Convective forecast. Meteorological dictionary glossary of meteorological terms
To forecast thunderstorms, showers and other phenomena associated with the development of powerful cumulus and cumulonimbus clouds, N.V. Lebedeva proposed using morning sounding data to calculate convection parameters, which are used to determine the possibility of the occurrence of certain convective phenomena. These parameters include:
1) Total dew point temperature deficit at levels of 850,700 and 500 hPa (ΣD,°C). This parameter indirectly takes into account the influence of entrainment and characterizes the possibility of cloud formation in the 850-500 hPa layer. If ΣD>25°С, then further calculations are not made, since with very dry air in the lower half of the troposphere, convection does not lead to the formation of cumulonimbus clouds. If ΣD≤25°С, then the second parameter is calculated.
2) Dew point temperature deficit near the ground or at the upper boundary of the surface inversion at the time of maximum development of convection (Do, °C). If Do>20°C, then the condensation level is located at an altitude of more than 2.5 km, therefore, precipitation will not reach the earth's surface, and further calculations are not made. At such a height of the level of condensation, and therefore the height of the lower boundary of the clouds, a drop of rain on its way to the ground will have time to completely evaporate. If the condensation level is located below 2 km and favorable conditions exist for the occurrence of convection, then in this case all other parameters should be determined.
3) Thickness of the convective-unstable layer (CIL) – (ΔНкнс, hPa). Each particle of this layer will participate in convection to high altitudes. The greater the thickness of the KNS, the greater the likelihood of the formation of cumulonimbus clouds, the greater the likelihood of developing thunderstorm activity (the thickness of the KNS is determined by the aerological diagram).
4) Condensation level (Ncond., km). The level of condensation indicates the average position of the height of the base of the cumulonimbus cloud. The level of condensation is also determined using the aerological diagram.
5) Convection level (Nconv., km). The level of convection allows us to determine the average position of the tops of cumulonimbus clouds. It is quite obvious that the higher this level, the more powerful the “thunderstorm” clouds should be.
6) Air temperature at the convection level (Tconv, °C). It has been established that the lower this temperature, the more likely showers and thunderstorms are.
7) The average deviation of the temperature on the state curve (T") from the temperature on the stratification curve (T). This deviation is designated ΔT and is determined by the formula:
Where: T" and T are the temperatures on the state curve and the stratification curve, respectively, at levels that are multiples of 100 hPa, n is the number of whole layers 100 hPa thick, starting from the condensation level to the convection level.
It is quite obvious that the greater ΔT, the greater the degree of instability of the air, and therefore, the more intense convection can develop.
8) Average vertical power of convective clouds (ΔНк.о, km). This value is defined as the difference between the heights of the convection level and the condensation level. The larger this value, the more likely the occurrence of convective phenomena and the greater their intensity.
Based on the results of calculating the indicated eight convection parameters in accordance with Table. 1 N.V. Lebedeva suggests assessing the possibility of the occurrence of convective phenomena.
The validity of the forecast for the presence of thunderstorms using the N.V. method Lebedeva is 80%, and their absence is 89%.
∑D(850-500),°C | (Tmax-Tdmax),°C | ΔΗ kns, hPa | Nkond, km | Nkonv, km | Tconv,°C | ΔT°C | ΔH,km | Convective phenomena |
---|---|---|---|---|---|---|---|---|
>25 | >20 | - | - | - | - | - | - | Convection is not expected to develop |
≤25 | ≤16 | >10 | ≈1.5 | ≥6 | <-22.5 | >4 | ≈4.5 | Light showers with a chance of thunder or dry thunderstorms |
≤20 | ≤14 | >20 | ≈1.5 | >5 | -22.5<Т<-10 | ≥3 | >3.5 | Light showers without thunderstorms |
≤20 | ≤14 | >30 | ≈1.5 | ≥8 | <-22.5 | ≥3 | >6.5 | Shower rain, thunderstorms in places |
≤16 | ≈10 | >60-100 | 1.5>H>1.0 | >8 | <-22.5 | ≥3 | ≥7.5 | Heavy rain and thunderstorms |
≈16 | ≈10 | - | 1.5>H>1.0 | >8 | <-22.5 | >3 | ≥7.5 | hail |
FEDERAL SERVICE 1№ HYDROMETEOROLOGY AND ENVIRONMENTAL MONITORING
HYDROMCTE<»РОЛОГНЧВЛШ НАУЧНО-ИССЛЕДОВАТЕЛЬСКИЙ ЦЕНТР Р Г 6 Ой РОССИЙСКОЙ ФЕДЕРАЦИИ
SHEVELENA OLGA VASILIEVNA
STRUCTURE ASHHM "KGNIH FRONT I! 11 about gida kosyaktishsh PHENOMENA OVER the south of eastern EUROPE
Siatsialyyust 11.00.09 - Mk "gzhfoyaogin, climatology,
ASH"ORKSH"A!
NN geSh"KsSHIA uchchioy IPMI"NI knndiditi (>g kik muk
The work was carried out at the Hydrometeorological Research Center of the Russian Federation
Scientific supervisor: Doctor of Physical and Mathematical Sciences, Professor Shanina I.11.
Official opponents: Doctor Fia"-mat. Sciences, Prof. Belov N.11 Candidate of Geographical Sciences Velinsky O. K
Leading organization High Mountain Geophysical Institute, Nalchik
Defense will take place No./0 1993 per hour at the meeting of the Specialized Council K. 024. Vol. 02 Hydrometeorological Research Center at the address: 123376, Moscow, B. Predtechensky per., no. 9-13, Roshydrometcenter.
The dissertation can be found in the library of the Rosgkdrometsentr.
Scientific secretary
Specialized Council ^S&lL^ A-I. Strashnaya
0Б111ДЯ ХЛЛЛК.1 ERIST SHA WORK
RELEVANCE OF THE TOPIC. Convective activity, widespread in the atmosphere, is one of the most important weather-forming factors. It is associated with such important and sometimes dangerous weather phenomena as showers, thunderstorms, squalls, tornadoes, etc. At the same time, forecasting convective activity is often “not free from subjectivity”, since convective foci are meaoscale phenomena and are thus located far away within the range of scales described by currently operationally used numerical models.
However, as a rule, active convegada (leading to the development of showers, thunderstorms, hail, squalls) develops within larger-scale zones characterized by certain properties of the air mass (temperature, humidity, vertical movements, stratification). The emergence of such zones favorable for convective activity is successfully described within the framework of numerical predictions of pressure, temperature, humidity and wind. To forecast the characterized zones, called zones of active convection, an automated method for forecasting zones of active convection has been developed in the Department of Aviation Meteorology of the Hydrometeorological Center of the Russian Federation. However, despite the fairly high justification of this methodology for the European territory of the country as a whole (the overall justification for the warm season of 1992 was 6?. 6%), for the south of the forecast territory the justification of this method is ok
is significantly lower than average. This indicates the need to improve the methodology for forecasting zones of active convection for these areas. On the other hand, there is no doubt that the use of large-scale characteristics of thermobaric fields in addition to the particle method, predominantly used at present, cannot but give a positive effect in predicting AC zones.
