{"id":49868,"date":"2022-12-16T12:13:39","date_gmt":"2022-12-16T12:13:39","guid":{"rendered":"https:\/\/dev.metos.global\/?p=49868"},"modified":"2023-06-21T08:02:37","modified_gmt":"2023-06-21T08:02:37","slug":"farm-weather-talk-002","status":"publish","type":"post","link":"https:\/\/metos.global\/ro\/farm-weather-talk-002\/","title":{"rendered":"Farm Weather Talk #002 - Prognoza meteo"},"content":{"rendered":"
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Trebuie s\u0103 discut\u0103m despre previziunile meteorologice, deoarece impactul viitor al vremii pe teren este la fel de important, dac\u0103 nu chiar mai important, ca \u0219i condi\u021biile de p\u00e2n\u0103 acum.<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Farm Weather Talk #002 - Prognoza meteo<\/h2>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\u00cen primul episod al emisiunii\u00a0Discu\u021bii despre vremea din ferm\u0103<\/strong><\/a><\/span>, am discutat\u00a0beneficiul unei sta\u021bii meteorologice de teren specifice locului sau al unui dispozitiv IoT<\/strong> \u0219i cum pot reduce \"riscurile incontrolabile\" cu care se confrunt\u0103 fermierii pe baza condi\u021biilor meteorologice de p\u00e2n\u0103 acum, dar aceasta reprezint\u0103 doar jum\u0103tate din solu\u021bia pentru probleme meteorologice. Cealalt\u0103 parte este prognoza. Da, trebuie s\u0103 discut\u0103m despre previziunile meteorologice, deoarece impactul viitor al vremii pe teren este la fel de important, dac\u0103 nu chiar mai important, ca \u0219i condi\u021biile de p\u00e2n\u0103 acum.<\/p>

\"Prognoze<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Prognozele meteo sunt adesea considerate a fi \u00een mod notoriu gre\u0219ite; ele sunt mereu sursa multor glume.<\/h3>

Apoi,\u00a0cum este posibil s\u0103 se ob\u021bin\u0103 previziuni precise, specifice fiec\u0103rui loc, la nivel de teren<\/strong>? Totul \u00eencepe cu datele sta\u021biilor meteorologice de pe teren<\/a><\/span> \u0219i actualiz\u0103ri rapide ale modelelor de prognoz\u0103. S\u0103 analiz\u0103m cum este posibil acest lucru.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Credit foto: Mark Anderson<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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Sursa: Flickr<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Prognoze meteorologice la nivel de teren specifice la fa\u021ba locului<\/h3>

\u00cen prezent, la fel ca \u00een multe alte industrii, capacitatea de a calcula seturi mari de date este din ce \u00een ce mai u\u0219oar\u0103 \u0219i mai rapid\u0103:\u00a0cloud computing \u0219i costuri ieftine ale CPU<\/strong>. Acest lucru le permite meteorologilor s\u0103 creeze prognoze orare specifice pentru fiecare zon\u0103, care se bazeaz\u0103 pe observa\u021biile meteorologice de la sta\u021bia specific\u0103 zonei pentru urm\u0103toarele c\u00e2teva zile.<\/p>

Datele de la\u00a0sta\u021bie de teren<\/a><\/span>\u00a0ajut\u0103 la ajustarea \u0219i reglarea previziunilor:\u00a0se adapteaz\u0103 la starea real\u0103 \u00eenregistrat\u0103 pe teren<\/strong>. \u00cen plus, prognoza devine inteligent\u0103 pentru teren, prin \u00eenv\u0103\u021barea condi\u021biilor locale cu ajutorul AI (inteligen\u021b\u0103 artificial\u0103) pentru a alege cea mai potrivit\u0103 prognoz\u0103 pentru fiecare loca\u021bie, situa\u021bie, vreme \u0219i anotimp, mai degrab\u0103 dec\u00e2t o abordare de ansamblu pur \u0219i simplu. Acest lucru \u00eenseamn\u0103 c\u0103 alege \"cea mai bun\u0103\" prognoz\u0103 \u0219i nu \"media\" tuturor modelelor (sau a variantelor de modele) pentru a realiza o prognoz\u0103 mai precis\u0103, specific\u0103 locului.<\/p>

