scholarly journals Reply to “Comments on ‘Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence’”

2016 ◽  
Vol 31 (4) ◽  
pp. 1397-1405
Author(s):  
Weihong Qian ◽  
Ning Jiang ◽  
Jun Du
Keyword(s):  
Large Scale ◽  
Value Added ◽  
Heavy Rain ◽  
Heavy Precipitation ◽  
Small Scale ◽  
Precipitation Efficiency ◽  
Long Duration ◽  
Advection Term ◽  
Rain Events ◽  
Mathematical Derivation

Abstract Mathematical derivation, meteorological justification, and comparison to model direct precipitation forecasts are the three main concerns recently raised by Schultz and Spengler about moist divergence (MD) and moist vorticity (MV), which were introduced in earlier work by Qian et al. That previous work demonstrated that MD (MV) can in principle be derived mathematically with a value-added empirical modification. MD (MV) has a solid meteorological basis. It combines ascent motion and high moisture: the two elements necessary for rainfall. However, precipitation efficiency is not considered in MD (MV). Given the omission of an advection term in the mathematical derivation and the lack of precipitation efficiency, MD (MV) might be suitable mainly for heavy rain events with large areal coverage and long duration caused by large-scale quasi-stationary weather systems, but not for local intense heavy rain events caused by small-scale convection. In addition, MD (MV) is not capable of describing precipitation intensity. MD (MV) worked reasonably well in predicting heavy rain locations from short to medium ranges as compared with the ECMWF model precipitation forecasts. MD (MV) was generally worse than (though sometimes similar to) the model heavy rain forecast at shorter ranges (about a week) but became comparable or even better at longer ranges (around 10 days). It should be reiterated that MD (MV) is not intended to be a primary tool for predicting heavy rain areas, especially in the short range, but is a useful parameter for calibrating model heavy precipitation forecasts, as stated in the original paper.

scholarly journals Stochastic modelling and diffusion modes for proper orthogonal decomposition models and small-scale flow analysis

2017 ◽  
Vol 826 ◽  
pp. 888-917 ◽  
Author(s):  
Valentin Resseguier ◽  
Etienne Mémin ◽  
Dominique Heitz ◽  
Bertrand Chapron
Keyword(s):  
Fluid Flow ◽  
Velocity Component ◽  
Large Scale ◽  
Stochastic Modelling ◽  
Wake Flow ◽  
Small Scale ◽  
Cylinder Wake ◽  
Diffusion Term ◽  
Advection Term ◽  
Dimensional Models

We present here a new stochastic modelling approach in the constitution of fluid flow reduced-order models. This framework introduces a spatially inhomogeneous random field to represent the unresolved small-scale velocity component. Such a decomposition of the velocity in terms of a smooth large-scale velocity component and a rough, highly oscillating component gives rise, without any supplementary assumption, to a large-scale flow dynamics that includes a modified advection term together with an inhomogeneous diffusion term. Both of those terms, related respectively to turbophoresis and mixing effects, depend on the variance of the unresolved small-scale velocity component. They bring an explicit subgrid term to the reduced system which enables us to take into account the action of the truncated modes. Besides, a decomposition of the variance tensor in terms of diffusion modes provides a meaningful statistical representation of the stationary or non-stationary structuration of the small-scale velocity and of its action on the resolved modes. This supplies a useful tool for turbulent fluid flow data analysis. We apply this methodology to circular cylinder wake flow at Reynolds numbers $Re=100$ and $Re=3900$. The finite-dimensional models of the wake flows reveal the energy and the anisotropy distributions of the small-scale diffusion modes. These distributions identify critical regions where corrective advection effects, as well as structured energy dissipation effects, take place. In providing rigorously derived subgrid terms, the proposed approach yields accurate and robust temporal reconstruction of the low-dimensional models.

