• TABLE OF CONTENTS
HIDE
 Front Cover
 Acknowledgement
 Foreword
 Introduction
 Data and methodology
 Precipitation
 Evaporation and rainfall defic...
 Temperature
 Growing and heat stress degree...
 Hurricanes
 Forest fires
 Reference
 Back Cover






Group Title: El Nino, La Nina and Florida's climate
Title: El Nin̆o, La Nin̆a and Florida's climate
CITATION PAGE IMAGE ZOOMABLE PAGE TEXT
Full Citation
STANDARD VIEW MARC VIEW
Permanent Link: http://ufdc.ufl.edu/UF00053822/00001
 Material Information
Title: El Nin̆o, La Nin̆a and Florida's climate effects on agriculture and forestry
Alternate Title: Nin̆o, La Nin̆a and Florida's climate
Physical Description: 1 v. (unpaged) : col. ill., maps ; 28 cm.
Language: English
Creator: Florida State University -- Center for Ocean-Atmospheric Prediction Studies
University of Florida -- Institute of Food and Agricultural Sciences
Rosenstiel School of Marine and Atmospheric Science
Florida Consortium
Publisher: Florida Consortium
Place of Publication: <Tallahassee>
Publication Date: <1999>
 Subjects
Subject: Crops and climate -- Florida   ( lcsh )
Forest microclimatology -- Florida   ( lcsh )
El Niño Current   ( lcsh )
La Niña Current   ( lcsh )
Genre: government publication (state, provincial, terriorial, dependent)   ( marcgt )
bibliography   ( marcgt )
non-fiction   ( marcgt )
 Notes
Bibliography: Includes bibliographical references.
Statement of Responsibility: the Florida Consortium, the Florida State University Center for Ocean-Atmospheric Prediction Studies, University of Florida Institute of Food and Agricultural Sciences, University of Miami Rosenstiel School of Marine & Atmospheric Science.
General Note: "June 1999."
Funding: Florida Historical Agriculture and Rural Life
 Record Information
Bibliographic ID: UF00053822
Volume ID: VID00001
Source Institution: Marston Science Library, George A. Smathers Libraries, University of Florida
Holding Location: Florida Agricultural Experiment Station, Florida Cooperative Extension Service, Florida Department of Agriculture and Consumer Services, and the Engineering and Industrial Experiment Station; Institute for Food and Agricultural Services (IFAS), University of Florida
Rights Management: All rights reserved by the source institution and holding location.
Resource Identifier: aleph - 002500624
oclc - 43577776
notis - AML6350

Table of Contents
    Front Cover
        Front Cover
    Acknowledgement
        Acknowledgement 1
        Acknowledgement 2
    Foreword
        Foreword
    Introduction
        Page 1
        What are El Nino and La Nina?
            Page 1
        How ocean temperatures affect Florida's climate
            Page 1
    Data and methodology
        Page 2
        Defining El Nino and La Nina
            Page 2
        Maps of temperature and precipitation anomalies
            Page 2
        Graphs of monthly average climate statistics
            Page 3
            Page 4
    Precipitation
        Page 5
        Page 6
        Page 7
        Page 8
        Page 9
    Evaporation and rainfall deficit
        Page 10
        Page 11
        Page 12
        Page 13
    Temperature
        Page 14
        Page 15
        Page 16
        Page 17
        Page 18
        Page 19
    Growing and heat stress degree-days
        Page 20
        Page 21
        Page 22
        Page 23
    Hurricanes
        Page 24
    Forest fires
        Page 25
    Reference
        Page 26
        Page 27
    Back Cover
        Back Cover
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ACKNOWLEDGMENTS


This booklet was prepared by the Florida Consortium, which is a collaborative effort of the
Center for Ocean-Atmospheric Prediction Studies (COAPS) at the Florida State University.
the Institute of Food and Agricultural Sciences (IFAS) at the University of Florida. and the
Rosenstiel School of Marine and Atmospheric Science (RSMAS) at the University of Miami.
The Florida Consortium seeks to identify regions susceptible to climate variability, assess the
vulnerability of agriculture and production systems in these regions, and develop strategies to
cope with climate change. The Florida Consortium has its base support from the NOAA Office
of Global Programs. In addition, we have support from the National Science Foundation and
the InterAmerican Institute for Global Change Research.

COAPS, under the direction of Dr. James J. O'Brien, receives its base support from the
Office of Naval Research, Secretary of the Navy Grant. NASA Headquarters provides addi-
tional funding.

This project was partially supported by the Institute of Food and Agricultural Sciences
(IFAS) at the University of Florida. Florida Consortium investigators at the University of Florida
are faculty members in the Department of Agricultural and Biological Engineering and the
Food and Resource Economics Department at IFAS. We also acknowledge the contributions
of other graduate students and faculty members at IFAS for the research and surveys that led
to the development of this booklet.

We would like to thank the National Climatic Data Center for their work with the USHCN.
Summary of the Day, and SAMSON data sets.


This booklet was prepared by:

Florida State University/COAPS: James J. O'Brien, David F. Zierden, and
David Legler

University of Florida/IFAS: James W. Hansen, James W. Jones, and
Allen G. Smajstrla

University of Miami/RSMAS: Guillermo PodestA and David Letson


Design and production by: Ruth Pryor, Florida State University/COAPS


Back cover illustration: Mary Donahue











El Niifo, La Ninia and Florida's Climate:
Effects on Agriculture and Forestry







The Florida Consortium


THE FLORIDA STATE
UNIVERSITY

Center for Ocean-Atmospheric
Prediction Studies


UNIVERSITY OF
FLORIDA
Institute of Food and Agricultural
Sciences


June 1999




Cover: The background image shows sea surface height as well as temperature (colors) and
wind (arrows) departures from normal during the El Niho of 1997-1998. The raised, bright red
area indicates surface temperatures in excess of 800F. Image provided courtesy of The
Laboratory for Hydrospheric Processes, NASA/Goddard Space Flight Center. Also pictured
is an AP wire photo of Florida forest fires in the summer of 1998, and a drought-damaged
corn field. Photo taken by Milt Putnam, UF/IFAS.