At the same time, using large-scale field characteristics to predict mesoscale phenomena, one cannot refuse to study meaoscale phenomena as such, both theoretically and in terms of attracting new field data, especially when it comes to ordered convection, which is currently poorly understood compared to purely thermal instability.
The listed aspects of the problem of studying and forecasting convective activity determine the relevance of this work.
THE PURPOSE OF THE WORK is to study the conditions for the emergence of ordered convection from the standpoint of the theory of hydrodynamic instability, to analyze the synoptic conditions for the formation of ordered convective structures, and, further, to identify and use the most informative large-scale characteristics as predictors to improve the currently used method for automatically predicting zones of active convection.
RESEARCH TASKS, based on the purpose of the work, are formulated as follows:
1) Study of the conditions for the development of ordered convective structures (cosmic active bands) in order to clarify some aspects of the issue of the predominant orientation of band structures in the ranges of gravitational-inertial waves and shorter wavelengths.
new convective and gravitational modes.
2) Detailed analysis of the conditions for the formation of observed quasi-periodic structures in cloudiness and precipitation fields in specific cases.
3) General physical and statistical analysis of the conditions for the development of both ordered and disordered convection over the south of the European part of the CIS in order to identify large-scale characteristics that can serve as predictors in the forecast of AO.
4) Establishing diagnostic connections and developing an improved methodology for forecasting active convection in the southern regions of the European country.
RESEARCH METHOD. The work used methods of the theory of hydrodynamic instability (DLI ynniunin conditions for the development of ordered convective structures and their predominant orientation in the ranges of gravitational-inertial waves and shorter wavelength modes); synoptic method and elements of the climatological method (to identify general patterns of circulation conditions of the study area); methods of mesometeorological analysis, in particular, isentropic analysis (to study the internal structure of baroclinic AOs and the conditions for the formation of ordered convective structures in them); computational physical-statistical and synontic-statistical methods (to search for predictive relationships between large-scale characteristics of thermobaric fields and the possibility of "! ioziikio-" 1
of active convection).
MATERIALS USED To complete the assigned tasks, the following materials were used:
Synoptic (ground) maps (1U85-1992)
Pressure topography maps 850 - 300 g1!a (19ВБ-1992)
Consolidated radar K£1r"Sh (1988-1991)
Maps of semi-daily precipitation amounts (1988-1991)
Satellite MK and TV images, including images from the VO radar (1986-1992)
Object analysis archive data on magnetic tapes (1985-1992)
Output data of the semi-feral ten-level forecast model, operationally used in the Hydrometeorological Center of the Russian Federation (1989-1992)
Data from the experimental pluviographic test site UKRNIGII (1985-1988)
The calculations were carried out at the Hydrometeorological Center of the Russian Federation on KS-1060, partly on a personal computer.
SCIENTIFIC NOVELTY ¡YULU"SHSHU. IN THE DISSERTATION OF RESULTS.
1. For the first time, an analysis of the conditions for the growth of mesoscale wills non-parallel to the front was carried out (in a special case of fulfillment of conditions (1)) and conclusions were drawn about the ratio of the growth rates of the decree! ny waves and symmetrically unstable waves, and the latter are approx. were more rapidly growing, and therefore prevailing conditions. This conclusion is consistent with observations.
2. For the first time, a detailed analysis of three was carried out; dimensional structure of the air masses in which the hollow (precipitation) developed and it is shown that such structures, parallel to the wind, wind shear (hence, the average temperatures of the layer) developed in two typical situations, characterized by the presence of shallow layers of the possible development of convection and significant baroclinicity and non-stationarity.
3. For the first time, a physical and statistical analysis of the relationships between the parameters of static instability and parameters that rasterize “grid” scale processes, on the one hand, and the presence or absence of active convection, on the other, was carried out
based on the output data of the operational scheme of objective analysis.
4. A new improved version of the methodology for calculating and constructing a map of active convection zones based on output forecast data has been developed.
These main new conclusions are presented for defense.
APPROBATION OF THE WORK. The main results of the work were presented at seminars of the Department of Aviation Meteorology, a report on the topic of the dissertation was included in the program of the 3rd All-Union Conference on Aviation Meteorology (Suadal, 1990); The main results obtained during the work and related to the development of a prognostic methodology were included in the reports of the OAM HMC on topics 1. 2v.1 (1991) and VII. Zh. 1(1992). Some results were published in articles:
1. Borisova V. V., Shakina N. II, Sheveleva O. V., Isanthropic analysis of the conditions that formed "1 precipitation bands detected by side-scan satellite radar. Proceedings of the State Medical Center of the Russian Federation, 1992, issue 324.
2. Skrintunova E. E., Shakina N. P., Sheveleva O. V. Improved methodology for forecasting active convection zones over the south of Eastern Europe, deposited manuscript.
PRACTICAL VALUE OF THE WORK. The developed improved method for automated forecasting of active convection zones based on the results of proprietary and operational tests provides a significant increase in the success of forecasting AC zones. The methodology has been prepared for consideration at the Center for Medical Design. Implementation is expected in RCPC Moscow and GAMC Vnukovo.
STRUCTURE AND SCOPE OF WORK. The dissertation consists of an introduction, four chapters, a conclusion and a list of references and includes 149 pages of printed text, including 18 tables and 35 figures. The list of references includes 108 titles.
The introduction substantiates the relevance of the dissertation topic, formulates the purpose and objectives of the research, and briefly outlines the main content of the work.
The first chapter provides a description of the problem, a discussion of the fundamental principles of predicting convection using the particle method and methods for predicting conditions favorable for convective activity over large areas.
Most existing methods for forecasting convection are based on the following scheme:
1) forecast of the state of the atmosphere that you add up? to the moment of interest; vertical profiles of temperature and humidity are practically forecast for 6, 12 or 18 hours;
2) the degree of stability of this state is assessed - the possibility of developing convection from the ground or from upper levels. Depending on the instability energy reserves, convection of varying intensity may develop. To predict the use of shsn threshold values of instability energy or any associated quantities, starting from which appears! significant probability of developing one or another form of convection
There are many developments aimed at objectifying the forecast of convective activity. As a rule, the author! either they follow the path of simple objectification of known calculation methods (for example, variants of the particle method), or, modify!
known calculation methods create special algorithms. Currently, Roshydrometsengr has a methodology for calculating zones of active convection, developed in ZAM, which uses N.V. Lebedeva’s method for forecasting intramass!junction and prognostic discriminant functions proposed by [\E Reshetov for forecasting convection in baroclinic zones as a basis. The technique uses the output data of the operational numerical forecast scheme used in the Russian Hydrometeorological Center (multilevel adiabatic hemispherical model of L. V. Berkovich).
