Impact of the Korea Rapid Developing Thunderstorms (K-RDT) product nudging to the convective parameterization over the Korean Peninsula

2020 ◽  
Author(s):  
Namgu Yeo ◽  
Eun-Chul Chang ◽  
Ki-Hong Min
Keyword(s):  
Heavy Rainfall ◽  
Large Scale ◽  
Deep Convection ◽  
Weather Prediction ◽  
Model System ◽  
Prediction Skill ◽  
Precipitation Forecast ◽  
Small Scale ◽  
Convective System ◽  
Convective Cells

<p>In this study, Korea Rapid Developing Thunderstorms (K-RDT) product from geostationary meteorological satellite which represents developing stage of convective cells is nudged to the Simplified Arakawa Schubert (SAS) deep convection scheme using a simple nudging technique in order to improve prediction skill of a heavy rainfall caused by mesoscale convective system over South Korea in the short-term forecast. Impact of the K-RDT information is investigated on the Global/Regional Integrated Model system (GRIMs) regional model program (RMP) system. For the selected heavy rainfall cases, the control run without nudging and two nudging experiments with different nudging period are performed. Although the simulated precipitations in the nudging experiments tend to depend on the distribution of convective cells detected in the K-RDT algorithm, the nudging experiment shows improved precipitation forecast than the control experiment. Particularly, the experiment with nudging for longer time produces better prediction skill. The results present that the small-scale convective cells from the K-RDT which are detected with a 1-km resolution have clear impacts to large-scale atmospheric fields. Therefore, it is suggested that utilizing small-scale information of convective system in the numerical weather prediction can have critical impact to improve forecast skill when the model system, which cannot properly represent sub-grid scale convections.</p>

scholarly journals Simulations of deep convection in the Mediterranean area using 3DVAR of conventional and non-conventional data

2005 ◽  
Vol 2 ◽  
pp. 65-71 ◽  
Author(s):  
R. Ferretti ◽  
C. Faccani ◽  
D. Cimini ◽  
F. S. Marzano ◽  
A. Memmo ◽  
...  
Keyword(s):  
Large Scale ◽  
Initial Conditions ◽  
Deep Convection ◽  
Weather Prediction ◽  
Rain Gauge ◽  
Precipitation Forecast ◽  
Variational Assimilation ◽  
First Case ◽  
Surface Data ◽  
The Mediterranean

Abstract. In autumn deep convection in the Mediterranean region is a common phenomenon. The local events characterized by deep convection are still a difficult task even for high resolution numerical weather prediction. Three flood cases, produced by convection either embedded in a large scale system or locally developed, occurring in Italy, are presented. All these case were not correctly forecasted: Sardinia (Cagliari, 13 November 1999); Calabria (Soverato, 7 September 2000) and Sicily (Catania, 16 September 2003). The first case occurred during the Mesoscale Alpine Programme (MAP) campaign, therefore a lot of data are available; for the second one only data from SSM/I and local rain-gauge are available; the third one occurred during the operational experimentation of the TOUGH project. The last one was not well predicted even using the operational assimilation of ground based GPS. To improve the forecast of these cases the assimilation of several data is tested. The variational assimilation performed using 3DVAR of GPS, SSM/I and surface and upper air data is applied to improve the Initial Conditions of the Sicily case. The Sardinia case is improved using either GPS and surface data, whereas for the Soverato case only ZTD is assimilated. The experiments are performed using the MM5 model from Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR); the model is initialized using the new Initial Conditions produced by the variational assimilation of conventional and non conventional data. The results show that the assimilation of the retrieved quantities does produces large improvement in the precipitation forecast. Large sensitivity to the assimilation of surface data and brightness temperature from SSM/I is found.

scholarly journals Preliminary signs of the initiation of deep convection by GNSS

2012 ◽  
Vol 12 (8) ◽  
pp. 20351-20382
Author(s):  
H. Brenot ◽  
J. Neméghaire ◽  
L. Delobbe ◽  
N. Clerbaux ◽  
M. Van Roozendael
Keyword(s):  
Deep Convection ◽  
Critical Role ◽  
Small Scale ◽  
Convective System ◽  
Weather Forecasts ◽  
Convective Systems ◽  
Infrared Radiance ◽  
Using Data ◽  
Convective Cells