FOREWORD

A remarkable scientific breakthrough has enormous financial implications for agriculture
and forestry in Florida and the Southeastern United States. It is now possible to forecast El
Niho and its opposite, La Niha, months in advance by monitoring the Pacific Ocean west of
Peru.

These phenomena are extremely important since they affect climate in Florida and the
Southeastern United States. Note that we refer to climate and not weather. Weather is the
day-to-day variations in temperature and precipitation. Weather is chaotic and not predictable
past a few days. Climate variations are shifts of average weather patterns due to global
conditions such as ocean temperatures. An example of weather is a hard freeze in Central
Florida that lasts for 2-3 days. In contrast, one's heating bill may be smaller due to a warmer
winter, which is climate. Climate may also mean more rainfall over the early parts of the
growing season. Farmers and foresters can now know months in advance if a drought or
more rain than normal is anticipated during different seasons of the year. Although there :s
still uncertainty about weather on a day-to-day basis during these seasons, knowing that
these climate patterns are likely will allow decision makers to plan ahead to minimize the risKs
associated with such patterns.

In this booklet we have prepared maps and graphs to illustrate the average shifts of rain
totals and temperature during different seasons due to a typical El Niho and La Niia. These
graphs are based on historical data (e.g. 1948 to 1997) from dozens of weather stations
across Florida and historical records of El Niho and La Niha events. Simply. El Niho usually
means a wetter winter, and maybe cooler; fewer hurricanes in the previous season: and fewer
forest fires, except for the early summer, such as in June 1998. La Nina usually means winter
and spring drought; and more hurricanes in the preceding hurricane season. These shifts in
climate and El Niho/La Nina predictions can have important implications for farmers. For
example, strawberry growers have learned to plant varieties more tolerant to dry conditions in
La Niha years. Some potato farmers in south Florida have crowned their fields in El Niio
years to allow excess January rains to run off. There are potentially many other money-
making possibilities for farmers in Florida and other states in the Southeastern United States.
This publication is provided solely for information purposes. The information does not consti-
tute either a prediction of future weather conditions or recommendations to modify agricultural
practices.

We are continuing to study these ideas and opportunities, and would appreciate hearing
about efforts utilizing information in this report. Please browse our website at (htt.
www.coaps.fsu.edu/lib/Florida_Consortium), or contact us via email, fax, or telephone.





Jim O'Brien & David Legler James W. Jones & James Hansen Guillermo Podesta & Dave Le:sco
Center for Ocean-Atmospheric Institute of Food and Agricultural Rosenstiel School of Marne
Prediction Studies Sciences And Atmospher c Science
The Florida State University University of Florida University of Miam
Suite 200, Johnson Building PO. Box 110570 4600 Rickenbacker Cause,, ay
Tallahassee, FL 32306-2840 Gainesville, FL 32611 Miami. FL 33149-1098
Phone: (850) 644-4581 Phone: (352) 392-8694 Phone: (305) 361-4000
Fax: (850) 644-4841 Fax: (352) 392-4092 Fax: (305) 361-4711
Email: obrien(a coaps.fsu.edu Email: jiones(a agen.ufl.edu Email: gpodes:a. r"< ::;:: e,
Website: www.coaps.fsu.edu Website: www.ifas.ufl.edu Website: www.rsmas.miami.edc









INTRODUCTION


In the winter of 1982-1983, one of the strongest El Niho events measured this century
developed undetected in the waters of the tropical Pacific. California and the Gulf Coast were
battered by strong winter storms, while other parts of the country were drier and warmer than
normal. The event opened the eyes of the nation as well as the scientific community to the
potential climate impacts caused by fluctuations in sea surface temperatures of the equatorial
Pacific Ocean. This year to year variability of climate influences many aspects of our daily
lives, with impacts ranging from our comfort level when we work or travel to disasters such as
hurricanes and floods. It can also influence the productivity and safety of our work. The
agriculture and forestry industries are particularly vulnerable to variations in climate. With a
heightened awareness of El Niho and La Niha driven climate patterns, these sectors have
expressed the need for more detailed information on which to base their decisions.

What are El Niio and La Niia?

Recorded as far back as the 1500's, unusually warm water appeared periodically off the
coast of Peru. This often occurred around Christmas, thus the phenomenon was called El
Niho for the Christ child. Satellite measurements and moored buoys now show that the warm
waters of an El Niho extend along the equator well out into the central Pacific (see cover).
The tropical Pacific can be thought of as a large bathtub. Normally, trade winds blow from
east to west, piling up warm water around Indonesia and Australia. During an El Niho, the
trade winds die down and the warm water sloshes back towards the South American coast,
resulting in sea surface temperatures that are much warmer than normal. In a La Niha,
stronger than normal trade winds bring up cooler water from the ocean's depths, causing the
sea surface to be colder than normal. Although El Niho and La Nina return every 2 to 7 years,
the tropical Pacific can be thought of as neutral, or near normal, a majority of the time. In fact,
neutral years outnumber El Niho or La Niha years over 2 to 1.

How Ocean Temperatures Affect Florida's Climate

The jet stream is a fast moving ribbon of air that circles the globe several miles above the
ground. The jet stream is responsible for steering storms and fronts, driving the day-to-day
weather we all experience. In an El Niho winter, the warm surface waters of the Pacific
provide a source of heat and moisture that strengthens the jet stream, pulls it further south
and keeps it flowing west to east across the southern United States. The new position guides
winter storms into California and along the Gulf Coast. These storms provide abundant rain-
fall and cooler temperatures for Florida and the deep South. In La Nina winters, a weaker jet
stream strays to the north and meanders across the country. Fronts and storms do not make
it down to Florida as often and the winters are warmer and dryer than normal.

