecast models in this study use input of the factors that influence the weather, namely air temperature, dew point, wind speed, visibility, and barometric pressure.The results of testing the network with a different number of neurons in the hidden layer of artificial neural network method with backpropagation learning algorithms show that the increase in the number of neurons in the hidden layer is not directly proportional to the value of the accuracy of the weather forecasts, the increase in the number of neurons in the hidden layer does not necessarily increase or decrease value accuracy of weather forecasts we obtain the best accuracy rate of 51.6129% on a network model with three neurons in the hidden layer.

NOAA’s Sensing Hazards with Operational Unmanned Technology (SHOUT) Experiment Observations and Forecast Impacts

2020 ◽  
Vol 101 (7) ◽  
pp. E968-E987 ◽  
Author(s):  
Gary A. Wick ◽  
Jason P. Dunion ◽  
Peter G. Black ◽  
John R. Walker ◽  
Ryan D. Torn ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Statistical Significance ◽  
High Sensitivity ◽  
Weather Forecast ◽  
Unmanned Aircraft ◽  
Impact Studies ◽  
Weather Events ◽  
Forecast Models ◽  
Scientific Results ◽  
Global Hawk

Abstract The National Oceanic and Atmospheric Administration’s (NOAA) Sensing Hazards with Operational Unmanned Technology (SHOUT) project evaluated the ability of observations from high-altitude unmanned aircraft to improve forecasts of high-impact weather events like tropical cyclones or mitigate potential degradation of forecasts in the event of a future gap in satellite coverage. During three field campaigns conducted in 2015 and 2016, the National Aeronautics and Space Administration (NASA) Global Hawk, instrumented with GPS dropwindsondes and remote sensors, flew 15 missions sampling 6 tropical cyclones and 3 winter storms. Missions were designed using novel techniques to target sampling regions where high model forecast uncertainty and a high sensitivity to additional observations existed. Data from the flights were examined in real time by operational forecasters, assimilated in operational weather forecast models, and applied postmission to a broad suite of data impact studies. Results from the analyses spanning different models and assimilation schemes, though limited in number, consistently demonstrate the potential for a positive forecast impact from the observations, both with and without a gap in satellite coverage. The analyses with the then-operational modeling system demonstrated large forecast improvements near 15% for tropical cyclone track at a 72-h lead time when the observations were added to the otherwise complete observing system. While future decisions regarding use of the Global Hawk platform will include budgetary considerations, and more observations are required to enhance statistical significance, the scientific results support the potential merit of the observations. This article provides an overview of the missions flown, observational approach, and highlights from the completed and ongoing data impact studies.

scholarly journals The disastrous storm of 4 November 1966 on Italy

2006 ◽  
Vol 6 (5) ◽  
pp. 861-879 ◽  
Author(s):  
S. De Zolt ◽  
P. Lionello ◽  
A. Nuhu ◽  
A. Tomasin
Keyword(s):  
Wind Speed ◽  
Storm Surge ◽  
Weather Forecast ◽  
Integrated Approach ◽  
Soil Condition ◽  
Eastern Alps ◽  
Western Mediterranean ◽  
Northern Adriatic ◽  
The North ◽  
North Eastern

Abstract. This is the first modeling reconstruction of the whole aspects (both meteorological and oceanographic) of the storm which hit Italy on 4 November 1966, producing 118 victims and widespread damages in Tuscany, at the northern Adriatic coast and in the north-eastern Italian Alps. The storm was produced by a cyclone which formed in the western Mediterranean and moved eastward towards Italy, reaching the Thyrrenian Sea, and then northward. The most peculiar characteristic of the storm has been the strong zonal pressure gradient and the consequent intensity and long fetch of the south-easterly sirocco wind, which advected a large amount of warm moist air, and determined exceptional orographic precipitation over Tuscany and the north-eastern Alps. The funneling of the wind between the mountain chains surrounding the Adriatic basin further increased the wind speed and determined the highest ever recorded storm surge along the Venetian coast. This study shows that present models would be able to produce a reasonably accurate simulation of the meteorological event (surface pressure, wind and precipitation fields, and storm surge level). The exceptional intensity of the event is not suggested by single parameters such as the sea level pressure minimum, the wind speed or the total accumulated precipitation. In fact, the precipitation was extreme only in some locations and the pressure minimum was not particularly deep. Moreover, the prediction of the damages produced by the river run-off and landslides would have required other informations concerning soil condition, snow coverage, and storage of water reservoirs before the event. This indicates that an integrated approach is required for assessing the probability of such damages both on a weather forecast and on a climate change perspective.

