Effects of Global Warming on Drought Frequency and Duration in the Northeast United States

Chaochao Gao and Alan Robock Department of Environmental Sciences, Rutgers University, New Brunswick, NJ 08901

Submitted to the Journal of Hydrometeorology October, 2003

Corresponding Author: Alan Robock Department of Environmental Sciences Rutgers University 14 College Farm Road New Brunswick, NJ 08901 Phone: (732) 932-9478 Fax: (732) 932-8644 E-mail: robock@envsci.rutgers.edu

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Abstract

Over the past century, the northeast United States experienced several major droughts,

with great economic damage as a consequence. We use the Standardized Precipitation Index to

study the change of drought conditions in the northeast United States, using observations and

simulations from eight state-of-the-art general circulation models for the period 1901 to 2050.

We separated the droughts into two different time scales, 3 months and 12 months, and three

different severities, moderate, severe, and extreme. While the models behave quite differently

from each other, the ensemble averages of the model simulations showed decreases in the

frequencies of droughts in the future. The models project the frequencies of 3-month moderate,

severe, and extreme droughts to decrease by about 12%, 20%, and 5% respectively for the first

quarter of the 21st century and 13%, 19%, and 11% for the second quarter compared with the

20th century; and 12-month droughts to decrease by 2%, 14%, and 7% during the first quarter

and 18.5%, 36%, and 37% during the second quarter of this century. While only the 12-month

severe and extreme decreases are statistically significant at the 80% level, and none of the other

decreases is statistically significant, the results are consistent with projected precipitation

increases, and serve as valuable guidance for water availability planning for the future. This

study uses only a precipitation-based index and does not account for potential changes in

evaporation. As climate models improve, this study should be repeated analyzing soil moisture

simulated by the models.

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1. Introduction

Over the last century New Jersey has experienced several major droughts, for example

during the periods 1908-1912, 1916-1920, 1923-1927, 1927-1933, 1964-1968, 1980-1984, and

2001-2002. This is representative of the situation in the northeastern United States. These

droughts have a significant impact on the availability of water for agricultural, industrial,

domestic, natural ecosystem, and recreational uses. As the population grows during the 21st

century and water demand increases, planning for the water supply infrastructure will depend on

whether droughts become more or less frequent and shorter or longer during this period. In this

paper we investigate this question by examining simulations of future climate by eight state-of-

the-art atmosphere-ocean coupled general circulation models (GCMs).

Drought is defined as a deficiency of precipitation over an extended period of usually a

season or more. Drought indices such as the widely-used Palmer Drought Severity Index have

been use to detect and monitor droughts with limited success. Recently Keyantash (2002)

evaluated the existing drought indices and recommended a relatively new drought index – the

Standardized Precipitation Index (SPI) – as one of the best estimators of drought. Besides its

high reliability, the SPI is simpler and more temporally flexible, which allows its application for

water resources on different timescales. Hayes (1999) used the SPI to monitor the 1996 drought.

Edwards et al. (1997) also used it to analyze the history of drought in the United States.

Therefore this paper will use the SPI to detect and monitor changes of drought for the next

several decades compared with the last century.

While drought also has an evaporation component, and climate model simulations of

actual soil moisture might seem like the best way to evaluate future drought, climate model

simulations of soil moisture have not yet reached a point that they can be considered reliable

(Robock et al. 1998, Srinivasan et al. 2000). Although summer desiccation is predicted with

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warming during the current century, these predictions are made with simple evaporation

parameterizations that may overestimate evaporation and not properly include the effects of

vegetation (Qu et al. 1998). Therefore, we focus on a precipitation-based index here.

Because of our interest in New Jersey droughts, we study a region of the northeast United

States, 60-83°W, 30-50°N, centered on New Jersey (Figure 1) of a scale likely to capture the

patterns in New Jersey, without being too small and noisy. Average precipitation for the period

1961-1990 for this region runs from less than 2.0 mm/day in the northwest to more than 4.0

mm/day in the northeast. New Jersey average precipitation is almost 3.0 mm/day (Hulme, 1996).

2. Standardized Precipitation Index (SPI) methodology

The SPI for a given period of time is defined as the difference of precipitation from the

mean divided by the standard deviation (McKee et al., 1993). Since the precipitation is usually

not normally distributed for time scales of 12 months or less, we calculated the SPI by first

fitting a gamma probability density function to the monthly precipitation totals for the desired

time series; then the cumulative probability of a particular event for the given time scale was

determined based on the resulting parameters, which is then converted to the standard normal

random variable – the SPI value (Edwards et al., 1997). Figure 2 shows the observed 3-month

SPI values for the study region (Figure 1). The definitions of drought intensity used by both

McKee et al. (1995) and Agnew (2000) are shown in Table 1. We use the latter in this study,

since it is based on probability classes (5%, 10% and 20% for moderate, severe and extreme

droughts, respectively) rather than magnitude of the SPI.

A moderate drought event is defined for each time scale as a period in which the SPI is

continuously negative and the SPI reaches -0.85 or less. The drought begins when the SPI first

goes below zero and ends when the SPI becomes positive again. Severe and extreme droughts

are defined the same way for their SPI values.