In addition to the effect of thermal instability, which causes disordered convection, it is necessary to take into account the fact that in the real atmosphere the horizon scales of the layers at which convection develops are quite large (10 km), 1 at such scales layers with wind shear turn out to be hot - are thermally heterogeneous in temperature, which creates additional reserves of potential energy that can serve as a source for the development of movements that level out temperature contrasts, “which movements caused by baroclinic instability may develop with indifferent and even weakly stable stratification; with unstable stratification, the actions of these melismas lead to the formation of more intense convective phenomena. An additional impulse to the development of convective movements is often given by a forced rise of air, the intensity of which is determined by dynamic factors.
Often convection is most intense on the roofs. Since fronts are baroclinic zones, the conditions for the development of convection here are influenced by hydrodynamic instability. The vertical movements it causes serve as an additional forcing factor for convection or suppress it. Hydrodynamic, in particular, inertial instability
is of great interest from the point of view of improving the forecast of convective phenomena. The most studied special case of this type of instability - symmetric instability - leads to the development of stripes of vertical movements parallel to the front. Conditions created in saturated air are especially favorable for their development, i.e. inside cloud layers.
IN THE SECOND CHAPTER, the analysis and solution of the linear problem “on inertial instability in frontal zones is carried out. This problem is posed with the aim of identifying atmospheric conditions in which convective structures in the form of rolls non-parallel to the front develop predominantly. From observations it is clear that such structures are quite rare ; as a rule, cloud banks are elongated along the wind shear, which corresponds to a direction parallel to the front. We consider not the general case of the problem, but a special case of the characteristic relationship between the parameters of the waves and the main flow.
k7" - pG, (1)
where whale are the wave numbers along the x and z axis, respectively, G is the Coriolis parameter.
This case is still more general than the previously studied case of so-called symmetric perturbations. Like the simplest cases 1=0 or V=0, it lends itself to an analytical solution (unlike the general case).
G*- 1b + «[ ik(co+ki) +
+ (kA+1g)(o^kiANg(kg+) +1 g"1 (th"- O (2)
where сО is the complex frequency, k, 1, m are the wave numbers along the k, y, z axes, respectively. I*" - Brent-Väisälä frequency, n -<*■
A study was carried out of the conditions for the existence of neutral-stable and growing (and conjugate decaying) values for different wavelengths, different stratification and layer thickness. Next, the influence of flow parameters on the wave growth index, which is found as one of the roots of the cubic equation (dispersion relation), is investigated.
It was found that structures not parallel to the front are unstable and can grow in a wide range of conditions, but their growth is slower than that of stripes parallel to the front, which is why the latter should dominate. Waves of the type under study, in contrast to symmetrically unstable waves, form ordered strip structures, not necessarily oriented parallel to the Front; they form an arbitrary angle with a direction parallel to the front. Analysis of dispersion relations showed that waves of arbitrary orientation can exist in a flow with a shear and at the same time be both neutrally stable and unstable in a wide range of conditions, including at a sufficiently high degree of stability. However, their growth is slower than that of the stripes parallel to the front, which is why the latter should dominate. The source of energy for growing disturbances that are not parallel to the front is the kinetic energy of the air flow with vertical wind shear; thus, the source is the same as for baroclinic-unstable disturbances. The waves under consideration are mesoscale (wavelength 30 - 300 km) and differ from baro-wedge-unstable waves of synoptic scale primarily
its non-hydrostagicity.
Thus, the few cases of development of convective bands not parallel to the front known from observations cannot be explained by instability of the gravitational-inertial type. Unfortunately, there are no detailed data in the literature on the parameters of nonparallel hollows and fronts near which they were observed.
Li 1>f;< условий развития упорядоченных конвективных струк-ур (независим« от их ориентации) приводит к общему выводу.что существование таких структур определяется параметрами более крупномасштабных движений (т.е. движений с характерными размерами, по крайней мере на порядок превышающими размеры конвективных структур). К таким параметрам относится прежде всего сдвиг ветра(связанный с горизонтальным градиентом температуры) и степень статической устойчивости (см. ур-ние (2)). Кроме того, поскольку для развития неустойчивости благоприятны насыщенные влагой слои, к определяющим параметрам следует отнести те, которые характеризуют условия упорядоченного подъема воздуха(давление, лапласиан давления) и степень его увлажнения.
CHAPTER THREE analyzes the observed three-dimensional structure of air flow under conditions where ordered systems of stripes of precipitation were recorded on the Earth's surface. Observations made with the help of satellite side-observation radar (BO radar) indicate the presence of “traces” of the passage of ordered rainfall systems. The “wavelength” of parallel strips of moistened soil in the 9 cases used for analysis varies from 10 to 35 km; Thus, we are talking about a substantially “subgrid” scale of the phenomenon. For a more detailed analysis of the thermobaric field in the atmosphere,
sphere, at a time closest to the observations, isentropic analysis was applied according to a technique previously developed at OAM and repeatedly used for the purposes of mesoscale analysis. Within the framework of this technique, profiles of temperature and wind components are reconstructed using cubic splines, after which the heights of isentropic surfaces and vertical ones are calculated. movement of particles on these surfaces. The isentropic analysis method makes it possible to determine with great accuracy the position of isentropic surfaces and the value of the potential Ertel vortex, which are material invariants of hydrostatic flow; it also allows one to calculate vertical movements on each isosurface independently, which eliminates the accumulation of errors with height. As a result of the analysis of the state of the atmosphere at the time of development of stripe structures in the fields of cloudiness and precipitation, 2 classes of characteristic conditions were identified.
The first class includes situations associated with the warm sector of the cyclone: the phenomenon is formed in the air of the warm sector near the baroclinic zone of the warm front under conditions of its erosion, the development of convection is limited along the vertical settling
lack of air. The first class of situations is associated with the rear of the cyclone: instability develops in cold air under a stable (frontal) layer. However, in a number of moments the situations of both classes turn out to be quite similar. In the cases studied, over those areas where stripes of non-uniform soil moisture were observed, the structure of the atmosphere included layers of probable development of wave movements with stratification approaching moisture-indifferent. The layers are characterized by limited vertical thickness (up to 4 km). The wind in these cases, as a rule, changes little with altitude in direction, while its speed usually increases, and for cases of class 1
its typical value is 3-5m/s near the ground and 15-E0m/s in the tropopause area; for the second class 5-10 and 25-30 m/s, respectively. The wind direction is parallel to the observed stripes. The phenomenon under study is repeatedly associated with wave formation at the front or with a section in which the front changes sign with angicyclonic curvature of the isohypsum. In other cases (class 2), the phenomenon develops in the absence of a pronounced frontal zone, but in the presence of increased baroclinicity in the middle troposphere and at values of the Frontogenetic function corresponding to the frontogenetic function. That is, at the moment of development of the phenomenon, non-stationarity of the baroclinic zone necessarily takes place. At the same time, the formation of strip structures associated, for example, with well-developed, rapidly moving atmospheric fronts, was not recorded. which would be clearly visible throughout the entire thickness of the atmosphere and would retain the sign of the frontogenetic function at successive moments in time. Perhaps it is the transformation of the baroclinic zone that plays a certain role, creating specific conditions for the formation of quasi-periodic precipitation fields.