Through their relatively predictable influence on the climate of Florida and surrounding
states, El Niho and La Niha have important implications for agricultural production. El Niho
and La Nina influence yields of winter vegetables, some citrus species, sugarcane and field
corn in Florida, and several crops in the neighboring states. This booklet summarizes the
effects of El Niho and La Niha years on the climate of Florida and the Southeast, with









INTRODUCTION


In the winter of 1982-1983, one of the strongest El Niho events measured this century
developed undetected in the waters of the tropical Pacific. California and the Gulf Coast were
battered by strong winter storms, while other parts of the country were drier and warmer than
normal. The event opened the eyes of the nation as well as the scientific community to the
potential climate impacts caused by fluctuations in sea surface temperatures of the equatorial
Pacific Ocean. This year to year variability of climate influences many aspects of our daily
lives, with impacts ranging from our comfort level when we work or travel to disasters such as
hurricanes and floods. It can also influence the productivity and safety of our work. The
agriculture and forestry industries are particularly vulnerable to variations in climate. With a
heightened awareness of El Niho and La Niha driven climate patterns, these sectors have
expressed the need for more detailed information on which to base their decisions.

What are El Niio and La Niia?

Recorded as far back as the 1500's, unusually warm water appeared periodically off the
coast of Peru. This often occurred around Christmas, thus the phenomenon was called El
Niho for the Christ child. Satellite measurements and moored buoys now show that the warm
waters of an El Niho extend along the equator well out into the central Pacific (see cover).
The tropical Pacific can be thought of as a large bathtub. Normally, trade winds blow from
east to west, piling up warm water around Indonesia and Australia. During an El Niho, the
trade winds die down and the warm water sloshes back towards the South American coast,
resulting in sea surface temperatures that are much warmer than normal. In a La Niha,
stronger than normal trade winds bring up cooler water from the ocean's depths, causing the
sea surface to be colder than normal. Although El Niho and La Nina return every 2 to 7 years,
the tropical Pacific can be thought of as neutral, or near normal, a majority of the time. In fact,
neutral years outnumber El Niho or La Niha years over 2 to 1.

How Ocean Temperatures Affect Florida's Climate

The jet stream is a fast moving ribbon of air that circles the globe several miles above the
ground. The jet stream is responsible for steering storms and fronts, driving the day-to-day
weather we all experience. In an El Niho winter, the warm surface waters of the Pacific
provide a source of heat and moisture that strengthens the jet stream, pulls it further south
and keeps it flowing west to east across the southern United States. The new position guides
winter storms into California and along the Gulf Coast. These storms provide abundant rain-
fall and cooler temperatures for Florida and the deep South. In La Nina winters, a weaker jet
stream strays to the north and meanders across the country. Fronts and storms do not make
it down to Florida as often and the winters are warmer and dryer than normal.

Through their relatively predictable influence on the climate of Florida and surrounding
states, El Niho and La Niha have important implications for agricultural production. El Niho
and La Nina influence yields of winter vegetables, some citrus species, sugarcane and field
corn in Florida, and several crops in the neighboring states. This booklet summarizes the
effects of El Niho and La Niha years on the climate of Florida and the Southeast, with









INTRODUCTION


In the winter of 1982-1983, one of the strongest El Niho events measured this century
developed undetected in the waters of the tropical Pacific. California and the Gulf Coast were
battered by strong winter storms, while other parts of the country were drier and warmer than
normal. The event opened the eyes of the nation as well as the scientific community to the
potential climate impacts caused by fluctuations in sea surface temperatures of the equatorial
Pacific Ocean. This year to year variability of climate influences many aspects of our daily
lives, with impacts ranging from our comfort level when we work or travel to disasters such as
hurricanes and floods. It can also influence the productivity and safety of our work. The
agriculture and forestry industries are particularly vulnerable to variations in climate. With a
heightened awareness of El Niho and La Niha driven climate patterns, these sectors have
expressed the need for more detailed information on which to base their decisions.

What are El Niio and La Niia?

Recorded as far back as the 1500's, unusually warm water appeared periodically off the
coast of Peru. This often occurred around Christmas, thus the phenomenon was called El
Niho for the Christ child. Satellite measurements and moored buoys now show that the warm
waters of an El Niho extend along the equator well out into the central Pacific (see cover).
The tropical Pacific can be thought of as a large bathtub. Normally, trade winds blow from
east to west, piling up warm water around Indonesia and Australia. During an El Niho, the
trade winds die down and the warm water sloshes back towards the South American coast,
resulting in sea surface temperatures that are much warmer than normal. In a La Niha,
stronger than normal trade winds bring up cooler water from the ocean's depths, causing the
sea surface to be colder than normal. Although El Niho and La Nina return every 2 to 7 years,
the tropical Pacific can be thought of as neutral, or near normal, a majority of the time. In fact,
neutral years outnumber El Niho or La Niha years over 2 to 1.

How Ocean Temperatures Affect Florida's Climate

The jet stream is a fast moving ribbon of air that circles the globe several miles above the
ground. The jet stream is responsible for steering storms and fronts, driving the day-to-day
weather we all experience. In an El Niho winter, the warm surface waters of the Pacific
provide a source of heat and moisture that strengthens the jet stream, pulls it further south
and keeps it flowing west to east across the southern United States. The new position guides
winter storms into California and along the Gulf Coast. These storms provide abundant rain-
fall and cooler temperatures for Florida and the deep South. In La Nina winters, a weaker jet
stream strays to the north and meanders across the country. Fronts and storms do not make
it down to Florida as often and the winters are warmer and dryer than normal.