Abstract. This study reports on the exploitation of GNSS for weather forecasts, especially for nowcasting. We focus on GPS observations (post-processing with a time resolution of 15 min) and try to establish typical configurations of the humidity field which characterise convective systems and particularly which supply forerunners of their initiation associated with deep convection. We show the critical role of GNSS horizontal gradients of humidity to detect small scale structures of the troposphere (i.e. convective cells), and then we present our strategy to obtain typical water vapour configurations by GNSS, called "H2O alert". These alerts are based on a dry/wet contrast taking place during a 30 min window before initiation of a convective system. GNSS observations have been assessed for the rainfall event of the 28–29 June 2005 using data from the Belgian dense network (baseline from 5 to 30 km). To validate our GNSS H2O alert, we use the detection of precipitation by C-band weather radar and thermal infrared radiance of the 10.8-μm channel [Ch09] of SEVIRI instrument on METEOSAT Second Generation. Our H2O alert obtains a score of about 80%.

scholarly journals Deep learning for bias correction of MJO prediction

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
H. Kim ◽  
Y. G. Ham ◽  
Y. S. Joo ◽  
S. W. Son
Keyword(s):  
Deep Learning ◽  
Bias Correction ◽  
Numerical Models ◽  
Weather Prediction ◽  
Primary Source ◽  
Correction Method ◽  
Prediction Skill ◽  
Convective System ◽  
Forecast Errors ◽  
Potential Predictability

AbstractProducing accurate weather prediction beyond two weeks is an urgent challenge due to its ever-increasing socioeconomic value. The Madden-Julian Oscillation (MJO), a planetary-scale tropical convective system, serves as a primary source of global subseasonal (i.e., targeting three to four weeks) predictability. During the past decades, operational forecasting systems have improved substantially, while the MJO prediction skill has not yet reached its potential predictability, partly due to the systematic errors caused by imperfect numerical models. Here, to improve the MJO prediction skill, we blend the state-of-the-art dynamical forecasts and observations with a Deep Learning bias correction method. With Deep Learning bias correction, multi-model forecast errors in MJO amplitude and phase averaged over four weeks are significantly reduced by about 90% and 77%, respectively. Most models show the greatest improvement for MJO events starting from the Indian Ocean and crossing the Maritime Continent.

scholarly journals Mesoscale Features Associated with Tropical Cyclone Formations in the Western North Pacific

2008 ◽  
Vol 136 (6) ◽  
pp. 2006-2022 ◽  
Author(s):  
Cheng-Shang Lee ◽  
Kevin K. W. Cheung ◽  
Jenny S. N. Hui ◽  
Russell L. Elsberry
Keyword(s):  
Tropical Cyclone ◽  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Deep Convection ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Synoptic Patterns ◽  
The Mean

Abstract The mesoscale features of 124 tropical cyclone formations in the western North Pacific Ocean during 1999–2004 are investigated through large-scale analyses, satellite infrared brightness temperature (TB), and Quick Scatterometer (QuikSCAT) oceanic wind data. Based on low-level wind flow and surge direction, the formation cases are classified into six synoptic patterns: easterly wave (EW), northeasterly flow (NE), coexistence of northeasterly and southwesterly flow (NE–SW), southwesterly flow (SW), monsoon confluence (MC), and monsoon shear (MS). Then the general convection characteristics and mesoscale convective system (MCS) activities associated with these formation cases are studied under this classification scheme. Convection processes in the EW cases are distinguished from the monsoon-related formations in that the convection is less deep and closer to the formation center. Five characteristic temporal evolutions of the deep convection are identified: (i) single convection event, (ii) two convection events, (iii) three convection events, (iv) gradual decrease in TB, and (v) fluctuating TB, or a slight increase in TB before formation. Although no dominant temporal evolution differentiates cases in the six synoptic patterns, evolutions ii and iii seem to be the common routes taken by the monsoon-related formations. The overall percentage of cases with MCS activity at multiple times is 63%, and in 35% of cases more than one MCS coexisted. Most of the MC and MS cases develop multiple MCSs that lead to several episodes of deep convection. These two patterns have the highest percentage of coexisting MCSs such that potential interaction between these systems may play a role in the formation process. The MCSs in the monsoon-related formations are distributed around the center, except in the NE–SW cases in which clustering of MCSs is found about 100–200 km east of the center during the 12 h before formation. On average only one MCS occurs during an EW formation, whereas the mean value is around two for the other monsoon-related patterns. Both the mean lifetime and time of first appearance of MCS in EW are much shorter than those developed in other synoptic patterns, which indicates that the overall formation evolution in the EW case is faster. Moreover, this MCS is most likely to be found within 100 km east of the center 12 h before formation. The implications of these results to internal mechanisms of tropical cyclone formation are discussed in light of other recent mesoscale studies.