The 2010 Pakistan Flood and Russian Heat Wave: Teleconnection of Hydrometeorological Extremes

2012 ◽  
Vol 13 (1) ◽  
pp. 392-403 ◽  
Author(s):  
William K. M. Lau ◽  
Kyu-Myong Kim
Keyword(s):  
Heat Wave ◽  
Rossby Wave ◽  
Large Scale ◽  
Wave Train ◽  
Intraseasonal Oscillation ◽  
Heavy Rain ◽  
Atmospheric Blocking ◽  
Surface Energy Fluxes ◽  
Upper Level ◽  
Rain Events

Abstract In this paper, preliminary results are presented showing that the two record-setting extreme events during 2010 summer (i.e., the Russian heat wave–wildfires and Pakistan flood) were physically connected. It is found that the Russian heat wave was associated with the development of an extraordinarily strong and prolonged extratropical atmospheric blocking event in association with the excitation of a large-scale atmospheric Rossby wave train spanning western Russia, Kazakhstan, and the northwestern China–Tibetan Plateau region. The southward penetration of upper-level vorticity perturbations in the leading trough of the Rossby wave was instrumental in triggering anomalously heavy rain events over northern Pakistan and vicinity in mid- to late July. Also shown are evidences that the Russian heat wave was amplified by a positive feedback through changes in surface energy fluxes between the atmospheric blocking pattern and an underlying extensive land region with below-normal soil moisture. The Pakistan heavy rain events were amplified and sustained by strong anomalous southeasterly flow along the Himalayan foothills and abundant moisture transport from the Bay of Bengal in connection with the northward propagation of the monsoonal intraseasonal oscillation.

scholarly journals Large-Scale Circulation Patterns Associated with Heavy Spring Rain Events over Taiwan in Strong ENSO and Non-ENSO Years

2003 ◽  
Vol 131 (8) ◽  
pp. 1769-1782 ◽  
Author(s):  
Zhihong Jiang ◽  
George Tai-Jen Chen ◽  
Ming-Chin Wu
Keyword(s):  
Coastal Area ◽  
Large Scale ◽  
Eastern China ◽  
Lower Troposphere ◽  
Heavy Rain ◽  
Interdecadal Variation ◽  
Frontal System ◽  
Rain Events ◽  
The Relationship ◽  
Strong Enso

Abstract Daily rainfall data at 15 stations in Taiwan and the grid dataset of the National Centers for Environmental Prediction–National Center for Atmospheric Research during the period of February–March 1951–2000 were used to reveal the characteristics of large-scale circulations associated with spring heavy rain events over Taiwan in strong ENSO and non-ENSO years. The effect of interdecadal variation on the relationship of spring rainfall and ENSO was also examined. Results showed that the different regimes of interdecadal variation that occurred in the late 1970s exert significant effect on the relationship between ENSO and spring rainfall in Taiwan. A pronounced positive correlation with statistical significance between cold season Niño-3 SST and the following spring rainfall over western Taiwan was only found since the late 1970s. Large-scale environmental conditions associated with the heavy spring rain events in strong ENSO and non-ENSO years were found to be quite different. Intrusion of a weak midlatitude frontal system into the eastern China coastal area coupled with an anomalous anticyclone over the Philippine Sea (PSAC) in the lower troposphere were primarily responsible for the spring heavy rain events in strong ENSO years. On the other hand, the intrusion of a much more intense midlatitude frontal system into China and the coastal area was necessary to generate spring heavy rain events in non-ENSO years. This difference is also instrumental for more frequent occurrence of heavy rainfall events and more rainfall amount observed in ENSO years.

scholarly journals RADAR CHARACTERISTICS OF CLOUD SYSTEMS DURING HEAVY RAIN EVENTS

2020 ◽  
pp. 113-124
Author(s):  
Sergey V. Kostarev ◽  
◽  
Andrey L. Vetrov ◽  
Bogdan A. Sivkov ◽  
Anna A. Pomortseva ◽  
...  
Keyword(s):  
Heavy Rain ◽  
Heavy Precipitation ◽  
Maximum Height ◽  
Doppler Weather Radar ◽  
Statistical Features ◽  
Cloud Systems ◽  
Geometrical Features ◽  
Radar Echo ◽  
Rain Events ◽  
Precipitation Events

