scholarly journals A case study of the impact of INSAT derived humidity profiles on precipitation forecast by limited area model

MAUSAM ◽  
2022 ◽  
Vol 52 (4) ◽  
pp. 647-654
Author(s):  
Y .V. RAMA RAO ◽  
K. PRASAD ◽  
SANT PRASAD
Keyword(s):  
Regional Analysis ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Forecast System ◽  
Rainfall Prediction ◽  
Moisture Analysis ◽  
Analysis Scheme ◽  
The Impact ◽  
Humidity Profiles

The impact of humidity profiles estimated from INSAT digital IR cloud imagery data on initial moisture analysis in the IMD's operational limited area forecast system has been investigated. Method for assimilation of humidity profiles data as pseudo observations in the analysis scheme has been developed and implemented in the regional analysis scheme. Verification of humidity analysis with this data has shown substantial improvements in the moisture analysis over the data sparse region of tropics. Impact of the improved humidity analysis on model predicted rainfall is examined. The experiments show improved rainfall prediction.

scholarly journals Numerical simulations of June 7, 2020 convective precipitation over Slovakia using deterministic, probabilistic, and convection-permitting approaches

Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 571-607
Author(s):  
André Simon ◽  
Martin Belluš ◽  
Katarína Čatlošová ◽  
Mária Derková ◽  
Martin Dian ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Weather Prediction ◽  
Severe Weather ◽  
Precipitation Forecast ◽  
Convective Precipitation ◽  
Small Scale ◽  
Limited Area ◽  
Systematic Effect ◽  
The Impact

The paper presented is dedicated to the evaluation of the influence of various improvements to the numerical weather prediction (NWP) systems exploited at the Slovak Hydrometeorological Institute (SHMÚ). The impact was illustrated in a case study with multicell thunderstorms and the results were confronted with the reference analyses from the INCA nowcasting system, regional radar reflectivity data, and METEOSAT satellite imagery. The convective cells evolution was diagnosed in non-hydrostatic dynamics experiments to study weak mesoscale vortices and updrafts. The growth of simulated clouds and evolution of the temperature at their top were compared with the brightness temperature analyzed from satellite imagery. The results obtained indicated the potential for modeling and diagnostics of small-scale structures within the convective cloudiness, which could be related to severe weather. Furthermore, the non-hydrostatic dynamics experiments related to the stability and performance improvement of the time scheme led to the formulation of a new approach to linear operator definition for semi-implicit scheme (in text referred as NHHY). We demonstrate that the execution efficiency has improved by more than 20%. The exploitation of several high resolution measurement types in data assimilation contributed to more precise position of predicted patterns and precipitation representation in the case study. The non-hydrostatic dynamics provided more detailed structures. On the other hand, the potential of a single deterministic forecast of prefrontal heavy precipitation was not as high as provided by the ensemble system. The prediction of a regional ensemble system A-LAEF (ALARO Limited Area Ensemble Forecast) enhanced the localization of precipitation patterns. Though, this was rather due to the simulation of uncertainty in the initial conditions and also because of the stochastic perturbation of physics tendencies. The various physical parameterization setups of A-LAEF members did not exhibit a systematic effect on precipitation forecast in the evaluated case. Moreover, the ensemble system allowed an estimation of uncertainty in a rapidly developing severe weather case, which was high even at very short range.

scholarly journals Predictability of intense rain storms in the Central Mediterraneanbasin: sensitivity to upper-level forcing

2007 ◽  
Vol 12 ◽  
pp. 5-18 ◽  
Author(s):  
S. Federico ◽  
E. Avolio ◽  
C. Bellecci ◽  
A. Lavagnini ◽  
R. L. Walko
Keyword(s):  
Water Vapour ◽  
Precipitation Forecast ◽  
Ensemble Prediction ◽  
Limited Area ◽  
Ensemble Prediction System ◽  
Working Hypothesis ◽  
Intense Storm ◽  
Study Support ◽  
Upper Level ◽  
The Impact

Abstract. This study investigates the sensitivity of a moderate-intense storm that occurred over Calabria, southern Italy, to upper-tropospheric forcing from a Potential Vorticity (PV) perspective. A prominent mid-troposheric trough can be identified for this event, which occurred between 22–24 May 2002, and serves as the precursor agent for the moderate-intense precipitation recorded. The working hypothesis is that the uncertainty in the representation of the upper-level disturbance has a major impact on the precipitation forecast and we test the hypothesis in a two-step approach. First, we examine the degree of uncertainty by comparing five different scenarios in a Limited area model Ensemble Prediction System (LEPS) framework which utilizes the height of the dynamical tropopause as the discriminating variable. Pseudo water vapour images of different scenarios are compared to the corresponding METEOSAT 7 water vapour image at a specific time, antecedent to the rain occurrence over Calabria, in order to evaluate the reliability of the different precipitation scenarios simulated by the LEPS. Second, we examine the impact of upper tropospheric PV variations on precipitation by comparing model simulations with slightly different initial PV fields. Initial velocity and mass fields in each case are balanced with the chosen PV perturbation using a PV inversion technique. The results of this study support the working hypothesis.