Through their relatively predictable influence on the climate of Florida and surrounding
states, El Niho and La Niha have important implications for agricultural production. El Niho
and La Nina influence yields of winter vegetables, some citrus species, sugarcane and field
corn in Florida, and several crops in the neighboring states. This booklet summarizes the
effects of El Niho and La Niha years on the climate of Florida and the Southeast, with








particular emphasis on effects that potentially impact agriculture and forestry. Maps of the
Southeast United States are presented that show how average seasonal temperature and
precipitation changes during El Niio and La Nina years. These maps depict these changes
for not only Florida, but also for neighboring states. To concentrate on Florida. graphs show
average monthly values of temperature, precipitation and other variables important to agricul-
ture. For convenience, the graphs are based on six of Florida's climate divisions (excluding
the Florida Keys) for selected weather variables, and on seven locations that have solar radia-
tion data for potential evapotranspiration and rainfall deficit. In addition, the graphs present
differences between El Niho and neutral years and between La Nina and neutral years to
highlight times of the year when these two conditions have the most impacts.

A word of caution is in order. This booklet shows averages for a number of past El Nino
and La Nina events. However, not all El Niio, neutral, or La Nina years are the same. A
particular event may not have the monthly averages shown in the graphs. Although the aver-
age of past years is a good indication of what future El Niho or La Nina years will be like. it is
not a precise prediction of what will happen in a specific year.


DATA AND METHODOLOGY


Defining El Niho and La Niia

The first step in the analysis is to classify each year between 1946 and 1997 as El Nino. La
Niha or neutral. There are many different ways to define an El Nino or La Niha. We use an
index developed by the Japan Meteorological Agency (JMA) that is based on sea surface
temperature anomalies (departures from monthly normals) averaged over an area of the eastern
Pacific between 40N and 4S and between 90W and 150"W. The index is smoothed with a
five-month running mean to isolate long term trends. The JMA categorizes an El Niho as at
least six consecutive months with averaged sea surface temperatures in the defined area at
least 0.90F (0.5C) higher than normal, including the months of October. November. and De-
cember. A La Niha (or cold phase) is defined the same way except for averaged sea surface
temperatures at least 0.90F below normal.

Each El Niho, La Niha or neutral year is defined as beginning in October and running
through September of the next calendar year. The year is defined in this manner to capture
the maturation of an El Niho or La Nina, which usually peak in December and January. and
their subsequent decay through the following summer. Each year from 1946 through 1997 is
classified as El Niio, La Niha, or neutral according to the JMA index (Table 1).

Maps of Temperature and Precipitation Anomalies

The climate data used in preparing the maps are from the 1998 release of the U.S. Histori-
cal Climate Network (USHCN) data set from the National Climatic Data Center (NCDC). The
stations were chosen for length of record, homogeneity, quality and spatial coverage.








particular emphasis on effects that potentially impact agriculture and forestry. Maps of the
Southeast United States are presented that show how average seasonal temperature and
precipitation changes during El Niio and La Nina years. These maps depict these changes
for not only Florida, but also for neighboring states. To concentrate on Florida. graphs show
average monthly values of temperature, precipitation and other variables important to agricul-
ture. For convenience, the graphs are based on six of Florida's climate divisions (excluding
the Florida Keys) for selected weather variables, and on seven locations that have solar radia-
tion data for potential evapotranspiration and rainfall deficit. In addition, the graphs present
differences between El Niho and neutral years and between La Nina and neutral years to
highlight times of the year when these two conditions have the most impacts.

A word of caution is in order. This booklet shows averages for a number of past El Nino
and La Nina events. However, not all El Niio, neutral, or La Nina years are the same. A
particular event may not have the monthly averages shown in the graphs. Although the aver-
age of past years is a good indication of what future El Niho or La Nina years will be like. it is
not a precise prediction of what will happen in a specific year.


DATA AND METHODOLOGY


Defining El Niho and La Niia

The first step in the analysis is to classify each year between 1946 and 1997 as El Nino. La
Niha or neutral. There are many different ways to define an El Nino or La Niha. We use an
index developed by the Japan Meteorological Agency (JMA) that is based on sea surface
temperature anomalies (departures from monthly normals) averaged over an area of the eastern
Pacific between 40N and 4S and between 90W and 150"W. The index is smoothed with a
five-month running mean to isolate long term trends. The JMA categorizes an El Niho as at
least six consecutive months with averaged sea surface temperatures in the defined area at
least 0.90F (0.5C) higher than normal, including the months of October. November. and De-
cember. A La Niha (or cold phase) is defined the same way except for averaged sea surface
temperatures at least 0.90F below normal.

Each El Niho, La Niha or neutral year is defined as beginning in October and running
through September of the next calendar year. The year is defined in this manner to capture
the maturation of an El Niho or La Nina, which usually peak in December and January. and
their subsequent decay through the following summer. Each year from 1946 through 1997 is
classified as El Niio, La Niha, or neutral according to the JMA index (Table 1).

Maps of Temperature and Precipitation Anomalies

The climate data used in preparing the maps are from the 1998 release of the U.S. Histori-
cal Climate Network (USHCN) data set from the National Climatic Data Center (NCDC). The
stations were chosen for length of record, homogeneity, quality and spatial coverage.








particular emphasis on effects that potentially impact agriculture and forestry. Maps of the
Southeast United States are presented that show how average seasonal temperature and
precipitation changes during El Niio and La Nina years. These maps depict these changes
for not only Florida, but also for neighboring states. To concentrate on Florida. graphs show
average monthly values of temperature, precipitation and other variables important to agricul-
ture. For convenience, the graphs are based on six of Florida's climate divisions (excluding
the Florida Keys) for selected weather variables, and on seven locations that have solar radia-
tion data for potential evapotranspiration and rainfall deficit. In addition, the graphs present
differences between El Niho and neutral years and between La Nina and neutral years to
highlight times of the year when these two conditions have the most impacts.

A word of caution is in order. This booklet shows averages for a number of past El Nino
and La Nina events. However, not all El Niio, neutral, or La Nina years are the same. A
particular event may not have the monthly averages shown in the graphs. Although the aver-
age of past years is a good indication of what future El Niho or La Nina years will be like. it is
not a precise prediction of what will happen in a specific year.


