MIME-Version: 1.0
Content-Type: multipart/related; boundary="----=_NextPart_01C6AF65.9C0C5750"
Ten dokument to jednoplikowa strona sieci Web nazywana również plikiem archiwum sieci Web. Jeżeli widzisz ten komunikat, przeglądarka lub edytor nie obsługują plików archiwum sieci Web. Pobierz przeglądarkę obsługującą archiwa sieci Web, na przykład przeglądarkę Microsoft Internet Explorer.
------=_NextPart_01C6AF65.9C0C5750
Content-Location: file:///C:/B448B0D1/Prognozowanie1.htm
Content-Transfer-Encoding: quoted-printable
Content-Type: text/html; charset="us-ascii"
=
PROGNOZOWANIE POGODY
&n=
bsp;
&n=
bsp;
Poniżej
zamieszczam nieco przydatnych, aczkolwiek orientacyjnych wskazówek, =
jak
w przybliżeniu oszacować lokalne zmiany pogody na najbliższe
godziny. Pamiętajmy, że sprawdzalność takiej prognozy
zależy od ilości i wagi przesłanek, którymi się
kierujemy, a zjawiska, które obserwujemy, mogą być
mylące!
I. Prognozowanie na podstawie ciśnienia atmosferycznego
1. Interpretacja spadku ciśni=
enia:
·
Systematycz=
ny
spadek-> nadchodzi niż (front ciepły), opady, silny wiatr=
·
Wzrost
szybkości spadku ciśnienia (spadek o 2- 4 hPa w ciągu 3h)-&g=
t;
nadchodzi przednia część niżu, wzrost prędkoś=
ci
wiatru
·
Zmniejszanie
szybkości spadku ciśnienia-> zmniejszenie prędkości
wiatru, poprawa pogody
=
=
2. Interpretacja wzrostu
ciśnienia:
·
Systematycz=
ny
wzrost po pogodzie deszczowej z silnym wiatrem-> wyż, poprawa pogod=
y
·
Wzrost
szybkości wzrostu ciśnienia (wzrost o >4 hPa w ciągu 3h)-=
>
wzrost prędkości wiatru, możliwy szkwał, sztorm
·
Zmniejszenie
szybkości wzrostu ciśnienia-> poprawa pogody=
·
Wzrost podc=
zas
mgły-> zanik mgły (gdy utrzymuje się niskie
ciśnienie-> mgła się utrzyma)
=
3. Regularne wahania dobowe ciśnienia-> utrzymanie się dobrej pogody
=
II. Prognozowanie=
na
podstawie wiatru
=
1.
Ogólne wiadomości dotyczące wiatru:
·
Przed
południem wiatr ma tendencję do skręcania zgodnie z ruchem
wskazówek zegara, po południu w odwrotnym kierunku=
span>
·
Wiatr w
układach barycznych: w niżu najsilniejszy w centrum, w wyżu
najsilniejszy na obwodzie
·
Prędko=
ść
wiatru wzrasta bez zmiany kierunku-> nadchodzi niż
·
Prędko=
ść
wiatru maleje bez zmiany kierunku-> odchodzi niż<=
/p>
·
Prędko=
ść
wiatru maleje po przejściu frontu ciepłego i wzrasta po
przejściu frontu chłodnego
·
Za każ=
dym
frontem wiatr skręca o 900 w prawo
=
2. Zjawiska zapowiadające dobrą pogod&=
#281;:
·
Wzrost
prędkości wiatru przy długotrwałym deszczu=
span>
·
Nagły =
spadek
prędkości przy silnym deszczu
·
Wiatr przed
deszczem
·
Stopniowy w=
zrost
prędkości wiatru po wschodzie słońca (do południa)=
i
spadek wieczorem
·
Nocą s=
uche,
ciepłe powiewy na wzgórzach
=
3. Zjawiska zapowiadające złą pogodę:=
·
Nie
zmieniający się wiatr zachodni w czasie niepogody
·
Silny wiatr=
z NW
i W
·
Nagła =
zmiana
kierunku wiatru po długim czasie
·
Szybki wzro=
st
prędkości wiatru wieczorem lub rano
·
Wiatr
zmieniający kierunek po burzy
·
Kierunek wi=
atru
