Ecosystem Targets and Supporting Indicators

Heavy Precipitation

The heavy precipitation indicator shows the frequency of heavy single-day rain or snow events over a year. These events exceed the normal frequency of heavy precipitation.

Show/Hide Table Data

Days Greater Than 0.5 Inches - Queens, NY
YearDaysTrendline
19402727.19
19412527.24
19423127.28
19432627.32
19443527.36
19453027.41
19462527.45
19473127.49
19483527.53
19492527.58
19502527.62
19513727.66
19523827.71
19533827.75
19542927.79
19552327.83
19562427.88
19572327.92
19583427.96
19592628.00
19603328.05
19613028.09
19622528.13
19631628.17
19642128.22
19651328.26
19661928.30
19672828.35
19682828.39
19693028.43
19701328.47
19713128.52
19724128.56
19733128.60
19742628.64
19753928.69
19761928.73
19773128.77
19782628.82
19793228.86
19802428.90
19812628.94
19822128.99
19834429.03
19843229.07
19852329.11
19862729.16
19872929.20
19882729.24
19893629.29
19903329.33
19912129.37
19921829.41
19933229.46
19943329.50
19952429.54
19962929.58
19973329.63
19982829.67
19993029.71
20002929.75
20012129.80
20023029.84
20033929.88
20043029.93
20052829.97
20063630.01
20073330.05
20083230.10
20093430.14
20102730.18
20113830.22
20122330.27
20132730.31
20143230.35
20152530.40
20162530.44
20172930.48
20184930.52
20194030.57
20202530.61
Days Greater Than 1.0 Inches - Queens, NY
YearDaysTrendline
19401110.17
1941810.19
19421510.21
19431110.24
19441210.26
19451210.28
19461210.30
19471110.32
19481410.34
1949510.36
1950810.38
19511410.40
19521710.42
19531010.45
19541110.47
19551110.49
1956810.51
1957810.53
19581410.55
19591010.57
19601710.59
19611310.61
1962910.63
1963610.66
1964410.68
1965210.70
1966710.72
19671010.74
19681210.76
19691510.78
1970510.80
19711010.83
1972810.84
19731610.87
1974710.89
19751910.91
1976910.93
19771210.96
1978810.97
1979910.99
1980811.01
1981711.03
1982811.05
19831911.08
19841511.10
19851211.12
1986611.14
19871011.16
19881311.18
19891611.20
19901311.22
19911211.24
1992711.26
1993911.29
1994611.31
1995611.33
19961311.35
1997911.37
19981311.39
1999911.41
20001311.43
2001711.45
20021311.47
20031511.50
20041311.52
20051011.54
20061811.56
20071611.58
20081211.60
2009911.62
20101411.64
20112011.66
2012611.68
2013711.71
20141611.73
20151311.75
2016911.77
20171011.79
20181711.81
20191211.83
20201111.85
Days Greater Than 0.5 Inches - Bridgeport, CT
YearDaysTrendline
19492724.05
19502324.14
19512624.23
19523324.32
19533324.41
19542424.50
19552324.59
19562524.68
19572024.77
19583024.86
19592224.95
19602525.04
19612625.13
19621625.22
19632025.31
19641225.40
19651525.49
19661925.58
19672725.67
19683125.76
19692625.85
19701725.94
19713526.02
19723926.11
19733926.20
19742926.29
19753726.38
19762226.47
19772926.56
19782726.65
19792726.74
19802626.83
19812426.92
19822527.01
19834627.10
19842527.19
19852427.28
19861927.37
19871927.46
19882627.55
19893027.64
19902827.73
19912127.82
19923127.91
19932328.00
19942928.09
19952028.18
19962528.26
19972528.35
19982928.44
19992528.53
20002728.62
20012128.71
20023528.80
20033928.89
20042828.98
20052929.07
20063529.16
20072329.25
20083129.34
20093029.43
20103029.52
20113829.61
20122129.70
20132329.79
20143529.88
20152729.97
20163230.06
20172830.15
20184430.24
20193730.33
20202430.42
Days Greater Than 1.0 Inches - Bridgeport, CT
194968.85
195088.88
1951138.91
1952128.94
195398.97
1954109.00
195579.03
195689.05
195749.08
195899.11
195969.14
196099.17
196159.20
196299.23
196359.26
196429.29
196549.32
196659.35
1967109.38
1968149.41
1969149.44
197069.47
1971239.50
1972229.53
1973209.56
197489.59
1975119.62
1976119.65
1977119.68
1978139.71
1979129.74
1980109.77
198169.80
1982139.83
1983159.86
198499.89
198579.92
198659.95
198769.98
1988910.01
19891210.04
1990910.07
1991810.10
19921110.13
1993910.16
1994710.19
1995810.22
1996910.25
1997610.28
19981210.31
19991110.34
2000810.37
2001910.40
20021110.43
20031010.46
20041010.49
20051010.52
20061610.54
20071010.57
20081210.60
2009810.63
20101410.66
20111710.69
2012710.72
2013810.75
20141410.78
2015510.81
2016910.84
20171010.87
20181710.90
20191110.93
2020910.96