In addition, in the third chapter, a comparative analysis of the fields of vertical motions calculated by the method of entropic analysis was carried out (and the values of the vertical motions were obtained, which were well consistent in time and space), with the fields of vertical motions calculated by the generally accepted method. In general, the fields of vertical movements assigned by both methods provide summary pictures of the distribution of vertical movements. However, in the case of calculations using the isentropic analysis method, the results turn out to be less smooth and more detailed, which is an advantage of this method.
CHAPTER FOUR is devoted to physical and statistical analysis
conditions for the development of active convection over the study area and improvement of the method of objective forecasting of active convection zones. The climatic characteristics of precipitation and convective phenomena over the territory under consideration are presented. The connections between various stratification parameters and synoptic processes are analyzed, a system of potential predictors is selected, and a discriminant analysis of the sample is performed. The following predictors were considered the most informative:
1) O, TK (Mahalanobiea distance 1681.21)
2) aH&o>O, NK (Mahalanobis distance 1643.01) (3)
3) dT, B, TK (Mauchlanobis distance 1638.37)
4) 0, ¡^ , NK (Mahalanobis distance 1628.67), Here dH^ is the Laplacian of the geopotential of the isobaric surface 850 hPa. This value in itself is quite informative as a separation criterion. Thus, when using 4 Н^ as the only predictor at a threshold value of its Yuda, the success of the forecast turned out to be as follows: overall accuracy of 74. OX, accuracy of the forecast for the presence of active convection 62. O7., accuracy of the forecast of its absence 79. 3 predictability of the presence of active convection 65.17., warning of its absence - 83.57..
O - total dew point deficit on isobaric surfaces 850, 700, BOOgSH" In relation to our materials, the criterion for separation by this value is its value 34*, in contrast to the value 2B", used in the method of N. E. Lebedeva, which, apparently, explained by the climatic features of the study area
dT“ - the difference between the temperature of the dry and wet thermometers on the surface is 850 hPa, i.e., a value characterizing the proximity of air vapor to saturated water. It was found that
Table 1 Characteristics of separation efficiency using combinations of the three and four most informative parameters
PREDICTORS
justifying the suit
oh|n£i|ots |AK | AK
preuire-adeshjust
criteria
Rubinstein
discriiiiinant
functions (I, - for the past and other cash. (C, - for forecasting the absence of a phenomenon.
b,-0. 058^+0. 430+0. 897TX--9. 425
1^=0. 031d|^+0. 6310+0. 766Zh--10.064
b, -0.115dts+0.2380+0. 004NK--4.749
b^-0.095aH^O. 3250+0. 005NK--7.902
b, -0.57dT -O, 3160+0.93TK-9.16 |_x -0.888^T +0. 4070+0. 783GK--10.823
b -0.1450+0. OZbTs^+0.002NK--3.376
B-O. 2260+0.044^+0.003NK--7.706
and -0.088L^+4T +0.3490+0.8791"
10. 455 G-O. 067^^5+1. 217LT +0.4320+ +0.745-K-11.586
I_I-■ ■ ■ *
sensing the air vapor's proximity to saturation. It was found that the threshold value should be considered to be dT ~ 3.5*. This value turns out to be very informative when calculating using data from an object analysis archive (overall accuracy 777., Bagrov criterion 0.60, Obukhov O. criterion 54), but when calculating using numerical forecast data, the success of the forecast using &T sharply decreases, which is explained by the insufficient accuracy of the parameter forecast humidity in the current operational scheme in comparison with the forecast of pressure characteristics
leniya. Considering this, for use in improved
leniya. Taking this into account, a discriminant function is proposed for use in the improved methodology, which includes a pressure characteristic.
Нloc¿ geopotential of an isobaric surface of 1000 rila, characterizing the value of surface pressure. Being used as the only predictor, this greatest, with the separation criterion of 117dams, provides the following success of the forecast: overall accuracy of the forecast 69.7Z, accuracy of the forecast for the presence of the phenomenon 51.1%, accuracy of the forecast for its absence 94.3%, predicted for the presence of the phenomenon 96.4%, prevention of its absence is 45.2%.
For each of the combinations (.) we obtained on a dependent sample the values of justification and warning, the Bagrov and Obukho criteria, as well as the Rubinstein criterion, which takes into account the disparity of losses from false alarms and false alarms.
of these phenomena for the threshold probability P=0. b (Table 1). Next, discriminant functions were found for each combination of the three parameters.
In addition, calculations were made for partial samples obtained from the total sample by dividing by the values of individual parameters. Generally; splitting into partial samples did not lead to a significant improvement in the results.
Based on these results, an improved methodology for automated forecasting of active convection zones was formulated. The first of the dc-criminant functions (3) is used. The technique includes the following steps
1) Calculation of the Laplacians of the geopotential on the surface 850g11&.
2) “Calculation of convection parameters: altitude and condensation temperature.
3) Calculation of humidity characteristics: its total deficit on surfaces of 850, 700, 500 hPa, as well as temperature differences
dry and wet bulb bulbs near the ground.
4) Calculation of discriminant function values
1 ^.115-^0.240 b 0.004"NK -4.749 (4)
5) Calculation of the probability of occurrence of a phenomenon.
$) Based on the probability values, a map of active convection is automatically constructed. The zone is outlined by an isoline but with probability values of 25% (in accordance with the separation criteria specified above). In addition, those areas of the zone where the occurrence of active convection can be considered almost unconditional (probability value 607 or more) are especially highlighted.
The methodology was tested in a quasi-online mode at the Laboratory for Testing New Forecast Methods in accordance with
Rice. 1. Subregion of the forecast territory for which an improved methodology for forecasting zones of active convection was developed.
topic 1.2v.1 based on the material of the warm season of 1992.