DATA AND METHODOLOGY


Defining El Niho and La Niia

The first step in the analysis is to classify each year between 1946 and 1997 as El Nino. La
Niha or neutral. There are many different ways to define an El Nino or La Niha. We use an
index developed by the Japan Meteorological Agency (JMA) that is based on sea surface
temperature anomalies (departures from monthly normals) averaged over an area of the eastern
Pacific between 40N and 4S and between 90W and 150"W. The index is smoothed with a
five-month running mean to isolate long term trends. The JMA categorizes an El Niho as at
least six consecutive months with averaged sea surface temperatures in the defined area at
least 0.90F (0.5C) higher than normal, including the months of October. November. and De-
cember. A La Niha (or cold phase) is defined the same way except for averaged sea surface
temperatures at least 0.90F below normal.

Each El Niho, La Niha or neutral year is defined as beginning in October and running
through September of the next calendar year. The year is defined in this manner to capture
the maturation of an El Niho or La Nina, which usually peak in December and January. and
their subsequent decay through the following summer. Each year from 1946 through 1997 is
classified as El Niio, La Niha, or neutral according to the JMA index (Table 1).

Maps of Temperature and Precipitation Anomalies

The climate data used in preparing the maps are from the 1998 release of the U.S. Histori-
cal Climate Network (USHCN) data set from the National Climatic Data Center (NCDC). The
stations were chosen for length of record, homogeneity, quality and spatial coverage.








The data were quality controlled by NCDC, then adjusted for a number of biases including
time of observation, station relocation/instrument change, missing data, etc. The result is a
homogeneous monthly data set suited for the study of long term climate trends. For the
purposes of this study, only observations from 1946 through 1997 were used. Data quality
and missing values were a concern for earlier observations. Also, each station must have
less than 5% missing values during this time period in order to be considered.

The maps were prepared using the USHCN station data for the Southeast United States.
For each station, seasonal averages of mean temperature and total precipitation were com-
puted for warm, cold, and neutral years. Anomalies, or departures from the neutral condi-
tions, were found by subtracting the neutral seasonal average from the El Niho or La Niha
seasonal average. When plotted on a map, these anomalies show the areas of Florida and
the Southeast that are most affected by El Niho and La Niha.

Graphs of Monthly Average Climate Statistics

Monthly average rainfall and temperatures were calculated from daily data from five weather
stations in each climate division in Florida (except for Division 7, the Florida Keys) for prepa-
ration of the graphs. We used available weather stations with at least 95% complete records
from 1948 to 1995. Where more than five stations were available in a climate division, we
selected those that gave the best spatial coverage. Heating degree-days were calculated
from hourly temperatures interpolated from the daily minima and maxima. The best methods
to calculate reference evapotranspiration require solar radiation data. Reliable solar radiation
data were available for enough years (1961-1990) at only a few locations in and around
Florida. Graphs of reference evapotranspiration and precipitation deficit were derived for
seven locations.

To compute the graphs, monthly values for each climate division were calculated as an
average of the five stations, weighted by the number of days of available data from each
station to account for possible unequal numbers of missing data for the different stations. For
each calendar month, the average was calculated separately for the El Niho, neutral, and La
Niha years.









Table 1: El Niro, La Niha and Neutral Years


7/-Av


! I


70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96979899


I


3


2


1


0('1 C)

1


El Nifo Neutral La Niri

1951 1946 1978 1949
1957 1947 1979 1954
1963 1948 1980 1955
1965 1950 1981 1956
1969 1952 1983 1964
1972 1953 1984 1967
1976 1958 1985 1970
1982 1959 1989 1971
1986 1960 1990 1973
1987 1961 1992 1975
1991 1962 1993 1988
1997 1966 1994 \C19
1aJ9 1968 1995
1974 1996
1977 1997


Pacific Sea Surface Temperature Anomalies (JMA Index)
Pacific Sea Surface Temperature Anomalies (JMA Index)









PRECIPITATION


Inadequate water availability is probably the most important factor limiting crop production
in the absence of irrigation. Excess water can affect crops adversely by damaging root sys-
tems, leaching plant nutrients, favoring development of some diseases, and sometimes de-
laying field operations.

One of the most striking impacts is the increase in average winter (November to March)
rainfall during El Nino years, and the decrease in La Nina years. Florida is particularly vulner-
able, with an excess of over 30% of the normal seasonal total across much of the state during
an El Niho winter. La Niha has the opposite effect, with deficits of 10% to 30% lasting from fall
through winter and spring. The monthly deviation from normal due to either El Niho or La Nina
conditions exceeds 30% in all of Florida's climate divisions, and 50% in the southern
peninsula (Divisions 4 and 5) during some part of the year. The excess winter rainfall in
El Niho years can affect yields of winter-harvested vegetables adversely.


Flood damage assessment of mango tree at Homestead, Florida as a result of tropical
storm Gordon in 1995. Picture was taken by Dr. Johnathan H. Crane, University of
Florida/IFAS Tropical Research and Education Center, Homestead, Florida.






El Nifo Seasonal Precipitation
Anomalies


+40


+30


+20
P
E
+10 R
C
-10 E
N
T
-20


-30


-40


SDRY I


S (r A


6WN-V -----^ -Fe


I S U M ME R (u ne uy Aug.)






La Nifia Seasonal Precipitation
Anomalies


+40


+30


+20


+10


-10


-20


-30


-40


SR NG (mr. Aprl Ma)


M A


FALL (Oct., Nov., Dec
Uia ILlIg-^


I DRY )


WINTE (Dec., a Fb






Monthly Rainfall Amount
8
(Inches) 6

4

2


Oct Dec Feb Apr Jun Aug


0 -..--.-.....--I, -
Oct Dec Feb Apr Jun Aug
Month


-A- El Nitio
-0- Neutral
-- La Niia


!6 0 /-J
Oct Dec Feb Apr Jun Aug


8

6

4 --4

2 V/

0Oct Dec Feb Apr Jun Aug
Month


Oct Dec Feb Apr Jun Aug





90% -

60%

30%

0%

-30%

-60%
Oct Dec Feb Apr Jun Aug
90%

60%

30%

0%

-30-%

-60%
Oct Dec Feb Apr Jun Aug
90%

60%

30%



-30%

-60%
Oct Dec Feb Apr Jun Aug
Month


Monthly Rainfall Anomalies

(Percent)


-A- El Niio
-W- La Nifia


90%

60%

30%

0%

-30%

-60%
00
90%

60%

30%

0%

-30%

-60%

90%

60%

30%

0%

-30%

-60%


Oct Dec


Feb Apr Jun Aug


-!