odwrotny do kierunku przesuwania się chmur
·
Nagłe
zmniejszenie prędkości wiatru w południe=
p>
·
Całkow=
ity
bezruch powietrza
·
Podmuchy
ciepłego, wilgotnego powietrza
·
Wiatr a
możliwe opady:
-
z W: często poprzedza nadchodzący deszcz
-
z SW-> deszcz w godzinach wczesnoporannych
-
z S-> deszcz za 2-3 dni
=
4. Oznaki zbliżania się wiatru:
·
Bardzo szyb=
ki
spadek ciśnienia
·
Porywisty w=
iatr
wiejący z przerwami
·
Wzrost si=
322;y
wiatru po opadach
·
Ró=
380;ne
chmury przemieszczające się w różnych kierunkach=
·
Faliste,
kłębiące się chmury o wyraźnych konturach
·
Ciemnoniebi=
eskie
niebo
·
Silnie
świecące gwiazdy
·
Czerwone
zabarwienie księżyca
·
Krwistoczer=
wony
wschód słońca zza warstwy chmur (jeśli słoń=
ce
krwistoczerwono wschodzi i zachodzi, to następny dzień będzie
wietrzny, ale bez opadów)
=
5. O czym świadczy kie=
runek
wiatru:
·
Przy
wzroście ciśnienia:

·
Przy spadku
ciśnienia:

III.
Prognozowanie na podstawie temperatury
=
1. Zjawiska zapowiadające dobrą pogodę:
·
Szybki spad=
ek
temperatury przy niepogodzie- przeszedł front chłodny<=
/span>
·
Spadek
temperatury wieczorem (duża różnica temperatur między
dniem a nocą)
·
W lesie cie=
plej
niż na otwartym terenie
·
W nocy w do=
linach
chłodniej niż na wzniesieniach
·
Wzrost
temperatury przy mgle-> zanik mgły
=
2. Zjawiska zapowiadające złą pogodę:=
·
Wzrost
temperatury wieczorem i nocą
·
W lesie
chłodniej niż na otwartym terenie
·
Ocieplenie =
po
deszczu
·
Wzrost
temperatury i wilgotności powietrza, spadek ciśnienia<=
/span>
·
Znaczny spa=
dek
temperatury przy pogodzie wietrznej i deszczowej-> front chłodny
·
Spadek
temperatury latem przy niepogodzie-> front ciepły=
·
Spadek
temperatury przy mgle-> zgęstnienie mgły
=
3. Zimowe zapowiedzi mrozu:
·
Wygwież=
;dżone
niebo
·
Wiatr ze ws=
chodu,
północnego wschodu lub północy
·
Ż&oacu=
te;łtobrązowa
zorza
·
Szadź =
na
drzewach
·
Burza jest
oznaką przejścia chłodnego frontu
·
Opady sypki=
ego,
drobnego śniegu
·
Dźwi=
281;czenie
drutów telefonicznych-> mróz i śnieg
=
4. Zapowiedzi opadów
śniegu:
·
Zamglenie
powietrza
·
Mglisty
okrąg wokół słońca i księżyca
·
Wiatr z
północnego zachodu
=
5. Zjawiska zapowiadające odwilż:
·
Zamglone ni=
ebo,
mgły nad wodą
·
Wiatr
południowy lub zachodni
·
Śnieg =
pada
wielkimi płatami, zwłaszcza przy wzrastającym ciśnieniu=
·
Gołole=
dź
następująca po opadach śniegu i śniegu ziarnistego=
=
6. Prognozowanie temperatury na podstawie:
·
Adwekcji
termicznej- wiatr z kierunku, w którym aktualnie jest cieplej->
wzrost temperatury (i odwrotnie)
·
Zachmurzeni=
a:
Ø W dzień: pogodnie- szybkie nagrzewanie;
pochmurno- wolne nagrzewanie
Ø W nocy: pogodnie- szybkie ochładzanie; poch=
murno-
wolne ochładzanie
·
Wiatru: noc=
ą
wypromieniowanie ciepła przy ziemi
Ø Bezwietrznie-> podtrzymanie tego procesu i sz=
ybkie
wychładzanie
Ø Wiatr miesza ciepłe i zimne powietrze-
przeciwdziała ochłodzeniu
·
Pokrywy
śnieżnej: w dzień trudno pochłania promienie, nocą
łatwo oddaje ciepło-> szybkie ochładzanie
IV.