scholarly journals Overview of the first HyMeX Special Observation Period over Croatia

2016 ◽  
Author(s):  
Branka Ivančan-Picek ◽  
Martina Tudor ◽  
Kristian Horvath ◽  
Antonio Stanešić ◽  
Ivatek Ivatek-Šahdan
Keyword(s):  
Data Assimilation ◽  
Weather Prediction ◽  
Heavy Precipitation ◽  
High Impact ◽  
Precipitation Forecast ◽  
Grid Spacing ◽  
Maximum Rainfall ◽  
Weather Events ◽  
High Impact Weather ◽  
Observation Period

Abstract. The HYdrological cycle in the Mediterranean EXperiment (HyMeX) is intended to improve the capabilities to predict high impact weather events. In its framework, the first Special Observation Period (SOP1), 5 September to 6 November 2012, was aimed to study heavy precipitation events and flash floods. Here we present high impact weather events over Croatia that occurred during SOP1. A particular attention is given to eight Intense Observation Periods (IOP)s during which high precipitation occurred over the eastern Adriatic and Dinaric Alps. During the entire SOP1, the operational models forecasts generally represented well medium intensity precipitation, while heavy precipitation was frequently underestimated by the ALADIN 8 km and overestimated at higher resolution (2 km). During IOP2 intensive rainfall event occurred in wider area of the city of Rijeka in the northern Adriatic. Short-range maximum rainfall totals have achieved maximum values ever recorded at Rijeka station since the beginning of measurements in 1958. The rainfall amount measured in intervals of 20, 30 and 40 minutes could be expected once in a more than thousand, few hundreds and hundred years respectively, and they belong to the extraordinarily rare events. The operational precipitation forecast using ALADIN model at 8 km grid spacing underestimated the rainfall intensity. Evaluation of numerical sensitivity experiments suggested that forecast was slightly enhanced by improving the initial conditions through variational data assimilation. The operational non-hydrostatic run at 2 km grid spacing using configuration with ALARO physics package further improved the forecast. This article highlights the need for an intensive observation period in the future over the Adriatic region, to validate the simulated mechanisms and improve numerical weather prediction via data assimilation and model improvements in description of microphysics and air-sea interaction.

scholarly journals Overview of the first HyMeX special observation period over Croatia

2016 ◽  
Vol 16 (12) ◽  
pp. 2657-2682 ◽  
Author(s):  
Branka Ivančan-Picek ◽  
Martina Tudor ◽  
Kristian Horvath ◽  
Antonio Stanešić ◽  
Stjepan Ivatek-Šahdan
Keyword(s):  
Data Assimilation ◽  
Heavy Precipitation ◽  
High Impact ◽  
Precipitation Forecast ◽  
Grid Spacing ◽  
Maximum Rainfall ◽  
Northern Adriatic ◽  
Weather Events ◽  
High Impact Weather ◽  
Observation Period

