scholarly journals Forecasts covering one month using a cut-cell model

2013 ◽  
Vol 6 (4) ◽  
pp. 875-882 ◽  
Author(s):  
J. Steppeler ◽  
S.-H. Park ◽  
A. Dobler
Keyword(s):  
Cell Model ◽  
Control Model ◽  
Precipitation Forecast ◽  
Target Area ◽  
Strong Impact ◽  
Monthly Precipitation ◽  
Small Areas ◽  
Cut Cell ◽  
Terrain Following ◽  
The Impact

Abstract. This paper investigates the impact and potential use of the cut-cell vertical discretisation for forecasts covering five days and climate simulations. A first indication of the usefulness of this new method is obtained by a set of five-day forecasts, covering January 1989 with six forecasts. The model area was chosen to include much of Asia, the Himalayas and Australia. The cut-cell model LMZ (Lokal Modell with z-coordinates) provides a much more accurate representation of mountains on model forecasts than the terrain-following coordinate used for comparison. Therefore we are in particular interested in potential forecast improvements in the target area downwind of the Himalayas, over southeastern China, Korea and Japan. The LMZ has previously been tested extensively for one-day forecasts on a European area. Following indications of a reduced temperature error for the short forecasts, this paper investigates the model error for five days in an area influenced by strong orography. The forecasts indicated a strong impact of the cut-cell discretisation on forecast quality. The cut-cell model is available only for an older (2003) version of the model LM (Lokal Modell). It was compared using a control model differing by the use of the terrain-following coordinate only. The cut-cell model improved the precipitation forecasts of this old control model everywhere by a large margin. An improved, more transferable version of the terrain-following model LM has been developed since then under the name CLM (Climate version of the Lokal Modell). The CLM has been used and tested in all climates, while the LM was used for small areas in higher latitudes. The precipitation forecasts of the cut-cell model were compared also to the CLM. As the cut-cell model LMZ did not incorporate the developments for CLM since 2003, the precipitation forecast of the CLM was not improved in all aspects. However, for the target area downstream of the Himalayas, the cut-cell model considerably improved the prediction of the monthly precipitation forecast even in comparison with the modern CLM version. The cut-cell discretisation seems to improve in particular the localisation of precipitation, while the improvements leading from LM to CLM had a positive effect mainly on amplitude.

scholarly journals Forecasts covering one month using a cut cell model

2013 ◽  
Vol 6 (1) ◽  
pp. 625-643
Author(s):  
J. Steppeler ◽  
S.-H. Park ◽  
A. Dobler
Keyword(s):  
Cell Model ◽  
Control Model ◽  
Precipitation Forecast ◽  
Target Area ◽  
Strong Impact ◽  
Monthly Precipitation ◽  
Cut Cell ◽  
Terrain Following ◽  
The Impact ◽  
The Himalaya

Abstract. This paper investigates the impact and potential use of the cut cell vertical discretisation for forecasts of 5 days and climate simulations. A first indication of the usefulness of this new method is obtained by a set of five-day forecasts, covering January 1989 by 6 forecasts. The model area was chosen to include much of Asia, the Himalayas and Australia. The cut cell model LMZ provides a much more accurate representation of mountains on model forecasts than the terrain following coordinate used for comparison. Therefore we are in particular interested in potential forecast improvements in the target area downwind of the Himalaya, over South East China, Korea and Japan. The LMZ has been tested so far extensively for one-day forecasts on an European area. Following indications of a reduced temperature error for the short forecasts, this paper investigates the model error for five days in an area influenced by strong orography. The forecasts indicated a strong impact of the cut cell discretisation on forecast quality. The cut cell model is available only of an older (2003) Version of the model LM. It was compared using a control model differing by the use of the terrain following coordinate only. The cut cell model improved the precipitation forecasts of this old control model everywhere by a large margin. An improved version of the terrain following model LM has been developed since then under the name CLM. The CLM has been used and tested in all climates, while the LM was used for small areas in higher latitudes. The precipitation forecasts of cut cell model were compared also to the CLM. As the cut cell model LMZ did not incorporate the developments for CLM since 2003, the precipitation forecast of the CLM was not improved in all aspects. However, for the target area downstream of the Himalaya, the cut cell model improved the prediction of the monthly precipitation forecast even in comparison with the modern model version CLM considerably. The cut cell discretisation seems to improve in particular the localisation of precipitation, while the improvements leading from LM to CLM had a positive effect mainly on amplitude.