Prognozowanie na podstawie zachmurzenia
=
1. Zjawiska zapowiadają=
;ce
dobrą pogodę:
·
Wieczorem na
zachodzie pojawienie się pasma czystego nieba
·
Rozproszone
chmury pierzaste rano (ze wschodu) lub zanikające wieczorem
(różowe)
·
Smugi
kondensacyjne pozostawione przez samolot rozpadają się=
·
Latem: chmu=
ry
kłębiaste pojawiające się ok. godz. 11 przed
południem, rosną i wieczorem zanikają
·
Zimą:
mgła poranna przekształcająca się w chmury warstwowe,
które w południe zanikają
=
2. Zjawiska zapowiadające złą pogodę:=
·
Pojawianie
się chmur kłębiastych rano, rozwój pionowy i ł=
261;czenie
się w większe kompleksy, zwłaszcza wieczorem
·
Pojedyncze
strzępki chmur wznoszące się znad lasu
·
W nocy szyb=
ko
poruszające się chmury kłębiaste, zwłaszcza z kier=
unku
zachodniego
·
Zachó=
;d
słońca za ławicą chmur o lekko purpurowym zabarwieniu
·
Zjawisko ha=
lo
·
Utrzymywanie
się i rozrastanie smug kondensacyjnych
·
Pojawienie
się rano Ac, które następnie się łączą=
·
Ruch chmur
przeciwny do kierunku wiatru
·
Ró=
380;ne
chmury poruszające się w różnych kierunkach
=
V. Prognozowanie =
na
podstawie wyglądu nieba
Niebo
ma tym jaśniejszy kolor, im bardziej powietrze jest suche i zapylone.
Czyste, wilgotne powietrze nadaje niebu ciemniejszą barwę. Ciemno=
niebieskie
zabarwienie nieba można obserwować głównie wiosną=
; i
jesienią.
1.
Zjawiska zapowiadające dobrą pogodę:=
p>
·
Umiarkowanie
jasny lub połyskujący błękit nieba
·
Szare zabar=
wienie
porannego nieba
·
Krót=
kotrwały
świt lub zmierzch
·
Sło=
24;ce
wschodzi spoza czystego i jasnego widnokręgu, a niebo po przeciwnej
stronie ma barwę różową z wyraźną linia
widnokręgu
·
Zorza poran=
na lub
wieczorna w kolorach: żółtym, złocistym,
jasnoróżowym, zielonkawym, pozorna deformacja słońca-=
>
2-3 dni słonecznej pogody
·
Pojawienie
się na ok. 10 sekund przed zniknięciem tarczy słonecznej za
horyzontem zielonkawoniebieskich promieni-> upalny w=
yż
przez co najmniej 5-6 dni
·
Polepszenie
widoczności po opadach
·
Zła
widoczność wieczorem
·
Bł=
1;kitnozielone
niebo nocą
·
Gwiazdy o
zielonym zabarwieniu, brak migotania-> latem upalnie, zimą mroź=
;no
i sucho
·
Księ=
380;yc
świecący silnym, srebrzystym światłem=
·
Pozorna
deformacja księżyca
·
Halo w du=
380;ym
oddaleniu od księżyca-> dobra pogoda przez 3 dni
·
Poranne
słońce w postaci małego złocistego krążka
=
2. Zjawiska zapowiadające złą pogodę:=
·
Ciemnoniebi=
eska
barwa nieba przy dobrej widoczności (możliwe nagłe pogorszen=
ie
się pogody), =
&nb=
sp; =
lub bardzo rozbielony
błękit
·
Długot=
rwały
świt lub zmierzch
·
Zorza poran=
na lub
wieczorna o zabarwieniu krwistoczerwonym, przechodząca w jasny odcie=
324;
·
Zadymione n=
iebo
nad wschodzącym słońcem
·
Powięk=
szone
słońce o czerwonej tarczy rano lub wieczorem
·
Dobrze wido=
czne
promienie słoneczne w wilgotnym powietrzu zapowiada deszcz, ale po
przejściu opadów nie jest oznaką pogorszenia pogody=
o:p>
·
Polepszenie
widzialności (obserwowane jest przed, ale
również po przejściu frontu, wówczas zapowiada
rozpogodzenie)
·
Ciemnograna=
towe
niebo nocą, fioletowa poświata na granicy widnokręgu- opady w
ciągu 24h
·
Migotanie
powiększonych gwiazd o zabarwieniu czerwonym i niebieskim=
span>
·
Halo
wokół księżyca
·
Pozorna
bliskość księżyca
·
Bladoż=
ółty
wschód księżyca
VI.