OA



Oct Dec Feb Apr Jun Aug



**- \ ^

-vv^


Oct Dec


Feb Apr Jun Aug
Month








EVAPORATION AND RAINFALL DEFICIT

Evaporative demand, or potential evapotranspiration, influences the amount of water plants
need each day, and the amount of stress that plants experience when water supply is inad-
equate. Reference evapotranspiration (ET) is the maximum rate of evaporation from a short,
growing, well-watered grass under given air temperature, humidity, wind and solar radiation.

Under rain fed production conditions, precipitation represents the supply of water, and
reference evapotranspiration the upper limit of demand for water. As the graph below indi-
cates, precipitation surplus or deficit is the difference between the two. A surplus occurs
when rainfall exceeds reference ET. Rainfall less than reference ET indicates a deficit Pre-
cipitation deficit is a useful indicator of the potential for water stress in crops, and therefore the
need for supplemental irrigation. However, actual water use and irrigation requirements are
considerably more complicated, depending on characteristics of the crop and soil, and on the
timing of rainfall.


Oct Dec Feb Apr
Month


Jun Aug


In most of the state, reference ET is higher than normal in La Niha years and lower than
normal in El Niho years from November to March. However, the difference seldom exceeds
two-tenths of an inch. The critical period for rainfall deficit is from March to May in most of the
state. The deficit is likely to be more severe in April in northern Florida, and in March in
southern Florida during La Niha years. Rainfall deficit is generally less (equivalently, surplus
is greater) in El Niho years from January to March. The impact of El Niho and La Niia on
rainfall deficit are less consistent in the summer months.
















Oct Dec Feb Apr Jun Aug


Reference Evapotranspiration

(Inches)

-A- El Niflo
-0- Neutral
-V- La Nifia


Oct Dec Feb


Apr Jun Aug


6

5

4


6

5

4

3

2
4


Oct Dec Feb Apr Jun Aug Oct Dec Feb Apr Jun Aug
Month Month


Oct Dec Feb Apr Jun Aug
-w
-V



/ -


Oct Dec Feb Apr Jun Aug
Month






Reference Evapotranspiration
Anomalies


0.2

0.0


0.2-

0.0-


-0. D F

Oct Dec Feb Apr Jun Aug


0.2

0.0


-0.2-


Oct Dec Feb Apr Jun Aug
Month


0.2+


-0.2+


-0.4 -
Oct Dec Feb Apr Jun Aug
Month


0.2

0.0


0.2

0. 0


Ae-


Mon th


(Inches)

-A- El Nifio
-V- La Nifia


, Ax, A el-T







5.0

2.5

0.0

-2.5

-5.0


5.0

2.5

0.0

-2.5

-5.0


5.0

2.5

0.0

-2.5

-5.0


Rainfall Surplus or Deficit
(Inches, positive = surplus,
negative = deficit)

-A- El Nifno
-0- Neutral
-- La Nifia


Oct Dec Feb Apr Jun Aug


-5.0


-5.0


Oct Dec Feb Apr Jun Aug
Month


Oct Dec Feb Apr Jun Aug




-





Oct Dec Feb Apr Jun Aug
Month


Oct Dec Feb Apr Jun Aug
Month


Alt








TEMPERATURE


Crops and animals are affected adversely when temperatures are either too hot or too
cold. The idealized graph below shows how yields of an irrigated crop might respond to
season-average temperatures. Different crops have different optimal temperatures. Because
mammals regulate their body temperature, they tend to have wider optimal temperature ranges
than crops, but experience heat stress at temperatures lower than many crops. Temperature
also influences the rates of biological processes, and therefore the timing of flowering and
harvest. Temperatures above or below critical target values also influence energy costs as-
sociated with heating or cooling. The section on degree-days discusses these effects on crop
development and livestock heat stress.




1 100% -
E
| 75% -
0
E 50%-
S/ OPTIMUM
C 25%-- RANGE

>_ 0%
Temperature


Changes in average daily maximum or minimum temperatures associated with El Niio or La
Niha conditions are much smaller than the differences between seasons. However, depar-
tures from normal are significant in Florida, especially during winter months. Florida and the
Gulf Coast can expect to see average temperatures 20F to 30F below normal during El Niho
years. La Niha has the opposite effect, with temperatures 20F to 40F above normal during
winter months. La Niia's effect on temperature is more pronounced in north Florida, Ala-
bama, and Mississippi.

Monthly departures from normal for Florida's climate divisions show the same trends, with
greatest departures in January and February. In the winter and spring months (December to
April), average daily maximum temperatures are higher than normal in La Niia years, and
lower than normal in El Niho years through most of the state. The effect of La Niia on winter
temperatures generally increases as we move north within the state. The effects of El Niho
and La Nifa on winter average daily minimum temperatures is not as strong. In southern
Florida, however, average daily minimum temperatures in the summer (June to August) tend
to be lower than normal in La Niia years. Lower nighttime temperatures may benefit growth
and yield of some crops.