scholarly journals Effects of Increasing Horizontal Resolution in a Convection-Permitting Model on Flood Forecasting: The 2011 Dramatic Events in Liguria, Italy

2015 ◽  
Vol 16 (4) ◽  
pp. 1843-1856 ◽  
Author(s):  
Silvio Davolio ◽  
Francesco Silvestro ◽  
Piero Malguzzi
Keyword(s):  
High Resolution ◽  
Weather Prediction ◽  
Flood Forecasting ◽  
Horizontal Resolution ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Flood Prediction ◽  
Meteorological Model ◽  
The Impact ◽  
Atmospheric Simulations

Abstract Coupling meteorological and hydrological models is a common and standard practice in the field of flood forecasting. In this study, a numerical weather prediction (NWP) chain based on the BOLogna Limited Area Model (BOLAM) and the MOdello LOCale in Hybrid coordinates (MOLOCH) was coupled with the operational hydrological forecasting chain of the Ligurian Hydro-Meteorological Functional Centre to simulate two major floods that occurred during autumn 2011 in northern Italy. Different atmospheric simulations were performed by varying the grid spacing (between 1.0 and 3.0 km) of the high-resolution meteorological model and the set of initial/boundary conditions driving the NWP chain. The aim was to investigate the impact of these parameters not only from a meteorological perspective, but also in terms of discharge predictions for the two flood events. The operational flood forecasting system was thus used as a tool to validate in a more pragmatic sense the quantitative precipitation forecast obtained from different configurations of the NWP system. The results showed an improvement in flood prediction when a high-resolution grid was employed for atmospheric simulations. In turn, a better description of the evolution of the precipitating convective systems was beneficial for the hydrological prediction. Although the simulations underestimated the severity of both floods, the higher-resolution model chain would have provided useful information to the decision-makers in charge of protecting citizens.

scholarly journals Impact of Radiance Data Assimilation on the Prediction of Heavy Rainfall in RMAPS: A Case Study

2018 ◽  
Vol 10 (9) ◽  
pp. 1380 ◽  
Author(s):  
Yanhui Xie ◽  
Jiancheng Shi ◽  
Shuiyong Fan ◽  
Min Chen ◽  
Youjun Dou ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Heavy Rainfall ◽  
Precipitation Forecast ◽  
Observation Data ◽  
Rainfall Events ◽  
Satellite Radiance Data ◽  
Radiance Data ◽  
The Impact ◽  
Heavy Rainfall Events

Herein, a case study on the impact of assimilating satellite radiance observation data into the rapid-refresh multi-scale analysis and prediction system (RMAPS) is presented. This case study targeted the 48 h period from 19–20 July 2016, which was characterized by the passage of a low pressure system that produced heavy rainfall over North China. Two experiments were performed and 24 h forecasts were produced every 3 h. The results indicated that the forecast prior to the satellite radiance data assimilation could not accurately predict heavy rainfall events over Beijing and the surrounding area. The assimilation of satellite radiance data from the advanced microwave sounding unit-A (AMSU-A) and microwave humidity sounding (MHS) improved the skills of the quantitative precipitation forecast to a certain extent. In comparison with the control experiment that only assimilated conventional observations, the experiment with the integrated satellite radiance data improved the rainfall forecast accuracy for 6 h accumulated precipitation after about 6 h, especially for rainfall amounts that were greater than 25 mm. The average rainfall score was improved by 14.2% for the 25 mm threshold and by 35.8% for 50 mm of rainfall. The results also indicated a positive impact of assimilating satellite radiances, which was primarily reflected by the improved performance of quantitative precipitation forecasting and higher spatial correlation in the forecast range of 6–12 h. Satellite radiance observations provided certain valuable information that was related to the temperature profile, which increased the scope of the prediction of heavy rainfall and led to an improvement in the rainfall scoring in the RMAPS. The inclusion of satellite radiance observations was found to have a small but beneficial impact on the prediction of heavy rainfall events as it relates to our case study conditions. These findings suggest that the assimilation of satellite radiance data in the RMAPS can provide an overall improvement in heavy rainfall forecasting.