Although this methodology was developed only for part of the European territory of the country (Fig. 1), but in the process of developing topic 1.2c. 1, during the tests an attempt was made to generalize it for the entire ETC, which to a certain extent justified itself. The forecast success characteristics for the territory for which the methodology was directly developed turn out to be higher than for the entire territory as a whole, and, even more so, higher than for its northern and central parts: And why are they quite high even for the north of the ETC. Characteristics of forecast success are presented in Table 2. So, providing justification for everyone
Table 2. Indicators of forecast success using the proposed method
1 |Success indicators of the city - Dp throughout Europe - 1 For not >:ch correct. For the southern
| forecast, X territory of the country parts (Fig. 4.6) parts
| 1 (natural repetition)
capacity 48.5 53.2 43.6
|general processing capacity 70. 8 66. 7 78. 1
|justifiability of pro-
prediction of the presence of the phenomenon 76. 7 76. 2 84. 0
|justifiability of pro-
gnosis of absence of phenomena. 67.5 60.9 75.2
|andreducibility
| phenomena B7. g 54.5 61.4
warning from-
absence of the phenomenon 83.7 80.6 90.9
Bagrov criterion 0.411 0.345 0.54
1 Obukhov criterion 0. 497. 0.35 0. 521
of the territory as a whole is 70.8%, the accuracy of the forecast for the presence of the phenomenon is 76.77., the accuracy of the forecast for the absence of the phenomenon is 67.5%, the predicted phenomenon is 57.27%, the prediction of its absence is 87. for the southern part of the territory these indicators are higher by 4-8. Bagrov and Obukhov's criteria are 0.411 and 0.497 in the first case and 0.54 and 0.621 in the second. For comparison, we present success rates obtained on the same material when predicting using a previously accepted method. They are: overall justification 67. 5X, Table. 3. Indicators of forecast success using the proposed method in the case of transition to a probabilistic form of forecast
1 | Predicted probability of occurrence of AK 1 2 1 ........ 1 (Actual frequency of occurrence for a given city- | 1 ciD 1 1 |
| 90-100 ■ 1 1 | 95.2 |
| 80-90 | 97.8 |
| 70-80 | 96.6 |
| 60-70 | 90.7 |
| 50-60 | 82.3 |
| 40-50 | 76.5 |
| 30-40 I p.o " |
| 20-30 | 51.2 |
| 10-20 I 48.7 |
| 0-10 1 | 28.5 | | |
accuracy of the forecast of the presence of a phenomenon 60.6%, justification of the forecast of the absence of a phenomenon 76.6X, prevented phenomenon 76.8%, prevention of its absence 60.3%, ¿ng-row criterion 0.365, Obukhov criterion O. 372. It is obvious that the use of a new, improved The methods provide significant benefits even for the north of the territory, not to mention its southern part.
In table Table 3 shows the characteristics of the probabilistic form of the forecast. The values of the actual repeatability of the phenomenon turn out to be somewhat “shifted” towards larger values, which is explained by the difference in the sample sizes of the absence and presence of the phenomenon. The real threshold value turns out to be a probability of occurrence of the phenomenon of about 25%, which confirms the correctness of the choice of separation criterion for an alternative form of forecast.
MAIN RESULTS AND CONCLUSIONS
1. By analytically solving the equation for inertial-unstable waves, a class of waves whose wavelengths satisfy the condition ku""tG is selected from the spectrum of its solutions, their phase velocities, growth rates and other characteristics under certain conditions are determined. The purpose of this study is was an assessment of the possibility of the development of wave structures located at an arbitrary angle to the line of the atmospheric front. It was discovered that, although such waves will exist in a wide range of conditions, being both neutral-stable and unstable, yet their growth rates, other things being equal, turn out to be less, but the speed increased
This is greater than that of previously studied symmetrically unstable waves that form stripe structures oriented parallel to the front. From here we conclude that the latter should prevail in real conditions, which is confirmed by field data.
2. The synoptic conditions for the formation of meat-rich strip structures of heterogeneous soil moisture were studied and classified. The purpose of this study is to find out to what extent the three-dimensional structure of the flow and its large-scale characteristics are related to the possibility of the formation of mesoscale inhomogeneities in the fields of meteorological elements. It has been revealed that there are 2 classes of conditions for their formation, the first of which is associated with the warm sector of the cyclone and includes the presence of an eroding atmospheric front (usually warm) with characteristic wind speeds of 3-5 m/s near Hemli and 15-20 m/s in the tropopause area; the convection development layer has a small vertical thickness (1.5-3 km) and is limited by downward vertical movements. The second class is associated with the rear of the cyclone and is characterized by an exacerbation of the baroclinic zone with wind speeds of 5-10 and 25-30 m/s, respectively; the development of convection in cold air is limited by a layer of increased stability located at an altitude of 3-6 km. The structure of the fields of meteorological elements was restored by the method of isentropic analysis
3. In the process of research (item 2), it was found that when calculating vertical movements using the method of isentropic analysis, which excludes the accumulation of errors with height, it is possible to obtain fields of vertical movements that are well consistent in time and space. There is general agreement with the fields of vertical movements calculated from
operational model adopted by the Roshydrrmetcenter, however,
isentropic analysis gives a less blurred and smoothed picture, which is an advantage.
4. A statistical study was carried out on the possibility of using various large-scale (“grid”) characteristics of air flow as predictors. The study was carried out for the territory of the south of the European part of the country on the material of 3 warm seasons (1988-1990). We selected those quantities (Laplacians of the geopotential of various isobaric surfaces, horizontal temperature gradient, etc.) that, even with the existing database, have proven themselves to be significant predictors in the forecast of active convection. Other quantities, such as frontogenesis, advection angle, etc., were rejected for the reason that when calculating them using finite-difference approximations of the derivatives, excessive smoothing occurs and, consequently, a loss of predictive value of the calculated quantities (although, of course, the corresponding hydrodynamic quantities are significant for the formation of mesoscale cloud and precipitation fields).
5. Using the method of discriminant analysis on the specified material, connections were established between selected quantities, which make it possible to predict the occurrence of active convection based on data in the corners of the regional grid (on the material of object analysis, i.e. within the framework of the RR concept). The following combinations of predictors turned out to be optimal :
a) Laplacian of the geopotential of the isobaric surface 8П0гПн, total moisture deficit on surfaces 500, 700,850 rila, temperature (or height) of the condensation level.
b) the difference between the air temperature and the temperature of the wetted
thermometer on an isobaric surface 850 hPa, total humidity deficit on isobaric surfaces 500, 700, 850 hPa, condensation level temperature.
b) total humidity deficit, geopotential of the isobaric surface 1000 hPa, height of the condensation level.
How much less successful the forecast was obtained for some other combinations of parameters, including the Laplacian of the geopotential on the surface of ZOOgPa, the horizontal temperature gradient on the surface of 850 hPa.
ü. A method for calculating zones of active convection has been developed, included as a local one in the recommendations for introducing an automated forecast based on the output data of the numerical operational hemispherical mode w. The technique has passed the author's and operational tests, it is expected to be implemented in F 11.311 ^> well and GAMC Vnukovo.
Use: in all areas of human activity where it is important to know in advance about the occurrence of situations that are accompanied by significant material damage. Essence: the values of atmospheric pressure, temperature and air humidity are measured at various points in the atmosphere. From them, the values of the maximum vertical convective air velocity and the vertical velocity of large-scale ordered movement at the level of 850 hPa are determined. Additionally, the amplitude of the daily variation of the vertical velocity of large-scale ordered air movement at the level of 850 hPa is measured. A forecast of spontaneous convective phenomena is given when a given condition is met. Technical result: increasing the reliability of forecasting any of the known types of spontaneous convective hydrometeorological phenomena or their combination.
