Argentina vs Bangladesh: Tropical nights

Tropical nights in 2014: 42.6 nights in Argentina and 239.9 nights in Bangladesh, in the CMIP6 climate models’ median run. In 2014 the value was higher in Bangladesh, by 197.3 nights, or 5.63 times that in Argentina.

Watch it change on the map

nights a year · CMIP6

ArgentinaBangladeshCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

Bangladesh has been higher in every year both have figures for since 1950.
The CMIP6 model median (SSP2-4.5, middle of the road) puts Argentina at 65.2 nights and Bangladesh at 269.8 nights in 2100.

Every year

nights a year · CMIP6

Year	Argentina	Bangladesh
2014	42.6	239.9
2013	41.8	239
2012	41	240.4
2011	41.5	240.5
2010	40.8	241
2009	41.6	238.6
2008	41.4	236.7
2007	39.6	236.9
2006	39.3	238.9
2005	40.1	238.2
2004	40.6	238.7
2003	38.7	236.5
2002	40.2	237.6
2001	39.5	237.2
2000	39.5	239.3
1999	38.4	236.6
1998	38.8	235.5
1997	38.5	235.5
1996	37	235.5
1995	35.7	234.8
1994	34.7	233.6
1993	34.3	232.2
1992	33.4	228
1991	36.8	233.4
1990	36	234.6
1989	37	235.7
1988	36.9	235.1
1987	36.1	236.4
1986	36.4	233.8
1985	36	233.6
1984	34.7	236
1983	35.2	230
1982	35.7	232.3
1981	37.3	235.9
1980	36.3	233.4
1979	37.5	234.5
1978	35.7	231.8
1977	35.1	232.3
1976	35.7	232
1975	34.8	231.3
1974	35.4	232.9
1973	34.1	232.1
1972	35.5	234.3
1971	34.7	233.1
1970	34.9	232.5
1969	33.4	231.1
1968	34.6	229.7
1967	33	231.6
1966	34.3	232.6
1965	32.2	232.5
1964	30.3	229.3
1963	32	233.8
1962	35.2	231.9
1961	35.6	236.2
1960	35.6	232.5
1959	34.5	234.7
1958	33.3	233.5
1957	35.7	232.5
1956	35	234.3
1955	34.4	230.2
1954	33.6	232.9
1953	35.8	234
1952	34.4	230.3
1951	35.4	233.5
1950	33.9	233.9

CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100

Year	Argentina	Bangladesh
2015	44.433.5–53.4	241.2227–252.4
2016	43.532.4–53.4	237.9226.6–249.3
2017	42.834.2–52.6	239.8227.5–249.4
2018	42.632.7–52.6	242.6227–255
2019	43.633.4–53.1	241.2228.5–251.9
2020	45.735.5–57.2	242.6229.3–254.4
2021	45.634.3–56.4	244.3230.4–254.4
2022	44.633.3–56.4	243.8231.5–254.2
2023	44.934.9–53.9	243.5229.2–254.5
2024	45.834.2–57.5	245.7231.4–257.1
2025	46.536–58.1	242.5229.4–253.9
2026	47.936.7–57	243.9227.9–258.1
2027	46.434.5–56.3	247.1232.8–259.3
2028	46.133.5–58.5	244.2232.2–254.4
2029	48.336–58.8	247.3232.7–261.5
2030	47.835.4–60.3	243.9232.3–255.2
2031	46.935.5–58.7	245.1232.9–262.3
2032	4837.9–59.7	247.6236.6–257.8
2033	47.436.7–57.6	245.3231.7–256.6
2034	47.837.8–58.9	246.3233.2–260.4
2035	47.339–59	246.4234.1–260.9
2036	48.939.2–58.4	246.2228.6–260.4
2037	5141.2–60.9	247.7235.4–260.2
2038	48.737.9–59.7	249232.1–261
2039	48.839.1–58.4	250234.4–262.7
2040	50.440.4–62.3	248.9235.5–260.5
2041	50.740.4–61.7	248.3235.6–261.9
2042	5037.3–61.1	252.5237.8–265.3
2043	50.340.5–61	250.8234.7–263.4
2044	5240–65	251.8239.1–265.2
2045	52.441.3–65.6	250.3239.1–265.6
2046	51.941.2–62.7	252.7238.9–267.8
2047	51.542–64	253.9239.4–267.1
2048	54.542.6–65	254.4242.7–270.5
2049	53.942.8–64.9	253.7241.5–266.4
2050	52.543.6–62.4	254.6242.5–269.2
2051	55.743.3–67.4	254.7242.7–270.1
2052	55.642.2–67	252.3240.2–264.6
2053	55.342.6–67.6	256.9244–272.4
2054	54.743–66.7	255.9243.5–269.4
2055	55.942.3–67.2	255.2243.8–273.6
2056	57.642.8–68.6	259.1243.6–274.7
2057	56.842.3–68.7	257.5243.8–273.7
2058	54.841.5–68.1	257.4245.6–274.2
2059	57.844.9–70.3	258.3246.4–271.8
2060	56.943.4–67.9	259.2246.1–272.6
2061	56.542.3–70.6	257.7244.8–270.1
2062	57.345.8–68.5	260.4246.4–274.2
2063	58.244.6–70.2	259.9241.3–272.7
2064	58.845.8–71.5	260.2245.9–273.1
2065	58.746–71.1	259.8244.1–274.7
2066	59.947–68.9	260246.6–274.6
2067	58.944.8–71.5	261.4246.4–272.3
2068	57.844.3–70.3	260.1245.8–274.8
2069	59.445.4–70.5	263.3249.8–276.6
2070	61.348.2–74.3	259.6245.8–272.6
2071	60.148.7–73.2	262.2248.7–283.4
2072	60.146.7–73.7	259.8248.6–276
2073	60.847.6–73.5	264.1246.6–277.2
2074	60.447.6–73.7	262.6248.3–276.6
2075	61.347.9–73.9	263.6248.5–277.7
2076	61.146.8–75.8	261.6251–276.9
2077	60.647.1–73.1	264251.1–279.8
2078	63.449.4–75.6	265251.6–281.6
2079	59.948.7–73	263.8248.5–277.2
2080	6348.1–75.5	266.8251.9–280.3
2081	61.448.7–73.5	266.5250.7–279.9
2082	61.747.7–75	264249.6–277.3
2083	62.148.2–75.6	266.6251.8–282.8
2084	62.950.3–76	264.8253.1–284.2
2085	6246.9–76.4	265.4251.2–283.4
2086	62.749.4–76.4	268.2252.8–285.3
2087	61.847.9–74.9	265.7251.3–280.8
2088	64.450.8–77.5	267.2252.6–284.4
2089	62.749.3–76.3	267.1252.5–286.7
2090	64.152.5–77.1	267.9254.9–283.4
2091	64.451.7–78.3	267.7254.5–282.2
2092	65.650.8–78.3	268.8253.6–281.7
2093	62.749.7–76.8	268.1251.7–287
2094	63.950.1–78.5	267.4251.3–287.4
2095	62.948.8–77.9	270.8253.7–284.9
2096	64.749.4–78.9	267.9250.5–285.8
2097	64.552.4–80.1	269.3254.9–287.3
2098	65.652.7–78.7	268.8252.4–284.9
2099	65.249.3–80.2	269253–282.3
2100	65.250–81.7	269.8254.8–284.9

Each country on its own

Good to know

Nights in a year when the temperature stays above 20 °C, averaged over the country.
Source: World Bank Climate Change Knowledge Portal, CMIP6 multi-model median.
The dashed line is the CMIP6 model median (SSP2-4.5, middle of the road), a scenario rather than a forecast; the band is its models’ 10th–90th percentile.
Climate model values are the median of the CMIP6 models, run on past emissions to 2014 and on SSP2-4.5, a middle-of-the-road path, after: they are not measurements.

How the layers work, where their data comes from and what they can’t tell you: Countries through time

Argentina vs Bangladesh: Tropical nights

What the numbers say

Every year

Each country on its own

Good to know

Argentina vs Bangladesh

Health

People

Economy

Education

Politics

Conflict

Military

Climate

Technology and environment