Case study of an Arctic atmospheric river with the ICON model

2021 ◽  
Author(s):  
Hélène Bresson ◽  
Annette Rinke ◽  
Vera Schemann ◽  
Mario Mech ◽  
Susanne Crewell ◽  
...  
Keyword(s):  
Temporal Structure ◽  
Horizontal Resolution ◽  
Added Value ◽  
Arctic Climate ◽  
The Arctic ◽  
Limited Area ◽  
Polar Regions ◽  
Relative Role ◽  
The Impact

<p>The Arctic climate changes faster than the ones of other regions, but the relative role of the individual feedback mechanisms contributing to Arctic amplification is still unclear. Atmospheric Rivers (ARs) are narrow and transient river-style moisture flows from the sub-polar regions. The integrated water vapour transport associated with ARs can explain up to 70% of the precipitation variance north of 70°N. However, there are still uncertainties regarding the specific role and the impact of ARs on the Arctic climate variability. For the first time, the high-resolution ICON modelling framework is used over the Arctic region. Pan Arctic simulations (from 13 km down to ca. 6 and 3 km) are performed to investigate processes related with anomalous moisture transport into the Arctic. Based on a case study over the Nordic Seas, the representation of the atmospheric circulation and the spatio-temporal structure of water vapor, temperature and precipitation within the limited-area mode (LAM) of the ICON model is assessed, and compared with reanalysis and in-situ datasets. Preliminary results show that the moisture intrusion is relatively well represented in the ICON-LAM simulations. The study also shows added value in increasing the model horizontal resolution on the AR representation.</p>

scholarly journals Operational Implementation of the 1D+3D-Var Assimilation Method of Radar Reflectivity Data in the AROME Model

2014 ◽  
Vol 142 (5) ◽  
pp. 1852-1873 ◽  
Author(s):  
Eric Wattrelot ◽  
Olivier Caumont ◽  
Jean-François Mahfouf
Keyword(s):  
Relative Humidity ◽  
Data Assimilation ◽  
Three Dimensional ◽  
Radar Reflectivity ◽  
Precipitation Forecast ◽  
Limited Area ◽  
Short Term ◽  
Background Error ◽  
Reflectivity Data

AbstractThis paper presents results from radar reflectivity data assimilation experiments with the nonhydrostatic limited-area model Application of Research to Operations at Mesoscale (AROME) in an operational context. A one-dimensional (1D) Bayesian retrieval of relative humidity profiles followed by a three-dimensional variational data assimilation (3D-Var) technique is adopted. Several preprocessing procedures of raw reflectivity data are presented and the use of the nonrainy signal in the assimilation is widely discussed and illustrated. This two-step methodology allows the authors to build up a screening procedure that takes into account the evaluation of the results from the 1D Bayesian retrieval. In particular, the 1D retrieval is checked by comparing a pseudoanalyzed reflectivity to the observed reflectivity. Additionally, a physical consistency between the reflectivity innovations and the 1D relative humidity increments is imposed before assimilating relative humidity pseudo-observations with other observations. This allows the authors to counteract the difficulty of the current 3D-Var system to correct strong differences between model and observed clouds from the crude specification of background-error covariances. Assimilation experiments of radar reflectivity data in a preoperational configuration are first performed over a 1-month period. Positive impacts on short-term precipitation forecast scores are systematically found. The evaluation shows improvements on the analysis and also on objective conventional forecast scores, in particular for the model wind field up to 12 h. A case study for a specific precipitating system demonstrates the capacity of the method for improving significantly short-term forecasts of organized convection.

scholarly journals Historic Building Simulation of the Internal Insulation Behavior in Climate of Slovakia in a Case Study

2021 ◽  
Vol 1203 (2) ◽  
pp. 022065
Author(s):  
Kristián Hutkai ◽  
Dušan Katunský ◽  
Marek Zozulák ◽  
Matej Guman
Keyword(s):  
Indoor Environment ◽  
Gravimetric Method ◽  
Wall Structure ◽  
Historic Building ◽  
Moisture Analysis ◽  
Reduce Heat Loss ◽  
Puppet Theatre ◽  
The Impact ◽  
Support Wall

Abstract Main topic of the article speaks about historic building renovation in Košice. Nowadays, the building is in use as puppet theatre. The theatre suffers from various disorders caused by humidity. The envelope of building has been renovated several times, however, over time, the faults return over and over. The article can be divided into two parts. The first one presents the results of moisture analysis of the support wall. The samples from the facade probes were evaluated by gravimetric method. The second part of the article discusses the interior insulation of a historic building. Internal insulation is one of the solutions to reduce heat loss of historic buildings. The use of this type of insulation brings risks that affect the thermal-humidity behaviour of the perimeter structure. These risks are assessed using a simulation model. In addition to the risks, the impact of the insulation on the original wall structure and the impact on the indoor environment were also assessed. Based on the simulation results, we can assess whether the restoration approach is appropriate in this specific case of using insulation. The study shows that the initial humidity of the perimeter wall structure is an important factor for internal insulation. Before applying the internal insulation, it is necessary to examine the moisture and material properties of the masonry.