Prognozowanie na podstawie innych obserwacji
=
1. Zjawiska zapowiadające dobra pogodę:<=
/b>
·
Mgła
występująca wieczorem i w nocy w zagłębieniach terenu
·
Rano
ścieląca się mgła, zanikająca od góry
(zwłaszcza jesienią)
·
Mgła w=
ystępująca
po deszczu
·
Wzrost
ciśnienia podczas mgły-> zanik mgły
·
Rano obfita=
rosa
lub szron
·
Tęcza
pojawiająca się po południu
·
Dym unosz=
261;cy
się do góry
·
Morskie pta=
ki
latające daleko od brzegu
·
Fruwają=
;ce
motyle
=
2. Zjawiska
zapowiadające złą pogodę:
·
Mgła p=
oranna
szybko unosi się do góry
·
Mgła p=
oranna
w gorące dni-> burza
·
Mgła
połączona z mżawką
·
Pojawienie
się podczas pięknej pogody mgły na zachodzie widnokręgu=
·
Brak rosy i
szronu
·
Tęcza =
przed
południem
·
Dym śc=
iele
się przy ziemi
·
Szybkie
wyparowanie wody po deszczu
·
Dobra
widzialność i słyszalność
·
Morskie pta=
ki
trzymające się blisko brzegu
·
Ptaki lec=
261;ce
z otwartych przestrzeni np. do lasu
·
Wrób=
le
kąpiące się w piasku
·
Ptaki nie
śpiewają rano
·
Gryzące
komary
=
3. Interpretacja zmian wilgotności powietrza:=
·
Szybki wzro=
st
wilgotności przy wzroście temperatury i spadku ciśnienia->
opady, burza (latem)
·
Znaczny wzr=
ost
przy obniżeniu temperatury-> mgła
·
Znaczny wzr=
ost
przy spadku ciśnienia-> burza
·
Wzrost
wilgotności wieczorem-> dobra pogoda
·
Wieczorem u=
trzymanie
się wilgotności na stałym poziomie-> pogorszenie pogody
=
------=_NextPart_01C6AF65.9C0C5750
Content-Location: file:///C:/B448B0D1/Prognozowanie1_pliki/image001.gif
Content-Transfer-Encoding: base64
Content-Type: image/gif
R0lGODlhQAYFAPcAAJkAM/8zZswAM/8AM/+ZmcwzZv/M/8xmmZkzZmYAM8wzmf+ZzP9mzP+Z//9m
mcwAZv8AZv8zmf8Amf8zzP8AzP9m//8z//9QUNYAk5kAZsxmzMwzzMyZ/8xm/8wz/5kzmcwAzMwA
/5kAzJkAmcyZzJlmmWYzZmYAmZkzzGYAZpkA/5kz/5lmzDMAM2YzmWYzzGYAzJlm/zMAZmYA/2Yz
/8zM/5mZ/5mZzGZmzGZm/2ZmmTMzZjMzmTMAmTMAzDMAzDMz/zMzzABm/wAzzDNm/zNmzAAAZgAA
MwAA/wAAmQAzzAAAzDNmmQBmzJnM/2aZ/wAzZmaZzABmmTOZzACZzGbM/zOZ/wAzmQCZ/zPM/wDM
/5n//2b//wAzMwD//wDMzACZmWaZmZnMzMz//zPMzGbMzDOZmTNmZgBmZgAzMwD/zDP/zDPMmQDM
mWb/zJn/zAD/mTOZZgBmMzNmM2aZZmbMZpn/mWb/ZjOZM5nMmWb/mTP/mTPMZgDMZmbMmQCZZgCZ