\"Previziuni<\/p>

\u00a0<\/h3>

meteoblue\u00ae<\/sup>-Abordarea Pessl pentru prognoza meteo specific\u0103 unui domeniu de activitate<\/h3>

Haide\u021bi s\u0103 analiz\u0103m \u00eentreaga \u0219tiin\u021b\u0103\/tehnologie, astfel \u00eenc\u00e2t s\u0103 fie clar de ce aceast\u0103 abordare de prognoz\u0103 este mai bun\u0103 dec\u00e2t cea disponibil\u0103 \u00een mod public. \u00cen prezent, majoritatea companiilor meteorologice sau a guvernelor ofer\u0103 previziuni bazate pe loca\u021bia unui ora\u0219 sau a unei localit\u0103\u021bi, care sunt derivate dintr-o abordare gril\u0103. Unele vor folosi o gril\u0103 de 15, 10, 5 sau 1 km pentru a genera prognoza, ceea ce se nume\u0219te\u00a0reducere a dimensiunii la loca\u021bia<\/strong>.<\/p>

Ceea ce este unic la\u00a0meteoblue\u00ae<\/sup>-Abordare Pesl<\/strong>\u00a0este c\u0103 ei\u00a0combin\u0103 datele sta\u021biilor de teren cu prognoza<\/strong>. Cu alte cuvinte, sta\u021bia furnizeaz\u0103 date pentru a modifica \u0219i ajusta prognoza pe baza observa\u021biilor reale de la sol.<\/p>

\u00cen mod detaliat, se va\u00a0meteoblue Learning Multimodel (mLM)<\/strong>\u00a0este o nou\u0103 tehnic\u0103 de post-procesare a datelor de ie\u0219ire de la diferite modele numerice de prognoz\u0103 meteo, utiliz\u00e2nd m\u0103sur\u0103tori reale ale sta\u021biilor meteorologice \u0219i inteligen\u021ba artificial\u0103 (AI) pentru a alege cel mai potrivit dintre cele 17 modele pentru fiecare loca\u021bie, situa\u021bie meteorologic\u0103 \u0219i anotimp, mai degrab\u0103 dec\u00e2t o abordare de ansamblu. Acest lucru \u00eenseamn\u0103 c\u0103 alege \"cea mai bun\u0103\" prognoz\u0103 \u0219i nu \"media\" tuturor modelelor (sau a variantelor acestora) pentru a realiza o prognoz\u0103 mai precis\u0103, specific\u0103 locului.<\/p>

\u00cen esen\u021b\u0103, inteligen\u021ba artificial\u0103 mLM \u00eenva\u021b\u0103 meteorologia\/climatul din\u00a0sta\u021bie specific\u0103 domeniului<\/a><\/span>\u00a0\u00een c\u00e2teva s\u0103pt\u0103m\u00e2ni. De asemenea, mLM se actualizeaz\u0103 de mai multe ori pe zi, ceea ce ofer\u0103 o corec\u021bie suplimentar\u0103 a prognozei specifice domeniului.<\/p>

Bine, am discutat despre \u0219tiin\u021ba\/tehnologia \u00eembun\u0103t\u0103\u021bit\u0103 utilizat\u0103 pentru a furniza prognoze specifice fiec\u0103rui domeniu, dar \u00eembun\u0103t\u0103\u021be\u0219te aceasta acurate\u021bea prognozelor fa\u021b\u0103 de ceea ce este disponibil publicului? Pe baza \u0219tiin\u021bei\/tehnologiei utilizate pentru a crea prognoza meteo din mLM (meteoblue Learning Multimodel), precizia prognozei ajunge la o eroare absolut\u0103 orar\u0103 mai mic\u0103 de 1,3\u00b0C \u00een primele 24 de ore. Acest lucru \u00eenseamn\u0103 c\u0103 mai mult de 85% din prognoza orar\u0103 de temperatur\u0103 va avea o eroare mai mic\u0103 de 2\u00b0C. Pentru primele 12 ore, eroarea absolut\u0103 este mai mic\u0103 de 0,9\u00b0C.<\/p>