scholarly journals PERBANDINGAN PREDIKSI CURAH HUJAN GFS METEOROGRAM DENGAN CURAH HUJAN TRMM DI DAS RIAM KANAN KALIMANTAN SELATAN

2015 ◽  
Vol 16 (2) ◽  
pp. 73 ◽  
Author(s):  
Samba Wirahma ◽  
Ibnu Athoillah ◽  
Sutrisno .
Keyword(s):  
Correlation Coefficient ◽  
Catchment Area ◽  
Water Discharge ◽  
Tropical Rainfall Measuring Mission ◽  
Precipitation Forecast ◽  
Global Forecast System ◽  
Weather Modification ◽  
Forecast System ◽  
Tropical Rainfall ◽  
Rainfall Prediction

Teknologi Modifikasi Cuaca (TMC) yang diterapkan oleh BPPT di Kalimantan Selatan dilakukan guna mengatasi kekurangan debit air yang terjadi pada DAS Riam Kanan. Untuk melaksanakan TMC yang efektif dan efisien dibutuhkan prediksi cuaca harian yang akurat dan mendetail pada catchment area (daerah tangkapan hujan) tersebut, khususnya prediksi curah hujan harian. TMC yang diterapkan oleh BPPT menggunakan prediksi yang salah satunya diambil dari Global Forecast System (GFS) Meteorogram. Prediksi tersebut bisa menjadi referensi untuk mengolah dan menganalisis parameter cuaca dengan baik, serta merencanakan dan memutuskan pelaksanaan penerbangan eksekusi selama kegiatan TMC. Untuk menguji ketepatan suatu prediksi, maka diperlukan validasi/perbandingan hasil prediksi dengan data real, yaitu data curah hujan yang dapat diambil dari data Tropical Rainfall Measuring Mission (TRMM).Prediksi curah hujan menggunakan GFS Meteorogram dibandingkan dengan data curah hujan dari TRMM di daerah DAS Riam Kanan menggunakan korelasi Pearson, pengambilan data prediksi GFS dilakukan mulai dari 16 Mei 2014 s/d 31 Mei 2014. Koefisien korelasi yang diambil hanya yang memiliki pola/bentuk hubungan korelasi linear positif (+1). Dari hasil analisis korelasi didapatkan bahwa dari 16 hari pengambilan data di semua lokasi, rata-rata terdapat 8 - 11 hari yang memiliki nilai koefisien korelasi (KK) positif untuk prediksi di hari yang sama dan 6 - 11 hari untuk prediksi Lag_1, dengan nilai KK yang paling banyak muncul yaitu : range 0.4 - 0.7 untuk prediksi 7 hari ke depan, range 0.7 - 0.9 untuk prediksi 5 hari ke depan, dan range 0.9 - 1 untuk prediksi 3 hari ke depan. Dari keenam lokasi titik prediksi dengan nilai koefisien korelasi linear positif yang paling banyak muncul dan memiliki hubungan yang paling kuat adalah di titik Banjarmasin dan DAS bagian Utara.Kata Kunci : prediksi curah hujan GFS, curah hujan TRMM DAS Riam Kanan, koefisien korelasiWeather Modification Technology applied by BPPT in South Kalimantan in order to overcome the shortage of water discharge that occurs in the Riam Kanan Watershed. To implement the weather modification technology an effective and efficient required daily weather predictions are accurate and detail in the catchment area, especially dailiy rainfall prediction. In this Technology, BPPT using prediction from the Global Forecast System (GFS) Meteorogram. This prediction could be a reference to analyze weather parameter, planning, and deciding to do flight execution for weather modification. To verifying accuracy of this prediction, it is necessary validation/ comparison with real data that can be retrieved from the data Tropical Rainfall Measuring Mission (TRMM).Rainfall prediction of GFS Meteorogram compared with data from TRMM rainfall on the Riam Kanan Watershed using Pearson Correlation, GFS forecast data collected from May 16 - May 3,1 2014. The correlation coefficient is taken only has a pattern a positive linear correlation. The result from correlation analysis showed that 16 days of data collection in all locations, on average there are 8 – 11 days have a correlation coefficient is positive for prediction in the same day, and 6 – 11 days for prediction in lag_1 with most value arise of correlation coefficient is 0.4 – 0.7 for prediction of next 7 days, range 0.7 – 0.9 for prediction of next 5 days, and range 0.9 – 1 for prediction of next 3 days. From the six location of prediction points with most value arise of correlation coefficient positive linier and have the strongest relation are in Banjarmasin and northern watershed.Keywords : GFS precipitation forecast, Riam Kanan TRMM rainfall, correlation coefficient

scholarly journals The application of LEPS technique for Quantitative Precipitation Forecast (QPF) in Southern Italy