The paper analyzes radar characteristics of mesoscale precipitation systems associated with heavy precipitation in Western Urals. The characteristics under study, obtained from the Doppler weather radar, include the maximum height of the radar echo of clouds and precipitation, meteorological phenomena, speed and direction of the radar echo movement. An attempt was made to classify mesoscale precipitation systems with respect to their horizontal scales and geometrical features as well as precipitation patterns. Statistical features of radar characteristics of cloud systems causing heavy rain were calculated taking into account their classification by horizontal scales. Radar meteorological characteristics were obtained from instruments in the Izhevsk city and Ufa city for the warm period of 2016–2017. The results can be used during nowcasting of heavy precipitation events.

scholarly journals Detecting Water Vapor Variability during Heavy Precipitation Events in Hong Kong Using the GPS Tomographic Technique

2017 ◽  
Vol 34 (5) ◽  
pp. 1001-1019 ◽  
Author(s):  
Biyan Chen ◽  
Zhizhao Liu ◽  
Wai-Kin Wong ◽  
Wang-Chun Woo
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Heavy Rain ◽  
Heavy Precipitation ◽  
Radiosonde Data ◽  
Weather Forecasts ◽  
Moisture Variation ◽  
Tomographic Technique ◽  
Rain Events ◽  
Precipitation Events

AbstractWater vapor has a strong influence on the evolution of heavy precipitation events due to the huge latent heat associated with the phase change process of water. Accurate monitoring of atmospheric water vapor distribution is thus essential in predicting the severity and life cycle of heavy rain. This paper presents a systematic study on the application of tomographic solutions to investigate water vapor variations during heavy precipitation events. Using global positioning system (GPS) observations, the wet refractivity field was constructed at a temporal resolution of 30 min for three heavy precipitation events occurring in Hong Kong, China, in 2010–14. The zenith wet delay (ZWD) is shown to be a good indicator in observing the water vapor evolution in heavy rain events. The variabilities of water vapor at five altitude layers (<1000, 1000–2000, 2000–3000, 3000–5000, and >5000 m) were examined. It revealed that water vapor above 3000 m has larger fluctuation than that under 3000 m, though it accounts for only 10%–25% of the total amount of water vapor. The relative humidity fields derived from tomographic results revealed moisture variation, accumulation, saturation, and condensation during the heavy rain events. The water vapor variabilities observed by tomography have been validated using European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and radiosonde data. The results positively demonstrated the potential of using water vapor tomographic technique for detecting and monitoring the evolution of heavy rain events.

scholarly journals EXTRACTION OF SCATTERED SMALL-SCALE LANDSLIDES DISTRIBUTION BY OBJECT-BASED CLASSIFICATION USING OPTICAL HIGH-RESOLUTION SATELLITE IMAGES

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1213-1218
Author(s):  
H. Hashiba ◽  
M. Sonobe
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Image Interpretation ◽  
Heavy Rain ◽  
Wide Area ◽  
Small Scale ◽  
Superpixel Segmentation ◽  
Long Duration ◽  
High Resolution Satellite Images ◽  
Landslide Event

Abstract. Continuous heavy rain for a long duration over mountainous terrain, where the elevation is relatively low and the topography is complex leads to multiple small-scale landslides over a wide area. Detailed investigations of small-scale landslides have been effectively carried out using optical high-resolution satellite images with spatial resolution of about 2 m or less. In this study, the sediment-related disaster caused by heavy rain in northern Kyushu, Japan that occurred in July 2017 was selected as a typical example of small-scale landslide. For this landslide event, the applicability of the conventional superpixel segmentation for landslide separation was examined. The applicability of the representative SLIC and SLICO methods in the superpixel segmentation method by image interpretation in the case of a large number of small-scale landslides in a wide area was assessed. These results suggest that in the case of such a disaster, segmentation by the SLICO method will be better. In addition, the set value of the area size for the area division was systematically examined from the distribution tendency of the average NDVI value in the divided area. It was shown that the landslide region can be extracted with relatively high accuracy by the land cover classification process by the NN method by using the appropriate region size examined by the SLICO method.