The invention relates to meteorology, and more precisely to methods for predicting such dangerous and spontaneous convective hydrometeorological phenomena (showers, hail, squalls) in specific areas of the globe, which are developed based on data on the values of meteorological parameters in the previous day and can be most effectively used in all areas of human activity where it is important to know in advance about the possibility of such situations occurring, which are accompanied by significant material damage. There is a known method for forecasting spontaneous convective hydrometeorological phenomena, which consists in measuring at various points in the atmosphere the values of atmospheric pressure, temperature and air humidity, which determine the value of the maximum vertical convective air speed (Guide to short-term weather forecasts. Part 1. L.: Gidrometeoizdat, 1986, pp. 444-448). The disadvantage of this known method is that it is limited in application only for forecasting one of the dangerous convective phenomena, namely hail. Of the known, the closest in technical essence and achieved result is a method of forecasting spontaneous convective hydrometeorological phenomena, which consists in measuring at various points in the atmosphere the values of atmospheric pressure, temperature and air humidity, from which the value of the maximum vertical convective air speed and the vertical speed of large-scale ordered movement on the air are determined. level 850 hPa (Guide to the diagnosis and forecast of dangerous and especially dangerous precipitation, hail and squalls based on data from weather radars and artificial Earth satellites. / N.I. Glushkova, V.F. Lapcheva. M.: Roshydromet, 1996, p. 112 -113). The disadvantage of this known method is that it is limited in application only for forecasting one type of dangerous convective phenomena, namely showers. As a result, the reliability of forecasting other dangerous convective phenomena (hail, squalls), which in some cases are observed simultaneously with showers, is not high. The technical result of the invention is to increase the reliability of forecasting any of the known types of spontaneous convective hydrometeorological phenomena or their combination. This technical result is achieved by the fact that in the method of forecasting spontaneous convective hydrometeorological phenomena, including measuring at various points in the atmosphere the values of atmospheric pressure, temperature and air humidity, determining from them the value of the maximum vertical convective air speed and the vertical speed of large-scale ordered movement at the level of 850 hPa, according to the invention, the amplitude of the daily variation of the vertical velocity of large-scale ordered air movement at the level of 850 hPa is additionally measured, and the forecast of spontaneous convective phenomena is given if the condition c 1 W m +c 2 850 +c 3 850 +c 4 0 is met, where: c 1 , c 2, c 3, c 4 - empirical coefficients, the values of which for the warm period of the year are, for example: c 1 = 2 (s/m), c 2 = -0.52 (12 h/hPa), c 3 = -0 .16 (12 h/hPA), c 4 = -90; W m - the value of the maximum vertical convective speed (m/s); 850 - the value of the vertical speed of large-scale ordered air movement at the level of 850 hPa (hPa/12 h); 850 - the value of the amplitude of the daily variation of the vertical velocity of large-scale ordered air movement at the level of 850 hPa (hPa/12 h). The proposed technical solution complies with the conditions of patentability “Novelty”, “Inventive step” and “Industrial applicability”, since the declared set of features: measurement of atmospheric pressure, temperature and air humidity at various points in the atmosphere, determination of the maximum vertical convective speed from them air and vertical velocity of large-scale ordered movement at the level of 850 hPa, additional measurement of the amplitude of the daily variation of the vertical velocity of large-scale ordered movement of air at the level of 850 hPa and forecasting of spontaneous convective phenomena when the condition c 1 W m +c 2 850 +c 3 850 +c 4 is met 0, where: c 1, c 2, c 3, c 4 are empirical coefficients, the values of which for the warm period of the year are, for example: c 1 = 2 (s/m), c 2 = -0.52 (12 h/m hPA), c 3 = -0.16 (12 h/hPA), c 4 = -90; W m - the value of the maximum vertical convective speed (m/s); 850 - the value of the vertical speed of large-scale ordered air movement at the level of 850 hPa (hPa/12 h); 850 - the value of the amplitude of the daily variation of the vertical velocity of large-scale ordered air movement at the level of 850 hPa (hPa/12 h) ensures the achievement of a non-obvious result; increasing the reliability of forecasting any of the known types of spontaneous convective hydrometeorological phenomena or their combination. The method proposed in the present invention for forecasting spontaneous convective hydrometeorological phenomena can be used in all areas of human activity where it is important to know in advance about the possibility of such situations occurring, which are accompanied by significant material damage.
Formula of invention
A method for forecasting spontaneous convective hydrometeorological phenomena in the warm half of the year, which consists in measuring at various points in the atmosphere the values of atmospheric pressure, temperature and air humidity, from which the value of the maximum vertical convective air speed and the vertical speed of large-scale ordered movement at the level of 850 hPa is determined, characterized in that additionally, the amplitude of the daily variation of the vertical velocity of large-scale ordered air movement at the level of 850 hPa is measured, and a forecast of spontaneous convective phenomena is given if the condition c 1 W m +c 2 850 +c 3 850 +c 4 0 is met, where c 1 , c 2 , c 3 , s 4 - empirical coefficients, the values of which are s 1 = 2 (s/m), s 2 = -0.52 (12 h/hPa), s 3 = -0.16 (12 h/hPa), s 4 = -90; W m - value of the maximum vertical convective speed, (m/s); 850 - the value of the vertical speed of large-scale ordered air movement at the level of 850 hPa (hPa/12 h);
850 - the value of the amplitude of the daily variation of the vertical velocity of large-scale ordered air movement at the level of 850 hPa (hPa/12 h).
Similar patents:
The invention relates to meteorology and is intended for use in the system of atmospheric protection measures for the rapid identification of sources of air pollution (AP) with the current regulatory-unauthorized level of emissions of harmful substances (HS)
Chief developer – Alexander Sprygin ( [email protected]).
With the assistance and support of Alexander Conrad and Alexander Terekhin ( [email protected]).
GrADS software was used to compile the maps.
Forecast from +3 to +72 hours (3 days).
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Laplacian of reduced atmospheric pressure (Sea Level Pressure, SLP)
Laplacian SLP - Laplace operator for the reduced pressure field. In the context of our study, the most significant thing is that positive values of the Laplacian determine the convergence of flows and contribute to the emergence of large-scale upward movements in the lower troposphere, favorable for the formation of convective phenomena.
Specific humidity
Specific humidity - mass of water vapor in grams per kilogram of humidified air [g/kg], that is, the ratio of the masses of water vapor and humidified air. The higher the specific air humidity, the faster the rising particle is saturated, the lower the lower limit of convective cloudiness, and the faster it develops when warming up.
Temperature advection at the isobaric level of 850 hPa
Positive heat advection at this level contributes to the generation and development of powerful convective storms.
Moisture convergence
The convergence of moist air flows contributes to the intensification of the formation of cumulonimbus clouds and the formation of a mesoscale organization of convective storms (along lines or near centers of positive convergence values).
Wind speed and direction at different levels
Wind at different levels - wind shift and intensification with height can significantly enhance convection even under initially unfavorable conditions (weak instability) and are included in the equations of a number of convective indicesDew point at a height of 2 m from the surface
Dew point - the temperature at which moisture in the air begins to condense. The higher the dew point, the faster the rising particle is saturated, the lower the lower limit of convective cloudiness, and the faster it develops when warming up.
CAPE
z f, z n
Tν parcel
Тν bnv
g
).