What is the Heavy Precipitation Indicator?

The heavy precipitation indicator shows the frequency of heavy single-day rain or snow events over a year. These events exceed the normal frequency of heavy precipitation. Here we include two different scenarios that are considered heavy precipitation – greater than 0.5 inches and 1 inch over a 24-hour period. Since precipitation varies by area, we show two locations representing both states surrounding the Long Island Sound – La Guardia Airport, Queens, New York and Igor I Sikorsky Memorial Airport, Bridgeport, Connecticut.

What does heavy precipitation indicate?

From 1910-1980, the frequency of heavy single-day precipitation events was largely consistent. Since then, there has been a significant increase (EPA 2016). The reason for this acceleration may be driven by climate change. Climate change effects are known to influence the intensity and frequency of extreme weather events, including heavy precipitation. As the ocean warms, the evaporation rate increases, and since there is more moisture in the atmosphere, precipitation intensifies in quantity and frequency.

Heavy precipitation can have severe implications on the overall ecosystem health of the Long Island Sound. Rainfall on impervious surfaces increases the runoff input to waterbodies. Runoff carries a multitude of pollutants, including various nutrients (nitrogen), bacteria (E.coli), emerging (PBDE, pharmaceuticals) and legacy (heavy metals, PCBs) contaminants, and debris. The increase in pollutants impairs water quality, reduces habitat quality, and harms biota in the Sound. Furthermore, high nitrogen concentrations in the water column creates hypoxic conditions, meaning the increase in nutrients stimulates algal growth (known as algal blooms), and leads to severe decreases in dissolved oxygen. This depletion in oxygen induces massive fish kills. These impacts can scale-up and inhibit key ecosystem services that residents of the watershed rely on. For example, higher intensity and frequency of precipitation can result in flooding, which can enhance coastal erosion, hinder agriculture production, and damage coastal infrastructure.

Additionally, both Connecticut and New York Health Departments implement policies to restrict swimming and other recreational activities after rainfall exceeds a certain amount over a specific period of time. Connecticut prohibits swimming if rainfall exceeds 1 inch over a 24-hour period, or over 2 inches within 48 hours. In New York, Suffolk County also restricts swimming when rainfall exceeds 1 inch over a 24-hour period, while it’s 0.5 inches for Nassau County (New York City issues a rain advisory when rainfall exceeds 0.3 – 2.5 inches and Westchester issues after 0.5 – 2.0 inches). The increase in precipitation induces bacteria outbreaks in the waterbody, and therefore forces beach closures to protect the public from adverse effects. Furthermore, impaired water quality can also impact the commercial and recreational fisheries. When fish and shellfish consume these contaminants, it can cascade through the food chain and pose serious health effects on human – this is called biomagnification.

Status

Both New York and Connecticut locations are experiencing the same trend – increase in frequency of heavy precipitation events. Both scenarios, greater than 0.5 inches and 1 inch, are increasing. However, the frequency for greater than 0.5 inches is increasing at a faster rate than 1 inch – specifically in Connecticut (29 and 26 percent increase, respectively) compared to New York (11 and 17 percent increase, respectively). We chose to use the 0.50 inches scenario as the New England region has seen a significant increase in the amount of precipitation above this threshold compared to other regions of the country. Simultaneously, in 2018, total annual precipitation was highest on record for both stations – La Guardia Airport was fourth highest (1940-2019) and Igor I Sikorsky Memorial Airport was second highest (1949-2019).  By tracking both scenarios, we will be able to understand the heavy precipitation trends in our region, and therefore make more informed management decisions to better prepare for future conditions.

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