scholarly journals Impact of ASAR soil moisture data on the MM5 precipitation forecast for the Tanaro flood event of April 2009

2011 ◽  
Vol 11 (12) ◽  
pp. 3135-3149 ◽  
Author(s):  
G. Panegrossi ◽  
R. Ferretti ◽  
L. Pulvirenti ◽  
N. Pierdicca
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Land Surface ◽  
Ground Truth ◽  
Rain Gauge ◽  
Precipitation Forecast ◽  
Flood Event ◽  
Strong Impact ◽  
Moisture Field ◽  
The Impact

Abstract. The representation of land-atmosphere interactions in weather forecast models has a strong impact on the Planetary Boundary Layer (PBL) and, in turn, on the forecast. Soil moisture is one of the key variables in land surface modelling, and an inadequate initial soil moisture field can introduce major biases in the surface heat and moisture fluxes and have a long-lasting effect on the model behaviour. Detecting the variability of soil characteristics at small scales is particularly important in mesoscale models because of the continued increase of their spatial resolution. In this paper, the high resolution soil moisture field derived from ENVISAT/ASAR observations is used to derive the soil moisture initial condition for the MM5 simulation of the Tanaro flood event of April 2009. The ASAR-derived soil moisture field shows significantly drier conditions compared to the ECMWF analysis. The impact of soil moisture on the forecast has been evaluated in terms of predicted precipitation and rain gauge data available for this event have been used as ground truth. The use of the drier, highly resolved soil moisture content (SMC) shows a significant impact on the precipitation forecast, particularly evident during the early phase of the event. The timing of the onset of the precipitation, as well as the intensity of rainfall and the location of rain/no rain areas, are better predicted. The overall accuracy of the forecast using ASAR SMC data is significantly increased during the first 30 h of simulation. The impact of initial SMC on the precipitation has been related to the change in the water vapour field in the PBL prior to the onset of the precipitation, due to surface evaporation. This study represents a first attempt to establish whether high resolution SAR-based SMC data might be useful for operational use, in anticipation of the launch of the Sentinel-1 satellite.

scholarly journals Improvement of RAMS precipitation forecast at the short-range through lightning data assimilation

2017 ◽  
Vol 17 (1) ◽  
pp. 61-76 ◽  
Author(s):  
Stefano Federico ◽  
Marco Petracca ◽  
Giulia Panegrossi ◽  
Stefano Dietrich
Keyword(s):  
Data Assimilation ◽  
Water Vapour ◽  
Short Range ◽  
Daily Precipitation ◽  
Atmospheric Modeling ◽  
Probability Of Detection ◽  
Precipitation Forecast ◽  
Target Area ◽  
Total Lightning ◽  
The Impact