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 RELATIONSHIP BETWEEN HIMAWARI-8-DERIVED OVERSHOOTING TOPS AND EXTREME WEATHER EVENTS IN SOUTHEAST ASIA

2016 ◽  
Vol XLI-B7 ◽  
pp. 325-327
Author(s):  
H. M. Park ◽  
M. A. Kim ◽  
J. Im
Keyword(s):  
Heavy Rainfall ◽  
Rain Rate ◽  
Deep Convection ◽  
Weather Prediction ◽  
Extreme Weather Events ◽  
Strong Wind ◽  
Atmospheric Conditions ◽  
Machine Learning Methods ◽  
Weather Events ◽  
Strong Convection

Severe weathers such as heavy rainfall, floods, strong wind, and lightning are closely related with the strong convection activities of atmosphere. Overshooting tops sometimes occur by deep convection above tropopause, penetrating into the lower stratosphere. Due to its high potential energy, the detection of OT is crucial to understand the climatic phenomena. Satellite images are useful to detect the dynamics of atmospheric conditions using cloud observation. This study used machine learning methods for extracting OTs. The reference cases were built using CloudSat, CALIPSO, and Numerical Weather Prediction (NWP) data with Himawari-8 imagery. As reference cases, 11 OT events were detected. The aim of this study is the investigation of relationship between OTs cases and the occurrences of heavy rainfall. For investigation of OT effects, TRMM daily rain rate data (mm/hr) were collected and averaged at 25 km intervals until 250km from the center of OT cases. As the result, precipitation rate clearly coincides with the distance from the center of OT occurrence.

scholarly journals The 1-way on-line coupled atmospheric chemistry model system MECO(n) – Part 1: Description of the limited-area atmospheric chemistry model COSMO/MESSy

2012 ◽  
Vol 5 (1) ◽  
pp. 87-110 ◽  
Author(s):  
A. Kerkweg ◽  
P. Jöckel
Keyword(s):  
Boundary Conditions ◽  
Atmospheric Chemistry ◽  
General Circulation ◽  
Weather Prediction ◽  
Model System ◽  
Small Scale ◽  
Limited Area ◽  
Tracer Transport ◽  
Chemistry Research ◽  
Supplementary Document

Abstract. The numerical weather prediction model of the Consortium for Small Scale Modelling (COSMO), maintained by the German weather service (DWD), is connected with the Modular Earth Submodel System (MESSy). This effort is undertaken in preparation of a new, limited-area atmospheric chemistry model. Limited-area models require lateral boundary conditions for all prognostic variables. Therefore the quality of a regional chemistry model is expected to improve, if boundary conditions for the chemical constituents are provided by the driving model in consistence with the meteorological boundary conditions. The new developed model is as consistent as possible, with respect to atmospheric chemistry and related processes, with a previously developed global atmospheric chemistry general circulation model: the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. The combined system constitutes a new research tool, bridging the global to the meso-γ scale for atmospheric chemistry research. MESSy provides the infrastructure and includes, among others, the process and diagnostic submodels for atmospheric chemistry simulations. Furthermore, MESSy is highly flexible allowing model setups with tailor made complexity, depending on the scientific question. Here, the connection of the MESSy infrastructure to the COSMO model is documented and also the code changes required for the generalisation of regular MESSy submodels. Moreover, previously published prototype submodels for simplified tracer studies are generalised to be plugged-in and used in the global and the limited-area model. They are used to evaluate the TRACER interface implementation in the new COSMO/MESSy model system and the tracer transport characteristics, an important prerequisite for future atmospheric chemistry applications. A supplementary document with further details on the technical implementation of the MESSy interface into COSMO with a complete list of modifications to the COSMO code is provided.

scholarly journals Modeling the Ocean in Climate Studies

1984 ◽  
Vol 5 ◽  
pp. 133-140 ◽  
Author(s):  
Albert J. Semtner
Keyword(s):  
Turbulent Mixing ◽  
Large Scale ◽  
Deep Convection ◽  
Vertical Mixing ◽  
Mesoscale Eddies ◽  
Small Scale ◽  
Polar Regions ◽  
Sea Ice Extent ◽  
Modeling Strategy ◽  
Climate Studies

A number of processes in the ocean must be modeled properly in order to produce valid estimates of oceanic heat transport, sea-surface temperature, and sea-ice extent in climate studies. These include: wind-driven turbulent mixing and water transport in the surface layer, internal vertical mixing due to several small-scale mechanisms, horizontal and vertical exchanges by mesoscale eddies, mixing along isopycnals, large-scale transport by currents, deep convection in polar regions, and boundary exchanges with atmosphere, ice, and land. Techniques to model these processes are described. Prospects are given for parameterizing the effects of phenomena that cannot be resolved in climate studies, particularly mesoscale eddies. Past simulations of the ocean in climate studies are reviewed. A modeling strategy is outlined for an improved treatment of the ocean, consistent with the computational power soon to be available.