+1.50 +2.70


+1.25 +2.25
D
E
G +1.00 +1.80
R
E +0.75 +1.35
E
S
+0.50 +0.90
C
E
E -0.50 -0.90
L
S
I -0.75 -1.35
U
S
-1.00 -1.80


-1.25 _-2.25


I COOL


El Nifo Seasonal Temperature
Anomalies






D
E

R NO EFFECT
E
E
S

F
A
H
R
E
N
H
E
T
T


I SG (


ec., Jan., F;eb.)l


j SUMMER (JunejulyAug]


.1






La Ninia Seasonal Temperature
Anomalies


-MUTM

+1.50 +2.70


+1.25 +2.25 D
E
E G
E
S+1.00 +1.80 R
G
E
R E
E
E +0.75 +1.35 S
E
S
+0.50- +0.90 F
C A
C
H
S-0.50 -0.90 R
L E
S N
I -0.75 --1.35 H
U
U E
S
-1.00 -1.80 I
T

-1.25 -2.25


I COOL


F A LL =SDc


S P IN (rAim


SUMMER (June, JulA
















Oct Dec Feb Apr Jun Aug



/"


Oct Dec Feb Apr Jun Aug


Oct Dec Feb Apr Jun Aug
Month


Average Daily Minimum and 85
Maximum Temperatures

(F) 6a

55

45


Oct Dec Feb Apr Jun Aug


-A- El Niio
-0- Neutral
-W- La Nifia


45

6 35
5 Oct Dec Feb Apr Jun Aug

85

75

65
55
45
35 ^--------
35Oct Dec Feb Apr Jun Aug
Month


~rr






4

2

0

-2--

-4
Oct Dec Feb Apr Jun Aug

4

2

0

-2

-4
Oct Dec Feb Apr Jun Aug


Oct Dec Feb Apr Jun Aiin
Mon t h


Average Daily Maximum 4
Temperature Anomalies
2
(F)


-2


Oct Dec Feb Apr Jun Aug


68


-A- El Niflo
-V- La Nifia


Oct Dec Feb Apr Jun Aug





t A\ XTN


-2

-4
O.4; ------ -F-- Apr--A
Oct Dec Ieh Apr Jun Aug
Mkon t h


r


.






Average Daily Minimum 4
Temperature Anomalies


Oct Dec Feb Apr Jun Aug


Dec Feb Apr Jun Aug


Oct Dec Feb Apr Jun Aug
Month


Oct Dec Feb Apr Jun Aug
Month


:I


-4-1
Oct









GROWING AND HEAT STRESS DEGREE-DAYS

Degree-days represent the accumulation or summation through time of temperatures above
some base temperature. Degree-days above a base temperature of 50F (often called "grow-
ing degree days") are used to estimate the time to flowering or maturity of several field crops.
Higher numbers of degree-days in a given month favor earlier flowering and maturity. El Niio
and La Nina influence growing degree days primarily in the winter (December through Febru-
ary). For winter crops that are insensitive to day length, development is likely to be about 5-
10% faster than normal in December to February of La Niia years, and about 10-15% slower
in El Niho years in South Florida (Division 5). Although the effect increases to the north and
west (up to 35% increase in January of La Nina in Division 1), relatively few annual crops are
grown north of Division 5 in the winter.











Growing degree-days


Rates of weight gain in cattle and hogs, and milk production, are reduced during periods
when temperatures exceed 770. Degree-days above 770F ("heat stress degree-days") is a
useful indicator of heat stress in livestock. Actual losses, however, depend on other factors,
such as whether nighttime temperatures are low enough to allow animals to recover from
stress. Monthly heat stress degree-days tend to be slightly lower in the spring (March to May)
and higher in the summer during El Niho years. La Niha reduces heat stress degree-days in
June and July. However, these differences are small compared to the total average heat
stress degree-days in the spring and summer.



o 100%
o,""


S3 75%

E E 50%

0 25%
ra)
w- 0
>, -77F
e Temperature







50OF base


1000

750

500

250

0

1000

750

500

250

0

1000

750

500

250

0


770F base


770F base


Oct Dec Feb Apr Jun Aug


Oct Dec Feb Apr Jun Aug
Month


Degree-Days 1000

(50 F and 77oF 750
base temperatures)

250
250


n.


1000

750


-A- El Niio
-0- Neutral
-V- La Niia


S Oct Dec Feb Apr Jun Aug


250 -


Oct Dec Feb Apr Jun Aug

1000 50F base / ,

750

500

250 770F base

0
Oct Dec Feb Apr Jun Aug
Month


50F base


50oF base





- 770F base


/


50oF base



/770
770C I


K







Growing Degree-Day
Anomalies

(Percent, 50TF base)


45%

30%

15%

0';

-15%

-30%


45%

30%

15%

0%

-15%

-30%


45';

30',

S15%



-15%

-3()0',


Oct Dec Feb Apr Jun Aug











Oct Dec Feb Apr Jun Aug
Oct Dec Feb Apr Jun Aug











Octl Dc Ich Apr Jun Aug
Mo, It h


Oct Dec Feb Apr Jun Augi
Month






15

5




-5
-15 -






5

5 -1




-25
Oct Dec Feb Apr Jun Aug







15M----
15
-5






-15 '\
-25
Oct Dec Feb Apr Jun Aug
15Month



-5





-25
Oct Dec Feb Apr Jun Aug
Month


Heat Stress Degree-Day
Anomalies

(77oF base)


Oct Dec Feb Apr Jun Aug











Oct Dec Feb Apr Jun Aug


Month









HURRICANES

Every summer and autumn, hurricanes become a threat to Florida. With their violent
winds and torrential rains, hurricanes have the potential to cause great damage to Florida's
agriculture and forestry. However, the threat that hurricanes pose to the United States and
Florida is not the same every year, due to the influences of El Niho and La Niia.

When El Niho conditions are present in the eastern tropical Pacific Ocean, upper level
winds over the Atlantic Basin become unfavorable for tropical cyclone development. With
fewer hurricanes developing, there is less threat for hurricane strikes in the U.S. Conversely.
La Niia conditions favor hurricane development in the Atlantic Basin, allowing for more storms
that can potentially strike the United States.