Abstract. The HYdrological cycle in the Mediterranean EXperiment (HyMeX) is intended to improve the capabilities of predicting high-impact weather events. Within its framework, the aim of the first special observation period (SOP1), 5 September to 6 November 2012, was to study heavy precipitation events and flash floods. Here, we present high-impact weather events over Croatia that occurred during SOP1. Particular attention is given to eight intense observation periods (IOPs), during which high precipitation occurred over the eastern Adriatic and Dinaric Alps. During the entire SOP1, the operational model forecasts generally well represented medium intensity precipitation, but heavy precipitation was frequently underestimated by the ALADIN model at an 8 km grid spacing and was overestimated at a higher resolution (2 km grid spacing). During IOP2, intensive rainfall occurred over a wider area around the city of Rijeka in the northern Adriatic. The short-range maximum rainfall totals were the largest ever recorded at the Rijeka station since the beginning of measurements in 1958. The rainfall amounts measured in intervals of 20, 30 and 40 min were exceptional, with return periods that exceeded a thousand, a few hundred and one hundred years, respectively. The operational precipitation forecast using the ALADIN model at an 8 km grid spacing provided guidance regarding the event but underestimated the rainfall intensity. An evaluation of numerical sensitivity experiments suggested that the forecast was slightly enhanced by improving the initial conditions through variational data assimilation. The operational non-hydrostatic run at a 2 km grid spacing using a configuration with the ALARO physics package further improved the forecast. This article highlights the need for an intensive observation period in the future over the Adriatic region to validate the simulated mechanisms and improve numerical weather predictions via data assimilation and model improvements in descriptions of microphysics and air–sea interactions.

scholarly journals The Impact of Weather Forecast Inconsistency on User Trust

2020 ◽  
Vol 12 (4) ◽  
pp. 679-694 ◽  
Author(s):  
Jessica N. Burgeno ◽  
Susan L. Joslyn
Keyword(s):  
Experimental Studies ◽  
Weather Forecast ◽  
Snow Accumulation ◽  
School Closure ◽  
Accurate Information ◽  
Weather Forecasts ◽  
Weather Events ◽  
High Impact Weather ◽  
The Impact ◽  
User Trust

AbstractFor high-impact weather events, forecasts often start days in advance. Forecasters believe that consistency among subsequent forecasts is important to user trust and can be reluctant to make changes when newer, potentially more accurate information becomes available. However, to date, there is little empirical evidence for an effect of inconsistency among weather forecasts on user trust, although the reduction in trust due to inaccuracy is well documented. The experimental studies reported here compared the effects of forecast inconsistency and inaccuracy on user trust. Participants made several school closure decisions based on snow accumulation forecasts for one and two days prior to the target event. Consistency and accuracy were varied systematically. Although inconsistency reduced user trust, the effect of the reduction due to inaccuracy was greater in most cases suggesting that it is inadvisable for forecasters to sacrifice accuracy in favor of consistency.

scholarly journals Site-specific analog weather-forecast system for northwest Himalaya, India

2008 ◽  
Vol 49 ◽  
pp. 224-230 ◽  
Author(s):  
Dan Singh ◽  
Amreek Singh ◽  
Ashwagosha Ganju
Keyword(s):  
Weather Forecasting ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Analog Model ◽  
Site Specific ◽  
Northwest Himalaya ◽  
Weather Forecasts ◽  
The Past ◽  
Weather Events ◽  
Weather Situation

AbstractIn an analog weather-forecasting procedure, recorded weather in the past analogs corresponding to the current weather situation is used to predict future weather. Consistent with the procedure, a theoretical framework is developed to predict weather at a specific site in the Pir Panjal range of the northwest Himalaya, India, using surface weather observations of the past ten winters (1991/92 to 2001/02) 3 days in advance. Weather predictions were made as snow day with quantitative snowfall category or no-snow day, for day1 through day3. As currently deployed, the procedure routinely provides a 3 day point weather forecast as guidance information to a weather and avalanche forecaster. Forecasts by analog model are evaluated by the various accuracy measures achieved for an independent dataset of three winters (2002/03 to 2004/05). The results indicate that weather forecasts by analog model are quite reliable, in that forecast accuracy corresponds closely to the relative frequencies of observed weather events. Moreover, qualitative weather (snow day or no-snow day) and quantitative categorical snowfall forecasts (quantitative snowfall category for snow day) are better than reference forecasts based on persistence and climatology for day1 predictions. Site-specific snowfall forecast guidance may play a major role in assessing avalanche danger, and accordingly formulating an avalanche forecast for a given area in advance.

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