Four Years of Tropical ERA-40 Vorticity Maxima Tracks. Part II: Differences between Developing and Nondeveloping Disturbances

2009 ◽  
Vol 137 (8) ◽  
pp. 2576-2591 ◽  
Author(s):  
Brandon Kerns ◽  
Edward Zipser
Keyword(s):  
Large Scale ◽  
Deep Convection ◽  
Vertical Wind Shear ◽  
Skill Score ◽  
Relative Vorticity ◽  
Prediction Skill ◽  
Tropical Cyclogenesis ◽  
Linear Discriminant ◽  
Predictive Skill ◽  
Heidke Skill Score

Abstract Using a subset of the relative vorticity maxima (VM) tracks described in Part I, large-scale environmental fields, cold cloud area, and rainfall area are used to discriminate between developing and nondeveloping tropical disturbances in the eastern North Pacific (EPAC) and Atlantic Oceans. By using a minimum cold cloud coverage requirement, the nondeveloping VM are limited to disturbances with enhanced low-level relative vorticity and widespread deep convection. Linear discriminant analysis is used to determine the overall discrimination and the relative importance of each predictor for each basin separately. It is important to distinguish the two basins because, for many predictors, the differences between the basins are greater than the differences between developing and nondeveloping VM in each basin. Using the parametric forecast method, there is greater discrimination and prediction skill in the EPAC than in the Atlantic. There are also significant differences between the two basins in terms of the degree of discrimination provided by each of the predictors. Surprisingly, the mean vertical wind shear magnitude is greater for EPAC developing VM than for EPAC nondeveloping VM. Incorporating the satellite-derived predictors marginally improves the potential forecast skill in the EPAC but not in the Atlantic. The prediction skill (Heidke skill score) of tropical cyclogenesis in the Atlantic is similar to what has been obtained in previous studies using cloud cluster tracks. There is greater predictive skill in the EPAC.

scholarly journals Transport by deep convection in basin-scale geostrophic circulation: turbulence-resolving simulations

2019 ◽  
Vol 865 ◽  
pp. 681-719
Author(s):  
Catherine A. Vreugdenhil ◽  
Bishakhdatta Gayen ◽  
Ross W. Griffiths
Keyword(s):  
Boundary Layer ◽  
Thermal Boundary Layer ◽  
Large Scale ◽  
Deep Convection ◽  
Ocean Basin ◽  
Open Ocean ◽  
Small Scale ◽  
Large Scale Circulation ◽  
Buoyancy Forcing ◽  
Basin Scale

Direct numerical simulations are used to investigate the nature of fully resolved small-scale convection and its role in large-scale circulation in a rotating $f$-plane rectangular basin with imposed surface temperature difference. The large-scale circulation has a horizontal geostrophic component and a deep vertical overturning. This paper focuses on convective circulation with no wind stress, and buoyancy forcing sufficiently strong to ensure turbulent convection within the thermal boundary layer (horizontal Rayleigh numbers $Ra\approx 10^{12}{-}10^{13}$). The dynamics are found to depend on the value of a convective Rossby number, $Ro_{\unicode[STIX]{x0394}T}$, which represents the strength of buoyancy forcing relative to Coriolis forces. Vertical convection shifts from a mean endwall plume under weak rotation ($Ro_{\unicode[STIX]{x0394}T}>10^{-1}$) to ‘open ocean’ chimney convection plus mean vertical plumes at the side boundaries under strong rotation ($Ro_{\unicode[STIX]{x0394}T}<10^{-1}$). The overall heat throughput, horizontal gyre transport and zonally integrated overturning transport are then consistent with scaling predictions for flow constrained by thermal wind balance in the thermal boundary layer coupled to vertical advection–diffusion balance in the boundary layer. For small Rossby numbers relevant to circulation in an ocean basin, vertical heat transport from the surface layer into the deep interior occurs mostly in ‘open ocean’ chimney convection while most vertical mass transport is against the side boundaries. Both heat throughput and the mean circulation (in geostrophic gyres, boundary currents and overturning) are reduced by geostrophic constraints.

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