Abstract. This study shows the application of a total lightning data assimilation technique to the RAMS (Regional Atmospheric Modeling System) forecast. The method, which can be used at high horizontal resolution, helps to initiate convection whenever flashes are observed by adding water vapour to the model grid column. The water vapour is added as a function of the flash rate, local temperature, and graupel mixing ratio. The methodology is set up to improve the short-term (3 h) precipitation forecast and can be used in real-time forecasting applications. However, results are also presented for the daily precipitation for comparison with other studies. The methodology is applied to 20 cases that occurred in fall 2012, which were characterized by widespread convection and lightning activity. For these cases a detailed dataset of hourly precipitation containing thousands of rain gauges over Italy, which is the target area of this study, is available through the HyMeX (HYdrological cycle in the Mediterranean Experiment) initiative. This dataset gives the unique opportunity to verify the precipitation forecast at the short range (3 h) and over a wide area (Italy). Results for the 27 October case study show how the methodology works and its positive impact on the 3 h precipitation forecast. In particular, the model represents better convection over the sea using the lightning data assimilation and, when convection is advected over the land, the precipitation forecast improves over the land. It is also shown that the precise location of convection by lightning data assimilation improves the precipitation forecast at fine scales (meso-β). The application of the methodology to 20 cases gives a statistically robust evaluation of the impact of the total lightning data assimilation on the model performance. Results show an improvement of all statistical scores, with the exception of the bias. The probability of detection (POD) increases by 3–5 % for the 3 h forecast and by more than 5 % for daily precipitation, depending on the precipitation threshold considered. Score differences between simulations with or without data assimilation are significant at 95 % level for most scores and thresholds considered, showing the positive and statistically robust impact of the lightning data assimilation on the precipitation forecast.

scholarly journals High resolution numerical study of the Algiers 2001 flash flood: sensitivity to the upper-level potential vorticity anomaly

2006 ◽  
Vol 7 ◽  
pp. 251-257 ◽  
Author(s):  
S. Argence ◽  
D. Lambert ◽  
E. Richard ◽  
N. Söhne ◽  
J.-P. Chaboureau ◽  
...  
Keyword(s):  
Potential Vorticity ◽  
Flash Flood ◽  
Numerical Study ◽  
Western Mediterranean ◽  
Precipitation Forecast ◽  
Inversion Method ◽  
Strong Impact ◽  
Upper Level ◽  
Vorticity Anomaly ◽  
The Impact

Abstract. From 9 to 11 November 2001, intense cyclogenesis affected the northern coasts of Africa and more particularly the densely populated city of Algiers. During the morning of 10 November, more than 130 mm of precipitation was recorded at Bouzareah and resulted in mudslides which devastated the Bab-el-Oued district. This disaster caused more than 700 casualties and catastrophic damage. Like many other heavy rainstorms in the western Mediterranean, this event was associated with the presence of an upper-level trough materialized by a deep stratospheric intrusion and characterized by high potential vorticity values. In this study, the impact of this synoptic structure on the localization and intensity of the precipitation which affected Algiers is investigated using a potential vorticity (PV) inversion method coupled for the first time with the French non-hydrostatic MESO-NH model. A set of perturbed synoptic environments was designed by slightly modifying the extent and the intensity of the coherent potential vorticity structures in the operational ARPEGE analysis. It is shown that such modifications may have a strong impact on the fine-scale precipitation forecast in the Algiers region, thereby demonstrating the fundamental role played by the potential vorticity anomaly during this exceptional meteorological event.

When Do Psychopathic Traits Affect Cooperative Behavior?: An Iterated Prisoner's Dilemma Experimental Study

2020 ◽  
Author(s):  
M Testori ◽  
M Kempf ◽  
RB Hoyle ◽  
Hedwig Eisenbarth
Keyword(s):  
Prisoner's Dilemma ◽  
Cooperative Behavior ◽  
Prisoner’S Dilemma ◽  
Selection Procedure ◽  
Psychopathic Traits ◽  
Strong Impact ◽  
Iterated Prisoner's Dilemma ◽  
Human Decision ◽  
The Impact ◽  
Iterated Prisoner’S Dilemma

© 2019 Hogrefe Publishing. Personality traits have been long recognized to have a strong impact on human decision-making. In this study, a sample of 314 participants took part in an online game to investigate the impact of psychopathic traits on cooperative behavior in an iterated Prisoner's dilemma game. We found that disinhibition decreased the maintenance of cooperation in successive plays, but had no effect on moving toward cooperation after a previous defection or on the overall level of cooperation over rounds. Furthermore, our results underline the crucial importance of a good model selection procedure, showing how a poor choice of statistical model can provide misleading results.

