Climate Data for Latitude 33.75 Longitude 4.25

Köppen climate classification: BWh (Climate: arid; Precipitation: desert; Temperature: hot arid)
 

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Mediterranean dry woodlands and steppe ecoregion

Averages (English) Metric

TypeUnitsJanFebMarAprMayJunJulAugSepOctNovDecPeriod
Min Temp37.940.544.951.059.468.474.073.365.955.646.040.0109 years
Mean Temp47.350.655.762.271.381.187.286.277.666.255.849.2109 years
Max Temp56.760.766.573.683.393.9100.699.289.476.965.758.5109 years
FrostDays21.313.514.78.63.02.22.91.72.53.110.116.811 years
WetDays3.23.63.62.72.11.30.71.11.53.02.54.1109 years
Precipitationin1.00.60.80.60.70.40.10.20.50.60.80.9107 years
Potential Evapotranspirationin1.82.43.54.65.96.77.26.64.93.62.21.8109 years
Yearly Average Temperatures 1901 - 2009 (English) Latitude 33.75 Longitude 4.25
Monthly Mean Temperatures 1901 - 2009 (English) Latitude 33.75 Longitude 4.25
Yearly Total Frost Days 1903 - 2009 Latitude 33.75 Longitude 4.25
Yearly Total Precipitation 1901 - 2009 (English) Latitude 33.75 Longitude 4.25
Yearly Total Wet Days 1901 - 2009 Latitude 33.75 Longitude 4.25
Yearly Total Potential Evapotranspiration 1901 - 2009 (English) Latitude 33.75 Longitude 4.25

Climate data provided by CRU TS 3.1 - University of East Anglia Climate Research Unit (CRU). [Phil Jones, Ian Harris]. CRU Time Series (TS) high resolution gridded datasets, [Internet]. NCAS British Atmospheric Data Centre, 2008, Accessed: 28-July-2011
Charting software provided by pChart - a PHP class to build charts.
Köppen climate classification provided by Kottek, M., J. Grieser, C. Beck, B. Rudolf, and F. Rubel, 2006: World Map of Köppen-Geiger Climate Classification updated. Meteorol. Z., 15, 259-263
The calculation method for the potential evapotranspiration is the FAO grass reference equation (Ekstrom et al., 2007, which is based on Allen et al., 1994). It is a variant of the Penman Monteith method using TMP, TMN, TMX, VAP, CLD.
(default) 12 queries took 162 ms
NrQueryErrorAffectedNum. rowsTook (ms)
1SELECT dtype, COUNT(*) AS yearcnt, AVG(m1) AS a1, AVG(m2) AS a2, AVG(m3) AS a3, AVG(m4) AS a4, AVG(m5) AS a5, AVG(m6) AS a6, AVG(m7) AS a7, AVG(m8) AS a8, AVG(m9) AS a9, AVG(m10) AS a10, AVG(m11) AS a11, AVG(m12) AS a12 FROM climate c WHERE gridx=369 AND gridy=248 GROUP BY dtype77152
2SELECT `Geographic`.`id`, `Geographic`.`name`, `Geographic`.`geotype`, `Geographic`.`mapped`, `Geographic`.`center_lat`, `Geographic`.`center_lon`, `Geographic`.`gridx`, `Geographic`.`gridy`, `Geographic`.`climate`, `Geographic`.`landuse`, `Geographic`.`koeppen` FROM `geographics` AS `Geographic` WHERE `Geographic`.`gridx` = 369 AND `Geographic`.`gridy` = 248 AND `Geographic`.`geotype` IN ('H', 'J', 'K', 'N', 'Q', 'T', 'U', 'V', 'F', 'P', 'W', 'X', 'Y', 'Z', 'BA', 'AZ') ORDER BY `Geographic`.`name` ASC 112
3SELECT koeppenval FROM koeppen WHERE gridx = 369 AND gridy = 248110
4SELECT dtype, dyear, (m1 + m2 + m3 + m4 + m5 + m6 + m7 + m8 + m9 + m10 + m11 + m12) / 12 as avg FROM climate c WHERE gridx=369 AND gridy=248 AND dtype IN ('N','T','X') ORDER BY dtype, dyear3273272
5SELECT dyear, m1, m2, m3, m4, m5, m6, m7, m8, m9, m10, m11, m12 FROM climate c WHERE gridx=369 AND gridy=248 AND dtype = 'T' ORDER BY dyear1091091
6SELECT dyear, m1 + m2 + m3 + m4 + m5 + m6 + m7 + m8 + m9 + m10 + m11 + m12 as tot FROM climate c WHERE gridx=369 AND gridy=248 AND dtype='F' ORDER BY dyear11111
7SELECT dyear, m1 + m2 + m3 + m4 + m5 + m6 + m7 + m8 + m9 + m10 + m11 + m12 as tot FROM climate c WHERE gridx=369 AND gridy=248 AND dtype='P' ORDER BY dyear1071071
8SELECT dyear, m1 + m2 + m3 + m4 + m5 + m6 + m7 + m8 + m9 + m10 + m11 + m12 as tot FROM climate c WHERE gridx=369 AND gridy=248 AND dtype='R' ORDER BY dyear1091091
9SELECT dyear, m1 + m2 + m3 + m4 + m5 + m6 + m7 + m8 + m9 + m10 + m11 + m12 as tot FROM climate c WHERE gridx=369 AND gridy=248 AND dtype='E' ORDER BY dyear1091091
10SELECT `Databasis`.`database_name_displayed`, `Databasis`.`record_id`, `Databasis`.`web_site`, `Databasis`.`abstract` FROM `databases` AS `Databasis` WHERE `Databasis`.`record_id` = (1021) 111
11SELECT `Databasis`.`database_name_displayed`, `Databasis`.`record_id`, `Databasis`.`web_site`, `Databasis`.`abstract` FROM `databases` AS `Databasis` WHERE `Databasis`.`record_id` = (1022) 110
12SELECT `Databasis`.`database_name_displayed`, `Databasis`.`record_id`, `Databasis`.`web_site`, `Databasis`.`abstract` FROM `databases` AS `Databasis` WHERE `Databasis`.`record_id` = (4463) 110