Pentru prognoza precipita\u021biilor, au fost detectate 79% de evenimente cu >1 mm, cu o rat\u0103 de alarm\u0103 fals\u0103 de numai 40%, ob\u021bin\u00e2nd un scor de competen\u021b\u0103 Heidke de 0,49, mai mare dec\u00e2t orice alt furnizor.<\/p>

\u00cen plus, prognoza mLM a fost evaluat\u0103 \u00een compara\u021bie cu alte modele de prognoz\u0103 publicate \u0219i a fost cotat\u0103 ca fiind prognoza num\u0103rul 1 \u00een ceea ce prive\u0219te acurate\u021bea \u00een peste 300 de loca\u021bii din \u00eentreaga lume, dep\u0103\u0219ind toate celelalte prognoze privind precipita\u021biile, temperatura din 11 ore \u0219i, mai exact, num\u0103rul 1 pentru temperatura din primele 12 ore, la egalitate pentru num\u0103rul 1 pentru temperatura din primele 24 de ore, num\u0103rul 1 pentru punctul de rou\u0103 \u0219i viteza v\u00e2ntului \u0219i liderul \u00eendep\u0103rtat num\u0103rul 1 pentru precipita\u021bii >1 mm \u00een 24 de ore.<\/p>

Abordarea mLM este, de asemenea, singura abordare validat\u0103 la nivel global cu rezultate disponibile public, astfel \u00eenc\u00e2t clien\u021bii \u0219tiu la ce se pot a\u0219tepta.<\/strong><\/p>

A\u0219a cum era de a\u0219teptat, exist\u0103 o precizie semnificativ\u0103 atunci c\u00e2nd se aplic\u0103 aceste metode, dar, ca orice model, este vorba de o prognoz\u0103, iar prognozele se vor schimba \u00eentr-un interval de timp \u0219i spa\u021biu scurt. Prin urmare, este important s\u0103 avem actualiz\u0103ri din or\u0103 \u00een or\u0103. Ceea ce este esen\u021bial este c\u0103 eroarea modelului de prognoz\u0103 este redus\u0103 prin aplicarea acestei abord\u0103ri.<\/p>

\u00cen alte studii, atunci c\u00e2nd se compar\u0103 o prognoz\u0103 specific\u0103 unui teren cu cea mai apropiat\u0103 prognoz\u0103 a unui ora\u0219\/localitate, cu valorile reale \u00eenregistrate la sta\u021bia de teren, \u00eembun\u0103t\u0103\u021birea poate varia \u00eentre 35 \u0219i 65% pentru temperatur\u0103 \u0219i precipita\u021bii pe o perioad\u0103 de 3 zile. Din nou, acest lucru reduce eroarea din prognoza specific\u0103 terenului, ceea ce reprezint\u0103 o \u00eembun\u0103t\u0103\u021bire fa\u021b\u0103 de prognozele tradi\u021bionale.<\/p>

\"Prognoza<\/p>

\u00a0<\/h3>

Ce \u00eenseamn\u0103 toate acestea?<\/h3>

\u00censeamn\u0103 c\u0103 acum ave\u021bi un prognoza specific\u0103 domeniului<\/a><\/span> care este actualizat din or\u0103 \u00een or\u0103 pentru urm\u0103toarele 7 zile, ceea ce este foarte precis \u0219i nu se bazeaz\u0103 pe cel mai apropiat ora\u0219, ci este construit \u0219i corectat pe baza sta\u021biei dumneavoastr\u0103 de teren.<\/p>