The probabilities of hurricanes making landfall on the U.S. during El Niho, neutral, and La
Niha years can be assessed by studying historical hurricane records. The graph shows the
probability of the minimum number of hurricanes hitting the United States during any hurri-
cane season, based on the conditions in the eastern tropical Pacific. The figure shows that
the chance of at least two hurricanes hitting the U.S. during El Niho conditions is 28%. Mean-
while, the probabilities of 2 landfalling hurricanes during neutral and La Niia years are 48;r.
and 66%, respectively. Therefore, the chances of 2 landfalls during a La Nina year are three
times greater than during an El Niho year. The changes in probability can be determined for
other numbers of landfalls from the figure.



El Nino
Neutral
La Nifa U.S. Landfalling Hurricane Probabilities







S60 -
10



S40 -


20

0 . .
0 1 2 3 4 5 6 7
Number of U.S. Hurricanes (or more)








FOREST FIRES


As with agriculture or any other activity that is highly dependent on the weather, forestry
can benefit from the knowledge of climate patterns associated with El Niho and La Nina. In
particular, the lack of rainfall during La Niha winters can cause an increased risk of fires in the
following spring and summer. La Niia winters in Florida are characterized by below normal
rainfall beginning in the fall and lasting through spring. This extended dry period runs into
April, historically one of the driest months of the year for all ENSO phases. This sets the stage
for extremely dry soil and forests, highly vulnerable to the threat of fire during the late spring/
summer peak fire period.

An examination of historical fire records shows that the number of acres burned in Florida
each year is highly correlated to El Niho and La Niia. The study shows an increase in the
number of acres burned during La Niha years, especially in southern Florida. In the limited
data that was examined (1981-1998), La Nina years averaged over 500,000 acres burned in
Florida while the neutral average is around 200,000 acres. The wet El Niho winters seem to
suppress forest fires. The signal was most apparent for strong El Niho and La Nina events.
The western Panhandle of Florida did not seem to be affected, as it receives much more
rainfall in a typical year than southern Florida.


Fire Threat in La Nifia Spring







Extreme

Well Above Normal

Above Normal r-


Normal to Above


e Normal =








FURTHER READING


Data Sources and Methods:

Earthlnfo. 1996. Database Guide for Earthlnfo CD NCDC Summary of the Day.
Earthlnfo, Inc., Boulder, CO, USA.

Ephrath, J. E., J. Goudriaan, and A. Marani. 1996. Modelling diurnal patterns of
Air temperature, radiation, wind speed and relative humidity by equations from
Daily characteristics. Agricultural Systems 51:1-17.

Karl, T. R., C. N. Williams, Jr., F. T. Quinlan, and T. A. Boden. 1990. United States
Historical Climatology Network (HCN) serial temperature and precipitation
Data. 387 PP. Environmental Science Division, Publication No. 3404. Carbon
Dioxide Information and Analysis Center, Oak Ridge National Laboratory.
Oak Ridge, TN, USA.

NREL. 1992. User's Manual, National Solar Radiation Data Base (1961-1990).
National Renewable Energy Laboratory, Boulder, CO, USA.


General Information about El Niho and La Niha:

Aceituna, P. 1993. El Niho, the Southern Oscillation and ENSO: Confusing names
For a complex ocean-atmosphere interaction. Bulletin of the American
Meteorological Society 73:483-485.

Bigg, G. R. 1990. El Niho and the Southern Oscillation. Weather 45:2-8.

Glantz, M. H. 1996. Currents of Change: El Niiio's Impact on Climate and Society.
Cambridge University Press, Cambridge, U.K.

Wallace, J. M. and S. Vogel. 1994. El Ninfo and Climate Prediction. Reports to the
Nation on our Changing Planet. University Corporation for Atmospheric
Research.


Influences on Florida's Agriculture:

Hansen, J. W., A. Irmak, and J. W. Jones. 1999. El Niho-Southern Oscillation
influences on Florida crop yields. Soil and Crop Science Society of Florida
Proceedings 57 (in press).

Hansen, J. W., J. W. Jones, C. F. Kiker, and A. H. Hodges. 1999. El Niho-Southern
Oscillation impacts on winter vegetable production in Florida. Journal of
Climate 12:92-102.








Hansen, J. W., A. W. Hodges, and J. W. Jones. 1989. ENSO influences on agriculture
In the southeastern United States. Journal of Climate 11:404-411.


Influences on Florida's Climate:

Bove, M. C., J. B. Elsner, C. W. Landsea, X. Niu, and J. J. O'Brien. 1997. Effect of
El Niho on U.S. landfalling hurricanes, revisited. Bulletin of the American
Meterological Society 79:2477-2482.

Green, P. M., D. M. Legler, C. J. Miranda, and J. J. O'Brien. 1997. The North
American Climate Patterns Associated with the El Niho-Southern Oscillation.
COAPS Project Report Series 97-1. Center for Ocean-Atmospheric Prediction
Studies, The Florida State University, Tallahassee, FL, USA.

Sittel, M. 1994. Differences in the Means of ENSO Extremes for Temperature and
Precipitation in the United States. COAPS Technical Report 94-2.


WEB SITES:

Florida Consortium:

Florida State University/COAPS: www.coaps.fsu.edu
University of Florida/IFAS: www.ifas.ufl.edu
University of Miami/RSMAS: www.rsmas.miami.edu

Climate Forecasts:

Climate Prediction Center: www.cpc.ncep.noaa.gov

El Nino and La Ninia Information:

Pacific Marine Environmental Laboratory: www.pmel.noaa.gov
Climate Diagnostics Center: www.cdc.noaa.gov
NOAA Office of Global Programs: www.ogp.noaa.gov/enso

Weather and Climate Information:

National Climatic Data Center: www.ncdc.gov
Southeast Regional Climate Center: water.dnr.state.sc.us
Florida Climate Center: www.coaps.fsu.edu/climate center
Florida Automated Weather Network: fawn.ifas.ufl.edu





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COT ON


CORN


FORESTS


SEAFOOD


WATERMELON


TURF GRASS



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ORNAMENTALS


STRAWBERRIES


TOMATOES


SEAFOOD


-TROPICAL FRUIT




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