The Impact of Economic Crisis on Tourism Industry: A Bangladesh Perspective

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Md. Ziaul Haque
Keyword(s):  
Economic Crisis ◽  
Tourism Industry ◽  
Political Crisis ◽  
Strong Impact ◽  
Negative Consequences ◽  
Policy Makers ◽  
Tourism Product ◽  
International Tourist ◽  
Sustained Recovery ◽  
The Impact

The tourism sector is experiencing numerous challenges as a result of the global economic crisis. After a significant contraction in 2009, tourism rebounded strongly  in  2010  and  in  2011  the  international  tourist  arrivals  and  receipts  are projected to increase substantially. The Tourism industry is expected to show a sustained recovery in 2012. The crisis has particularly strong impact and slightly negative consequences in Bangladesh. The country is undergoing a political crisis, as well, and it seems that the forthcoming elections may be the only solution for the restoration of stability and social peace.  In addition, tourism can be the driving force behind Bangladesh economic recovery. However, for its achievement the country’s policy makers should take several measures towards restructuring and improving the sector. These measures include: enhancement of alternative forms of tourism; environmental protection; creation of quality infrastructure; and boost of competitiveness through a tourism product that offers value for money

The Impact Of Economic Crisis On Tourism Industry: A Bangladesh Perspective

2015 ◽  
Vol 1 (1) ◽  
pp. 15
Author(s):  
Md. Ziaul Haque
Keyword(s):  
Economic Crisis ◽  
Tourism Industry ◽  
Political Crisis ◽  
Strong Impact ◽  
Negative Consequences ◽  
Policy Makers ◽  
Tourism Product ◽  
International Tourist ◽  
Sustained Recovery ◽  
The Impact

The tourism sector is experiencing numerous challenges as a result of the global economic crisis. After a significant contraction in 2009, tourism rebounded strongly  in  2010  and  in  2011  the  international  tourist  arrivals  and  receipts  are projected to increase substantially. The Tourism industry is expected to show a sustained recovery in 2012. The crisis has particularly strong impact and slightly negative consequences in Bangladesh. The country is undergoing a political crisis, as well, and it seems that the forthcoming elections may be the only solution for the restoration of stability and social peace.  In addition, tourism can be the driving force behind Bangladesh economic recovery. However, for its achievement the country’s policy makers should take several measures towards restructuring and improving the sector. These measures include: enhancement of alternative forms of tourism; environmental protection; creation of quality infrastructure; and boost of competitiveness through a tourism product that offers value for money

scholarly journals Performance of Adaptive Unstructured Mesh Modelling in Idealized Advection Cases over Steep Terrains

Atmosphere ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 444 ◽  
Author(s):  
Jinxi Li ◽  
Jie Zheng ◽  
Jiang Zhu ◽  
Fangxin Fang ◽  
Christopher. Pain ◽  
...  
Keyword(s):  
Unstructured Mesh ◽  
Computational Cost ◽  
Adaptive Mesh ◽  
Galerkin Finite Element Method ◽  
Adaptive Meshes ◽  
Galerkin Finite Element ◽  
Computational Costs ◽  
Cut Cell ◽  
Discontinuous Galerkin Finite Element ◽  
Terrain Following

Advection errors are common in basic terrain-following (TF) coordinates. Numerous methods, including the hybrid TF coordinate and smoothing vertical layers, have been proposed to reduce the advection errors. Advection errors are affected by the directions of velocity fields and the complexity of the terrain. In this study, an unstructured adaptive mesh together with the discontinuous Galerkin finite element method is employed to reduce advection errors over steep terrains. To test the capability of adaptive meshes, five two-dimensional (2D) idealized tests are conducted. Then, the results of adaptive meshes are compared with those of cut-cell and TF meshes. The results show that using adaptive meshes reduces the advection errors by one to two orders of magnitude compared to the cut-cell and TF meshes regardless of variations in velocity directions or terrain complexity. Furthermore, adaptive meshes can reduce the advection errors when the tracer moves tangentially along the terrain surface and allows the terrain to be represented without incurring in severe dispersion. Finally, the computational cost is analyzed. To achieve a given tagging criterion level, the adaptive mesh requires fewer nodes, smaller minimum mesh sizes, less runtime and lower proportion between the node numbers used for resolving the tracer and each wavelength than cut-cell and TF meshes, thus reducing the computational costs.