- CAPE below 0
- CAPE from 0 to 1000
- CAPE from 1000 to 2500
- CAPE from 2500 to 3500
- CAPE above 3500
Lifted index
Buoyancy index (Li)
air humidity
LI ≥ 4
LI 2…3
LI 1…2
LI 0...1
LI 0...-1
LI -1…-2
LI -2…-3
LI -3…-4
LI -4…-5
LI -5…-6
LI< -6
- Surface-based LI –
- Best LI –
Lifted index
Buoyancy index (Li) is another indicator of instability. This index is calculated using the formula:
Li = T500mb(amb.) - T500mb(frequent),
that is, the temperature value of the air layer at the 500 hPa level (about 5.5 km) minus the temperature value of the air mass raised as a result of convection to the 500 hPa level and invading this air layer. For example, the temperature of the air layer at 500 hPa is -5°. The temperature of the air mass, which due to convection rose to the level of 500 hPa and invaded this air layer, is +3°. Subtract: -5-(+3)=-8. LI = -8. And there is nothing complicated here. If the convection is so violent that the rising air masses simply do not have time to cool more than the air surrounding them, then strongly negative (-3 or lower) LI values arise, which serves as “food” for strong thunderstorms. Negative values indicate instability in the atmosphere and indicate the presence of strong updrafts that cause thunderstorms and heavy precipitation. On the contrary, in the absence of convection, the layer of air at the level of 500 hPa is homogeneous, and no atmospheric mini-cataclysms occur. This indicator is often used in conjunction with CAPE to forecast thunderstorms. However, it is necessary to take into account air humidity, because Convection alone is not enough to create a thunderstorm.
LI ≥ 4 – absolute stability, thunderstorm probability 0%;
LI 2…3– isolated Cu cong. possible, probability of thunderstorm 0 – 19%;
LI 1…2– weak convection (Cu cong.), probability of thunderstorms 19 – 32%;
LI 0...1– light showers possible (isolated Cb), probability of thunderstorm 32 – 45%;
LI 0...-1– slight thunderstorms are possible, probability 45 – 58%;
LI -1…-2– weak thunderstorms almost everywhere, squalls are possible, the probability of thunderstorms is 58 – 71%;
LI -2…-3– the probability of thunderstorms is high (71 – 84%), they can be moderate;
LI -3…-4– severe thunderstorms are expected (probability 84 – 100%), squalls, hail is possible;
LI -4…-5– severe thunderstorms everywhere, squalls, hail, deep convection;
LI -5…-6– very strong thunderstorms, formation of supercells, large hail, possible tornadoes;
LI< -6 – “explosive” convection, tornadoes, floods, destructive squalls, the degree of threat is extremely high;
There are 2 types of buoyancy index:
- Surface-based LI – this index is calculated hourly, assuming that the particle rises from the surface. To calculate it, the value of ground humidity and temperature is used. This method is valid for a well-mixed, near-dry adiabatic boundary layer where surface characteristics are similar to those observed in the 50 – 100 mb layer.
- Best LI – lowest Li value calculated from the ground surface to the 850 mb layer.
Convective Available Potential Energy (CAPE)
CAPE – available convective potential energy is the amount of buoyancy energy available to accelerate an air particle vertically or the amount of work done by an air particle as it rises. Used to forecast thunderstorm activity and convective phenomena. CAPE is the positive area on the diagram between the moist adiabatic line and the air condition curve from the level of free convection to the level of temperature equalization. CAPE is measured in Joules per kg of air and is calculated using the formula:
z f, z n
- heights, respectively, of free convection and the level of temperature equalization (neutral buoyancy);
Tν parcel
- virtual temperature of a certain air particle;
Тν bnv
- virtual ambient temperature;
g
- free fall acceleration (9.81 m/s 2).
When a particle is unstable (its temperature is higher than its surroundings), it will continue to rise until it reaches a stable layer (although momentum, gravity, and other forces can cause the particle to continue moving). There are various types of CAPE: Downdraft CAPE (DCAPE) - shows potential rainfall, etc.
- CAPE below 0– steady state (thunderstorms are impossible);
- CAPE from 0 to 1000– weak instability (thunderstorms are possible);
- CAPE from 1000 to 2500– moderate instability (strong thunderstorms and showers);
- CAPE from 2500 to 3500– severe instability (very strong thunderstorms, hail, squalls);
- CAPE above 3500– explosive convection (supercells, tornadoes, etc.).
Low Level Shear Index
This index shows the difference between the wind speed at the surface and at an altitude of 700 mb. The magnitude of wind shear in the lower layer (0 - 3 km) is an important characteristic for predicting derechos and bow echoes.
If the shift is less 11 m/s– weak shift, the occurrence of a “bow echo” is unlikely;
If the shift is from 12 to 19 m/s– moderate shear (“bow echo” probably together with destructive winds);
If the shift is greater 20 m/s– strong shear (100% occurrence of “bow echo” along with destructive winds persisting at significant heights from the surface).
Deep Layer Shear (DLS)
Defined as the magnitude of the vector difference between the wind speed vector at an altitude of 450 mb and the wind vector at the surface of the earth. As an alternative, the hodograph length in the layer from 0 to 6 km can be used. The shear in this layer is used to determine the supercell potential. However, this is not a very good indicator for determining the rotational potential in the lower layer.
- DLS: 35 – 39 kt– low potential for supercell development;
- DLS: > 40 kt– the development of a supercell is most likely.
* Experimental index of powerful convective storms SCS (Severe Convective Storm)
A comprehensive, testable index developed from a combination of convection indices that perform best in forecasting severe storms. The index takes into account the most important conditions for the formation of powerful organized convection, such as: instability, wind shear, heat advection, vorticity, specific temperature and humidity characteristics at various levels.
Formula**: SCS = 0.083*scpsfc+0.667*ui+0.5*mcsi+0.0025*sweat+0.025*ti,
Where:
scpsfc – SCP index, using sfcCAPE,
ui – Peskov index,
mcsi – MCS index,
sweat – SWEAT index,
ti – Thompson index.
Interpretation of SCS index values:
- <1 : the development of powerful convective storms (MCS) is not expected, weak thunderstorms are possible in places;
- 1…2 : MCS are unlikely (probability approximately 10-20%). Moderate thunderstorms with isolated adverse events (AEs) are possible;
- 2...3 : slight chance of MCS (20-40%), conditions for adverse convective phenomena and moderate thunderstorms;
- 3...4 : average probability of MCS (40-60%), possible complexes of adverse events (CAE), sometimes dangerous events (HE);
- 4...5 : high probability of developing MCS (60 – 90%) and OC;
- >5 : very high probability (>90%) of the development of dominant stable MCS (within a radius of approximately 100-150 km from the maximum index values), a complex of particularly destructive hazardous phenomena.
Direction of movement of convective storms
The map can be used to estimate the movement of thunderstorm cells and mesoscale convective systems. Only flows for SCS index values >1 are shown.
The calculation is based on the direction of flows at the levels of 500 and 700 hPa.
K.O.index
KO-Index is designed to determine the convective instability of the air layer. It ultimately represents the average vertical gradient of equivalent potential (pseudopotential) temperature and is calculated using the following formula:
KO-Index = 0.5 [ Te(700hPa) + Te(500hPa) ] - 0.5 [ Te(1000hPa) + Te(850hPa) ],
Where Te – the value of the equivalent potential temperature on a certain surface.