MzP/ZgD/Zsz/zMz/mZn/Zpn/MwDMMzP/MwDMMzPMMzPMM2b/M2bMMwBmAAAzAACZADPMAGb/AJn/
AGbMAADMADPMADOZAJnMZmaZM5nMMzNmAGaZAJnMAMz/Zsz/M8z/AJmZAMzMAMzMMzMzAGZmAJmZ
M8zMZmZmM5mZZszMmf//zP//mf//Zv//M///AP/MAP/MZv/MM8yZM5lmAMyZAP+ZAMxmAJkzAMxm
M2YzAP+ZZv9mM/+ZM/9mAMwzAJlmMzMAAGYzM5lmZsyZmZkzM8xmZv8zM8wzM/9mZmYAAJkAAMwA
AP8AAP8zAMyZZv/MmZmZmWZmZjMzMwAAAP///wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA
AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACH/C01TT0ZGSUNFOS4wFwAA
AAttc09QTVNPRkZJQ0U5LjBCPKT1ACH/C01TT0ZGSUNFOS4wGAAAAAxjbVBQSkNtcDA3MTIAAAAD
SABzvAAsAAAAAEAGBQAACP8AVwkcSLCgwYMIEypcyLChwWoCIa6SSHGiRYgYL2rMyHEjxo8TP1Yb
SbKkyZMoU6pcybKly5cwY8qcSbOmzZs4c+rcybOnz59AgwodSrSo0aNIkypdyrSp06dQo0qdSrWq
1ZYOs2rdOrDixq8dw0Yca7GsV7FoPXIEOTIk2LdhRYa8Sreu3bt48+rdy7ev37+AAwseTLiw4cOC
uSpebLYsY8cSG8O9mLay27lg2WKGubktW5GIQ4seTbq06dOoU6tezbq169enH8t+SDbh2bGWG2fU
TXa35bSXPwtfO/nmXNjIkytfzry58+fQo0ufTn3o7OsHIyv0yvB2V9y9ef8eFu7WM2W1oFOeH37c
ZPvq8OPLn0+/vv37+PPrDxwQADs=
------=_NextPart_01C6AF65.9C0C5750
Content-Location: file:///C:/B448B0D1/Prognozowanie1_pliki/image002.png
Content-Transfer-Encoding: base64
Content-Type: image/png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==
------=_NextPart_01C6AF65.9C0C5750
Content-Location: file:///C:/B448B0D1/Prognozowanie1_pliki/image003.jpg
Content-Transfer-Encoding: base64
Content-Type: image/jpeg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------=_NextPart_01C6AF65.9C0C5750
Content-Location: file:///C:/B448B0D1/Prognozowanie1_pliki/image004.png
Content-Transfer-Encoding: base64
Content-Type: image/png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------=_NextPart_01C6AF65.9C0C5750
Content-Location: file:///C:/B448B0D1/Prognozowanie1_pliki/image005.jpg
Content-Transfer-Encoding: base64
Content-Type: image/jpeg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------=_NextPart_01C6AF65.9C0C5750
Content-Location: file:///C:/B448B0D1/Prognozowanie1_pliki/filelist.xml
Content-Transfer-Encoding: quoted-printable
Content-Type: text/xml; charset="utf-8"