scholarly journals Seasonal streamflow forecasting by conditioning climatology with precipitation indices

2017 ◽  
Vol 21 (3) ◽  
pp. 1573-1591 ◽  
Author(s):  
Louise Crochemore ◽  
Maria-Helena Ramos ◽  
Florian Pappenberger ◽  
Charles Perrin
Keyword(s):  
Long Range ◽  
Precipitation Forecast ◽  
Low Flow ◽  
Drought Risk ◽  
Streamflow Forecasting ◽  
Streamflow Forecasts ◽  
Precipitation Indices ◽  
Seasonal Streamflow ◽  
Prediction Approach ◽  
The Impact

Abstract. Many fields, such as drought-risk assessment or reservoir management, can benefit from long-range streamflow forecasts. Climatology has long been used in long-range streamflow forecasting. Conditioning methods have been proposed to select or weight relevant historical time series from climatology. They are often based on general circulation model (GCM) outputs that are specific to the forecast date due to the initialisation of GCMs on current conditions. This study investigates the impact of conditioning methods on the performance of seasonal streamflow forecasts. Four conditioning statistics based on seasonal forecasts of cumulative precipitation and the standardised precipitation index were used to select relevant traces within historical streamflows and precipitation respectively. This resulted in eight conditioned streamflow forecast scenarios. These scenarios were compared to the climatology of historical streamflows, the ensemble streamflow prediction approach and the streamflow forecasts obtained from ECMWF System 4 precipitation forecasts. The impact of conditioning was assessed in terms of forecast sharpness (spread), reliability, overall performance and low-flow event detection. Results showed that conditioning past observations on seasonal precipitation indices generally improves forecast sharpness, but may reduce reliability, with respect to climatology. Conversely, conditioned ensembles were more reliable but less sharp than streamflow forecasts derived from System 4 precipitation. Forecast attributes from conditioned and unconditioned ensembles are illustrated for a case of drought-risk forecasting: the 2003 drought in France. In the case of low-flow forecasting, conditioning results in ensembles that can better assess weekly deficit volumes and durations over a wider range of lead times.

Cost of Dementia and Its Correlation With Dependence

2016 ◽  
Vol 28 (8) ◽  
pp. 1448-1464 ◽  
Author(s):  
Örjan Åkerborg ◽  
Andrea Lang ◽  
Anders Wimo ◽  
Anders Sköldunger ◽  
Laura Fratiglioni ◽  
...  
Keyword(s):  
Cognitive Ability ◽  
Resource Utilization ◽  
Annual Cost ◽  
Neuropsychiatric Symptoms ◽  
Dementia Care ◽  
Cost Of Care ◽  
Path Model ◽  
National Study ◽  
Strong Impact ◽  
The Impact

Objective: To estimate the cost of dementia care and its relation to dependence. Method: Disease severity and health care resource utilization was retrieved from the Swedish National Study on Aging and Care. Informal care was assessed with the Resource Utilization in Dementia instrument. A path model investigates the relationship between annual cost of care and dependence, cognitive ability, functioning, neuropsychiatric symptoms, and comorbidities. Results: Average annual cost among patients diagnosed with dementia was €43,259, primarily incurred by accommodation. Resource use, that is, institutional care, community care, and accommodation, and corresponding costs increased significantly by increasing dependency. Path analysis showed that cognitive ability, functioning, and neuropsychiatric symptoms were significantly correlated with dependence, which in turn had a strong impact on annual cost. Discussion: This study confirms that cost of dementia care increases with dependence and that the impact of other disease indicators is mainly mediated by dependence.

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