scholarly journals Small-scale (flash) flood early warning in the light of operational requirements: opportunities and limits with regard to user demands, driving data, and hydrologic modeling techniques

2016 ◽  
Vol 373 ◽  
pp. 201-208 ◽  
Author(s):  
Andy Philipp ◽  
Florian Kerl ◽  
Uwe Büttner ◽  
Christine Metzkes ◽  
Thomas Singer ◽  
...  
Keyword(s):  
Early Warning ◽  
Hydrological Modeling ◽  
Flash Flood ◽  
Input Parameter ◽  
Heavy Rain ◽  
Small Scale ◽  
Pilot Studies ◽  
Potential Benefits ◽  
Rain Events ◽  
Small Catchments

Abstract. In recent years, the Free State of Saxony (Eastern Germany) was repeatedly hit by both extensive riverine flooding, as well as flash flood events, emerging foremost from convective heavy rainfall. Especially after a couple of small-scale, yet disastrous events in 2010, preconditions, drivers, and methods for deriving flash flood related early warning products are investigated. This is to clarify the feasibility and the limits of envisaged early warning procedures for small catchments, hit by flashy heavy rain events. Early warning about potentially flash flood prone situations (i.e., with a suitable lead time with regard to required reaction-time needs of the stakeholders involved in flood risk management) needs to take into account not only hydrological, but also meteorological, as well as communication issues. Therefore, we propose a threefold methodology to identify potential benefits and limitations in a real-world warning/reaction context. First, the user demands (with respect to desired/required warning products, preparation times, etc.) are investigated. Second, focusing on small catchments of some hundred square kilometers, two quantitative precipitation forecasts are verified. Third, considering the user needs, as well as the input parameter uncertainty (i.e., foremost emerging from an uncertain QPF), a feasible, yet robust hydrological modeling approach is proposed on the basis of pilot studies, employing deterministic, data-driven, and simple scoring methods.

Transport equations for the normalized nth-order moments of velocity derivatives in grid turbulence

2021 ◽  
Vol 930 ◽  
Author(s):  
S.L. Tang ◽  
R.A. Antonia ◽  
L. Djenidi
Keyword(s):  
Large Scale ◽  
Transverse Velocity ◽  
Longitudinal Velocity ◽  
Transport Equations ◽  
Small Scale ◽  
Grid Turbulence ◽  
Mean Velocity ◽  
Local Isotropy ◽  
Advection Term ◽  
The Mean

Transport equations for the normalized moments of the longitudinal velocity derivative ${F_{n + 1}}$ (here, $n$ is $1, 2, 3\ldots$ ) are derived from the Navier–Stokes (N–S) equations for shearless grid turbulence. The effect of the (large-scale) streamwise advection of ${F_{n + 1}}$ by the mean velocity on the normalized moments of the velocity derivatives can be expressed as $C_1 {F_{n + 1}}/Re_\lambda$ , where $C_1$ is a constant and $Re_\lambda$ is the Taylor microscale Reynolds number. Transport equations for the normalized odd moments of the transverse velocity derivatives ${F_{y,n + 1}}$ (here, $n$ is 2, 4, 6), which should be zero if local isotropy is satisfied, are also derived and discussed in sheared and shearless grid turbulence. The effect of the (large-scale) streamwise advection term on the normalized moments of the velocity derivatives can also be expressed in the form $C_2 {F_{y,n + 1}}/Re_\lambda$ , where $C_2$ is a constant. Finally, the contribution of the mean shear in the transport equation for ${F_{n + 1}}$ can be modelled as $15 B/Re_\lambda$ , where $B$ ( $=S^*{S_{s,n + 1}}$ ) is the product of the non-dimensional shear parameter $S^*$ and the normalized mixed longitudinal-transverse velocity derivatives ${{S_{s,n + 1}}}$ ; if local isotropy is satisfied, $S_{s,n + 1}$ should be zero. These results indicate that if ${F_{n + 1}}$ , ${F_{y,n + 1}}$ and $B$ do not increase as rapidly as $Re_\lambda$ , then the effect of the large-scale structures on small-scale turbulence will disappear when $Re_\lambda$ becomes sufficiently large.