- KO-Index > 6: the probability of a thunderstorm is zero;
- KO-Index from 2 to 6 : possible development of weak thunderstorms;
- KO-Index< 2 : Significant chance of thunderstorms developing.
Ti - Thompson index
Another index used to assess the strength of a thunderstorm. When testing this indicator in the United States, a good relationship was obtained between severe weather conditions and Ti >40. Calculated using the formula:
Ti = Ki-Li
, Where
Ki - K-index, Li - Lifted index.
Ti< 25
- No thunderstorms.
TI 25 - 34- Thunderstorms are possible.
TI 35 - 39- Thunderstorms, sometimes strong.
TI ≥ 40- Severe thunderstorms.
Peskov index
According to this method, a thunderstorm is possible if the parameter u takes positive values. It is calculated using the following formula:
where (T * -T) 600 - deviation of the state curve from the stratification curve at the level of 600 hPa;
(T - T d ) 500 - dew point deficit at 500 hPa;
The Laplacian of surface pressure, which characterizes the surface convergence of flows, is calculated using 8 points located 250 km from the central point;
|ΔV|300/700 - difference module #1080; wind vectors at the levels of 700 and 300 hPa.
The u criterion may vary slightly depending on local conditions. For the forecast for the aerodrome and surrounding areas, the criterion is used u > 0. In another version of the method, a thunderstorm is not given if the deviation of the state curve from the stratification curve at the level of 500 hPa is negative, and if the deviation is positive, if the sum of the dew point deficits at the levels of 700 and 500 hPa is equal to 25-30 °C (more accurately, this value is found by special schedules). The state curve is constructed from the maximum temperature at the earth's surface; the prognostic stratification curve is constructed in the usual way.
SWEAT - Severe Weather ThrEAT index
SWEAT
- The instability index developed by the US Air Force. SWEAT is a comprehensive criterion for the diagnosis and forecast of dangerous and natural weather phenomena associated with convective clouds. SWEAT includes lower-tropospheric humidity, degree of instability, mid- and lower-tropospheric wind speed, and warm air advection (temperature deviation between 850 and 500 hPa levels). Therefore, this indicator is an attempt to combine the kinematic and thermodynamic characteristics of the atmosphere into one index:
SWEAT = 12⋅Td850 + 20⋅(TT- 49) + 3.888⋅F850 + 1.944⋅F500 + (125⋅), Where
Td850 - dew point temperature at 850 hPa (in degrees Celsius),
TT - Total Totals index,
F850 - wind speed at 850 hPa (in m/s),
F500 - wind speed at 500 hPa (in m/s),
D500 and D850 are the wind direction on the corresponding surfaces (in degrees).
The last term in the formula will be zero if any of the following conditions are not met:
- D850 in the range from 130 to 250 degrees;
- D500 in the range from 210 to 310 degrees;
- The difference in wind direction (D500 - D850) is positive;
- F850 and F500 wind speed ≥ 7 m/s.
SWEAT< 250
- there are no conditions for the occurrence of severe thunderstorms;
SWEAT 250-350- there are conditions for severe thunderstorms, hail and squalls;
SWEAT 350-500- there are conditions for very strong thunderstorms, large hail, strong squalls, tornadoes;
SWEAT ≥ 500- conditions for very strong thunderstorms, large hail, strong squalls, strong tornadoes.
MCS Index (Mesoscale Convective System Index)
MCS Index designed for forecasting Mesoscale convective systems. Using this indicator, areas are identified where favorable conditions exist for the development of the ISS and their maintenance over the next 6 hours, provided that there is nothing obstructing convective movements. This index is calculated as follows:
where each term in the equation (Li index, shear in the 0-3 km layer and temperature advection at the 700 hPa level) is normalized. It should be noted that this parameter makes sense if there are conditions for the development of convection (for example, at Li< 0). Для расчёта индекса могут использоваться как фактические, так и прогностические данные необходимых параметров.
Development of supercell cumulonimbus clouds (supercells) is expected at SCP>
Supercell composite parameter (SCP)
A comprehensive indicator for forecasting the most important conditions for the development of supercell cumulonimbus clouds (the most stable and powerful form of Cb clouds, which are associated with many dangerous convective phenomena). The calculation uses normalized values of instability energy (2 options for the CAPE parameter are used - sbCAPE or MU CAPE), wind shear (in the 0-6 km layer) and vorticity parameter in the 0-3 km layer:
SCP (sfcCAPE/MU CAPE) =(sb CAPE(MU CAPE)/1000)*(DLS/20)*(SRH_3km/50)
The development of supercell cumulonimbus clouds (supercells) is expected at SCP>0, the probability of their generation is proportional to the index values.Probability of significant (large) hail, %
A parameter used by the Storm Predictor Center (USA) to predict the likelihood of large (diameter >5 cm) hail.
Calculated using the formula:
SHIP = [(MUCAPE j/kg) * (Mixing Ratio of MU PARCEL g/kg) * (700-500mb LAPSE RATE c/km) * (-500mb TEMP C) * (0-6km Shear m/s) ] / 44,000,000
Where:
Mixing Ratio of MU PARCEL - mixture ratio in an unstable layer,
700-500mb LAPSE RATE - vertical temperature gradient in the layer of 700-500 hPa,
500mb TEMP C - temperature at 500 hPa,
0-6km Shear - wind shear in the 0-6 km layer.
* Probability of thunderstorms, %
Tested experimental index of overall thunderstorm probability based on moisture instability and convergence indices:
** TSP = ((0.05*KI -0.003*sbCAPE-LI-0.6*KO+0.18*MConv)/6)*100
Where:
LI - Lifted Index,
KO - KO index,
MConv - surface moisture convergence.
** The formula is subject to change based on testing results.
* Probability of powerful convective storms, %
An indicator of the probability of generation of mesoscale convective systems and convective complexes, supercell Cb and other powerful convective storms, based on the SCS index:
** SCSP = (SCS/6)*100
** The formula is subject to change based on testing results.
Maximum hail diameter (cm)
A tested index based on the calculation of the maximum speed of upward movements in unstable air.
Calculated using the formula:
Where:
sbCAPE - instability energy,
Significant tornado parameter
An indicator of the probability of tornadoes occurring.
Calculated using the formula:
STP=(sbCAPE/1500)*((2000-PLCL)/1000)*(SRH_1km/150)*(DLS/20)
Where:
sbCAPE - instability energy,
PLCL - Pressure at condensation level,
SRH_1km - vorticity in the 0-1 km layer,
DLS - wind shear in the 0-6 km layer.
Modified tested type of index (according to preliminary estimates, the values are more effective for the ETR):
STPmod=1.5*(sbCAPE/1500)*((2000-PLCL)/1000)*(SRH_1km/150)*(DLS/20)
The development of tornadoes can be expected with positive index values.
Direction and speed of movement of convective storms
Maximum wind gusts, m/s
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