Deci, ce facem cu aceste previziuni specifice domeniului?<\/h3>

\u00cen primul r\u00e2nd, ele ne ofer\u0103 o perspectiv\u0103 asupra condi\u021biilor pentru multe opera\u021biuni pe teren, \u00eembun\u0103t\u0103\u021besc verificarea instinctiv\u0103 a deciziilor care se iau, cum ar fi dac\u0103 v\u00e2ntul este favorabil pentru\u00a0pulverizare<\/a><\/span>\u00a0\u00een urm\u0103toarele 24, 48 sau 72 de ore. Prognozele sunt, de asemenea, ad\u0103ugate \u00een instrumentele\/solu\u021biile de planificare a muncii, cum ar fi ferestrele de \u00eens\u0103m\u00e2n\u021bare \u0219i de pulverizare, condi\u021biile de recoltare, capacitatea de prelucrare a solului, accesibilitatea c\u00e2mpului, nutri\u021bia plantelor.<\/p>

Aceste solu\u021bii sunt ferestre orare \u00een condi\u021biile pentru fiecare opera\u021biune. Previziunile specifice fiec\u0103rui sit pot fi ad\u0103ugate, de asemenea, la\u00a0modele de risc de boal\u0103<\/a><\/span>, care ofer\u0103 apoi o predic\u021bie a condi\u021biilor viitoare din urm\u0103toarele 24, 48 sau 72 de ore. Bine\u00een\u021beles, predic\u021bia randamentului se poate baza \u0219i pe o prognoz\u0103 viitoare, dar aceasta utilizeaz\u0103 o medie pe termen lung \u0219i\/sau o prognoz\u0103 ajustat\u0103 sezonier pentru a face o estimare a rezervei poten\u021biale de ap\u0103 pentru predic\u021bia randamentului pe parcursul sezonului de cre\u0219tere.<\/p>

\u00cen imaginea de mai jos, datele specifice sta\u021biei meteo din teren sunt combinate cu datele de mare precizie ale\u00a0prognoza specific\u0103 domeniului<\/a><\/span>\u00a0pentru a produce o fereastr\u0103 de pulverizare pentru protec\u021bia plantelor specific\u0103 pentru fiecare c\u00e2mp.<\/p>

\"Fereastra<\/p>

\u00cen imaginea urm\u0103toare, propunerea de valoare a prognozei \u0219i a sta\u021biei specifice terenului este ilustrat\u0103 \u00een mod clar, deoarece acum ave\u021bi posibilitatea de a cunoa\u0219te condi\u021biile \u00eenainte de a merge pe teren, o fereastr\u0103 orar\u0103 avansat\u0103 cu privire la condi\u021biile din urm\u0103toarele 7 zile \u0219i o ie\u0219ire orar\u0103 prognozat\u0103 pentru variabilele meteorologice importante, cum ar fi rafalele de v\u00e2nt, precipita\u021biile, umiditatea relativ\u0103 \u0219i\u00a0delta T<\/a><\/span>.<\/p>

\"Propunere<\/p>

Atunci c\u00e2nd decide\u021bi s\u0103\u00a0Cump\u0103ra\u021bi o STA\u021aIE METEO sau un dispozitiv IoT<\/strong><\/a><\/span>\u00a0pentru ferma\/c\u00e2mpurile dumneavoastr\u0103,\u00a0includ \u00eentotdeauna tariful orar specific domeniului\u00a0prognoza meteo<\/a><\/span><\/strong>. Sta\u021bia \u0219i prognoza ar trebui s\u0103 fie considerate ca untul de arahide \u0219i jeleul, ele merg m\u00e2n\u0103 \u00een m\u00e2n\u0103 pentru deciziile de gestionare a fermei.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Explora\u021bi prognoza meteo<\/h3>

Vremea \u00een timp real \u0219i istoric\u0103 este important\u0103 pentru a \u00een\u021belege care este impactul asupra culturilor. Vremea viitoare sau previziunile sunt importante pentru planificarea \u0219i activit\u0103\u021bile viitoare. Previziunile meteorologice de mare precizie v\u0103 pot ajuta s\u0103 v\u0103 organiza\u021bi ziua \u0219i s\u0103 reduce\u021bi \u0219i s\u0103 v\u0103 optimiza\u021bi deciziile de gestionare.<\/p><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tCLICK PENTRU A EXPLORA<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Sunte\u021bi curio\u0219i s\u0103 vede\u021bi cum func\u021bioneaz\u0103? \u00cencerca\u021bi-l.<\/h3>