scholarly journals Industrial Production and Investment in Pakistan

1964 ◽  
Vol 4 (3) ◽  
pp. 462-490 ◽  
Author(s):  
G. F. Papanek
Keyword(s):  
United Nations ◽  
Industrial Production ◽  
Industrial Development ◽  
Large Scale ◽  
Value Added ◽  
Industrial Sector ◽  
Policy Formulation ◽  
High Rate ◽  
Small Scale ◽  
Industrial Growth

Development in Pakistan so far has been largely sustained by a rapidly growing industrial sector. From 1953 to 1960, the index for manufacturing has grown more rapidly in Pakistan than in any other country for which United-Nations statistics are published, except Japan. Admittedly, the reliability of such comparisons is limited and the high rate of Pakistan's industrial growth is partly a function of the low initial level of industrial development—if you start at zero, any increase means an infinite rate. But the United-Nations index starts in the middle 1950's when Pakistan already had a respectable industrial sector and the statistics are sufficiently reliable so one can say with some confidence ' that Pakistan had a rate of industrial growth matched by few countries in the recent past. A reasonably accurate measure of the growth in industrial production and investment in Pakistan is, therefore, of particular importance to economic analysis, policy formulation, or planning. The dynamism of the industrial sector has been due to what is called " large scale industry ". No reasonably reliable information exists on value added in "small scale industry", but various official , and unofficial guesses on its growth rate have ranged from a decline to a 3.5- per-cent annual increase. There would be near-universal agreement that "large scale industry" has grown much more rapidly than "small scale". The Survey, discussed later in this paper, confirms this conclusion. From 1947 to 1959, the value added by firms with assets of less than one million rupees increased only five-fold, while that added by larger firms increased more than fifteen times.

scholarly journals NWP and Radar Extrapolation: Comparisons and Explanation of Errors

2020 ◽  
Vol 148 (12) ◽  
pp. 4783-4798
Author(s):  
James Wilson ◽  
Dan Megenhardt ◽  
James Pinto
Keyword(s):  
Data Assimilation ◽  
Large Scale ◽  
Rainfall Intensity ◽  
Large Fraction ◽  
Precipitation Amount ◽  
Local Scale ◽  
Colorado Front Range ◽  
Small Scale ◽  
Front Range ◽  
Rain Events

AbstractThis paper examines nowcasts of precipitation from the High-Resolution Rapid Refresh (HRRRv2) model from the summer of 2017 along the Colorado Front Range. It was found that model nowcasts (2 h or less) of precipitation amount were less skillful than extrapolation of the KFTG WSR-88-D data at a spatial scale of 120 km. It was also found that local-scale (mesoscale) influences on rainfall intensity and amount have a much greater impact on rainfall intensity than large-scale (synoptic) influences. Thus, large-scale trends are not useful for modifying extrapolation nowcasts on the local scale. Errors in the HRRR nowcasts are attributed to an inability of the model and data assimilation to resolve convergence along outflow boundaries and other terrain-influenced mesogamma-scale flows that contribute to storm formation and evolution. While the HRRRv2 1-h nowcasts were strongly correlated with observed precipitation events, the nowcast precipitation amounts were in error by more than a factor of 2 about 50% of the time, with half of the cases being overestimates and half being underestimates. A large fraction of the HRRRv2 overestimates were associated with stratiform rain events. It is speculated that this was a result of misinterpretation of the radar bright band as more intense precipitation aloft by the data assimilation scheme. A large fraction of the HRRRv2 underestimates occurred when the data assimilation and model were unable to fully resolve the low-level convergence along small-scale, narrow boundaries that led to new storm initiation and/or storm growth.

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