2006 ◽  
Vol 7 ◽  
pp. 1-8 ◽  
Author(s):  
S. Federico ◽  
E. Avolio ◽  
C. Bellecci ◽  
M. Colacino
Keyword(s):  
Case Studies ◽  
Horizontal Resolution ◽  
Precipitation Forecast ◽  
Computational Time ◽  
Ensemble Prediction ◽  
Limited Area ◽  
Ensemble Prediction System ◽  
Subjective Analysis ◽  
Quantitative Precipitation Forecast ◽  
The Impact

Abstract. This paper reports preliminary results of a Limited area model Ensemble Prediction System (LEPS), based on RAMS, for eight case studies of moderate-intense precipitation over Calabria, the southernmost tip of the Italian peninsula. LEPS aims to transfer the benefits of a probabilistic forecast from global to regional scales in countries where local orographic forcing is a key factor to force convection. To accomplish this task and to limit computational time, in order to implement LEPS operational, we perform a cluster analysis of ECMWF-EPS runs. Starting from the 51 members that forms the ECMWF-EPS we generate five clusters. For each cluster a representative member is selected and used to provide initial and dynamic boundary conditions to RAMS, whose integrations generate LEPS. RAMS runs have 12 km horizontal resolution. Hereafter this ensemble will be referred also as LEPS_12L30. To analyze the impact of enhanced horizontal resolution on quantitative precipitation forecast, LEPS_12L30 forecasts are compared to a lower resolution ensemble, based on RAMS that has 50 km horizontal resolution and 51 members, nested in each ECMWF-EPS member. Hereafter this ensemble will be also referred as LEPS_50L30. LEPS_12L30 and LEPS_50L30 results were compared subjectively for all case studies but, for brevity, results are reported for two "representative" cases only. Subjective analysis is based on ensemble-mean precipitation and probability maps. Moreover, a short summary of objective scores. Maps and scores are evaluated against reports of Calabria regional raingauges network. Results show better LEPS_12L30 performance compared to LEPS_50L30. This is obtained for all case studies selected and strongly suggests the importance of the enhanced horizontal resolution, compared to ensemble population, for Calabria, at least for set-ups and case studies selected in this work.

Cloud-dependent piecewise assimilation based on a hydrometeor-included background error covariance and its impact on regional Numerical Weather Prediction

2021 ◽  
Author(s):  
Deming Meng ◽  
Yaodeng Chen ◽  
Jun Li ◽  
Hongli Wang ◽  
Yuanbing Wang ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Precipitation Forecast ◽  
Background Error ◽  
Single Observation ◽  
Numerical Weather ◽  
Background Error Covariance ◽  
Error Covariance ◽  
Analysis Scheme ◽  
The Impact

AbstractThe background error covariance (B) behaves differently and needs to be carefully defined in cloudy areas due to larger uncertainties caused by models’ inability to correctly represent complex physical processes. This study proposes a new cloud-dependent B strategy by adaptively adjusting the hydrometeor-included B in the cloudy areas according to the cloud index (CI) derived from the satellite-based cloud products. The adjustment coefficient is determined by comparing the error statistics of B for the clear and cloudy areas based on the two-dimensional geographical masks. The comparison highlights the larger forecast errors and manifests the necessity of using appropriate B in cloudy areas. The cloud-dependent B is then evaluated by a series of single observation tests and three-week cycling assimilation and forecasting experiments. The single observation experiments confirm that the cloud-dependent B allows cloud dependency for the multivariate analysis increments and alleviates the discontinuities at the cloud mask borders by treating the CI as an exponent. The impact study on regional numerical weather prediction (NWP) demonstrates that the application of the cloud-dependent B reduces analyses and forecasts bias and increases precipitation forecast skills. Diagnostics of a heavy rainfall case indicate that the application of the cloud-dependent B enhances the moisture, wind, and hydrometeors analyses and forecasts, resulting in more accurate forecasts of accumulated precipitation. The cloud-dependent piecewise analysis scheme proposed herein is extensible, and a more precise definition of CI can improve the analysis, which deserves future investigation.

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