METOS Sta\u021bie meteorologic\u0103 virtual\u0103 VWS<\/a><\/span> este un partener indispensabil pentru to\u021bi cei care iau zilnic decizii care depind de vreme. METOS VWS de o lun\u0103 de prob\u0103 include 1 plasare a coordonatelor, licen\u021b\u0103 de prognoz\u0103 meteo (pentru 1 lun\u0103) \u0219i instrumente de planificare a muncii.<\/p><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tVIZITA\u021aI MAGAZINUL METOS<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Deja un METOS\u00ae<\/sup>\u00a0utilizator?<\/h3>

Activa\u021bi Abonamentul de prognoz\u0103 pentru un an \u0219i ob\u021bine\u021bi date meteorologice aproape reale \u0219i istorice pentru a \u00een\u021belege mai bine impactul asupra culturilor \u0219i pentru a v\u0103 planifica mai bine activit\u0103\u021bile viitoare. Economisi\u021bi timp, bani \u0219i resurse.<\/p><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tLA PROGNOZA METEO<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Despre autor:<\/em>
Guy Ash a lucrat \u00een ultimii 30 de ani ca agrometeorolog \u0219i specialist \u00een \u0219tiin\u021ba observa\u021biilor terestre. \u00cen prezent, este managerul global de formare \u0219i al conturilor cheie \u00een Canada pentru Pessl Instruments, Austria. Pessl Instrument este o companie IoT care produce hardware (loggere \u0219i senzori) \u0219i solu\u021bii software care se concentreaz\u0103 pe sectorul agricol. Lucr\u0103m \u00een peste 85 de \u021b\u0103ri \u0219i avem peste 70.000 de dispozitive \u0219i 700.000 de senzori implementa\u021bi pentru o gam\u0103 larg\u0103 de aplica\u021bii \u00een agricultur\u0103: gestionarea bolilor, iriga\u021bii, umiditatea solului, capcane pentru insecte, camere pentru culturi, sta\u021bii meteo, fertilitatea solului etc. Unul dintre rolurile sale este acela de a oferi instruire la nivel global pentru o list\u0103 extins\u0103 de solu\u021bii IoT pentru o mare varietate de culturi - orez, gr\u00e2u, soia, portocale, porumb, canola, furaje, struguri, fructe \u0219i legume etc.<\/p>

\"Avatar-Guy\"<\/p>

Guy Ash,<\/center>
METOS\u00ae<\/sup> Manager global de formare<\/center>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t<\/i>\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\u00ceNAPOI LA TOATE INTR\u0102RILE DE PE BLOG<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

We need to discuss weather forecasts, since the future impacts of weather on the field are as important, if not more important, as the conditions up to date. Farm Weather Talk #002 – Weather Forecasts In the first installment of\u00a0Farm Weather Talk, we discussed\u00a0the benefit of a site-specific field weather station or IoT device and […]<\/p>\n","protected":false},"author":2,"featured_media":49869,"comment_status":"closed","ping_status":"open","sticky":false,"template":"elementor_header_footer","format":"standard","meta":{"ocean_post_layout":"","ocean_both_sidebars_style":"","ocean_both_sidebars_content_width":0,"ocean_both_sidebars_sidebars_width":0,"ocean_sidebar":"0","ocean_second_sidebar":"0","ocean_disable_margins":"enable","ocean_add_body_class":"","ocean_shortcode_before_top_bar":"","ocean_shortcode_after_top_bar":"","ocean_shortcode_before_header":"","ocean_shortcode_after_header":"","ocean_has_shortcode":"","ocean_shortcode_after_title":"","ocean_shortcode_before_footer_widgets":"","ocean_shortcode_after_footer_widgets":"","ocean_shortcode_before_footer_bottom":"","ocean_shortcode_after_footer_bottom":"","ocean_display_top_bar":"default","ocean_display_header":"default","ocean_header_style":"","ocean_center_header_left_menu":"0","ocean_custom_header_template":"0","ocean_custom_logo":0,"ocean_custom_retina_logo":0,"ocean_custom_logo_max_width":0,"ocean_custom_logo_tablet_max_width":0,"ocean_custom_logo_mobile_max_width":0,"ocean_custom_logo_max_height":0,"ocean_custom_logo_tablet_max_height":0,"ocean_custom_logo_mobile_max_height":0,"ocean_header_custom_menu":"0","ocean_menu_typo_font_family":"0","ocean_menu_typo_font_subset":"","ocean_menu_typo_font_size":0,"ocean_menu_typo_font_size_tablet":0,"ocean_menu_typo_font_size_mobile":0,"ocean_menu_typo_font_size_unit":"px","ocean_menu_typo_font_weight":"","ocean_menu_typo_font_weight_tablet":"","ocean_menu_typo_font_weight_mobile":"","ocean_menu_typo_transform":"","ocean_menu_typo_transform_tablet":"","ocean_menu_typo_transform_mobile":"","ocean_menu_typo_line_height":0,"ocean_menu_typo_line_height_tablet":0,"ocean_menu_typo_line_height_mobile":0,"ocean_menu_typo_line_height_unit":"","ocean_menu_typo_spacing":0,"ocean_menu_typo_spacing_tablet":0,"ocean_menu_typo_spacing_mobile":0,"ocean_menu_typo_spacing_unit":"","ocean_menu_link_color":"","ocean_menu_link_color_hover":"","ocean_menu_link_color_active":"","ocean_menu_link_background":"","ocean_menu_link_hover_background":"","ocean_menu_link_active_background":"","ocean_menu_social_links_bg":"","ocean_menu_social_hover_links_bg":"","ocean_menu_social_links_color":"","ocean_menu_social_hover_links_color":"","ocean_disable_title":"default","ocean_disable_heading":"default","ocean_post_title":"","ocean_post_subheading":"","ocean_post_title_style":"","ocean_post_title_background_color":"","ocean_post_title_background":0,"ocean_post_title_bg_image_position":"","ocean_post_title_bg_image_attachment":"","ocean_post_title_bg_image_repeat":"","ocean_post_title_bg_image_size":"","ocean_post_title_height":0,"ocean_post_title_bg_overlay":0.5,"ocean_post_title_bg_overlay_color":"","ocean_disable_breadcrumbs":"default","ocean_breadcrumbs_color":"","ocean_breadcrumbs_separator_color":"","ocean_breadcrumbs_links_color":"","ocean_breadcrumbs_links_hover_color":"","ocean_display_footer_widgets":"default","ocean_display_footer_bottom":"default","ocean_custom_footer_template":"0","ocean_post_oembed":"","ocean_post_self_hosted_media":"","ocean_post_video_embed":"","ocean_link_format":"","ocean_link_format_target":"self","ocean_quote_format":"","ocean_quote_format_link":"post","ocean_gallery_link_images":"off","ocean_gallery_id":[],"footnotes":""},"categories":[2,154],"tags":[410,411,384,412,413,414,32,259,415,416,417,418,419,16,393,391,322,275,420,263,402],"class_list":["post-49868","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","category-pessl-blog","tag-disease-risk-models","tag-downscaling","tag-farm-management","tag-field-operations","tag-field-specific-forecast","tag-heidke-skill-score","tag-iot-solutions","tag-iot-weather-solutions","tag-learning-multimodel","tag-meteoblue","tag-meteorological-variables","tag-mlm-approach","tag-mlm-forecast","tag-pessl-instruments","tag-precipitation","tag-relative-humidity","tag-weather-forecast","tag-weather-solution","tag-work-planning-solutions","tag-work-planning-tools","tag-yield-prediction","entry","has-media"],"yoast_head":"\nFarm Weather Talk #002 - Weather Forecasting - METOS by Pessl Instruments<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/metos.at\/farm-weather-talk-002\/\" \/>\n<meta property=\"og:locale\" content=\"ro_RO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Farm Weather Talk #002 - Weather Forecasting - METOS by Pessl Instruments\" \/>\n<meta property=\"og:description\" content=\"We need to discuss weather forecasts, since the future impacts of weather on the field are as important, if not more important, as the conditions up to date. 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