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3. Data and methods

To study drought, we used monthly precipitation simulations from eight state-of-the-art

GCMs (Table 2) for the period 1901 to 2050. The models were all run with the IS92a

anthropogenic forcing scenario, one of the standard anthropogenic greenhouse gas and sulfate

aerosol forcings used for many climate model intercomparisons (IPCC, 1998). Output from the

GFDL experiments was obtained from GFDL website (http://www.gfdl.noaa.gov); outputs for

the rest of the experiments were extracted from the Data Distribution Center of the

Intergovernmental Panel for Climate Change data. For precipitation observations, we used the

guwld23-monthly climatological precipitation dataset developed by the Climate Research Unit of

University of East Anglia (Hulme, 1998). As observations are only available over land, time

series of both model outputs and observations were obtained by taking the land-area mean of the

study region (60-83°W, 30-50°N, Figure 1).

We used two time scales, 3-month and 12-month SPI, as the short-term (or seasonal) and

intermediate-term drought indices. The calculation of the 3-month SPI for Jan 1901, for example,

used the precipitation total of Nov 1900 through Jan 1901. Likewise, the 12-month SPI for Jan

1901 was calculated based on the precipitation total of Feb 1900 through Jan 1901.

4. Results

a. Changes of drought frequency and intensity

1) ENSEMBLE AVERAGE RESULTS

The frequencies of 3-month and 12-month droughts were calculated from each GCM

experiment for the period of January 1901 through December 2050. We counted the number of

drought events for each 25-year interval. Figure 3 shows the 3-month drought frequencies for

each of the eight models (ensemble averages if the model has several different runs) and also the

averaged values for all models. We can see that the model outputs are different from each other.

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For instance, the 3-month moderate drought frequency changes by -2.7 ± 3.2 (25 yr)-1 and -3.1 ±

3.0 (25 yr)-1across the models for the comparisons for the 2001-2025 and 2025-2050 periods to

the average of last century, respectively (see Table 1 in Appendix for the other droughts).

However, we can still obtain some general conclusions based on the ensemble average results

from the eight models as follows:

• The frequencies indicated by models are generally lower than the observations.

• The average moderate drought frequency (with units (25 yr)-1, same below) decreases from

about 21.4 during the last century to 18.8 (-12%) and 18.6 (-13%) for the periods of 2001-

2025 and 2026-2050, respectively.

• The average severe drought frequency decreases from about 14.1 during the last century to

11.3 (-20%) and 11.4 (-19%) for the two periods of this century.

• The average extreme drought frequency also decreases from 8.2 to 7.8 (-5%) and 7.3 (-11%),

respectively.

Figure 4 shows the change of three types of drought frequency for the same 8 models for

an intermediate time scale of 12 months. Again different models show different trends of

frequency change (see Table 1 in Appendix). Based on the average values, we can see that:

• The average frequencies of moderate, severe, and extreme droughts for a 25-year interval

were about 6.5, 4.7, and 3 (25 yr)-1 during the last century.

• The frequencies of moderate, severe and extreme droughts decrease by about 0.13 (-2%),

0.66 (-14%), and 0.22 (-7%) separately from last century to the first 25 years of this century.

• For the period of 2026-2050, the frequencies of moderate, severe, and extreme droughts

decrease about 1.2 (-18.5%), 1.7 (-36%) and 1.1 (-37%) separately.

In summary, the ensemble averages of eight models show that in the first half of the 21st

century all the three categories of drought events (both 3-month and 12-month) will occur less

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frequently; there are relatively more decreases during the second 25-year period, especially for

the 12 month droughts. Table 1 in the Appendix lists the values of frequencies shown in Figures

3 and 4.

2) MODELS’ NATURAL VARIABILITY

We saw above that models simulated decreases of drought frequency during the first half

of this century. But the question remains whether the decreases are caused by anthropogenic

forcing, or could be due to natural variability. To estimate the role that natural variability is

playing in this decrease of drought frequency, we calculated the probability distributions of

drought frequencies of a superensemble model control run. We first calculated the drought

frequencies for 25-year intervals for each model. We then combined these results to give us a

1675-year period of control run (see Table 2). The resulting probability distributions are shown

in Figure 5. Given the limited number of samples, we can see that the frequencies are

approximately normally distributed. The mean frequency and standard deviation for each case of

drought are listed in Table 4. Also listed in Table 4 are the estimated probabilities of model

average frequency changes being less than the average simulated frequencies by chance. As can

be seen, the probabilities range from 17% to 64% although most of them are about 20-40%.

Therefore, by taking into account of the possibility of frequency changes caused by

natural variability (assuming that models’ natural variation can represent the real world’s

variation), the confidence we have when saying the drought frequency will decrease for the first

half of this century is only 60-80%. According to the classic null hypothesis significance testing,

this can be denoted as “not statistically significant.” However, this classical test can be

misleading (Nicholls, 2001), and by reporting our results and the corresponding confidence

intervals we are pointing out possible phenomena that will occur in the future and hope this will

lead to more advanced or sophisticated studies.

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b. Changes of drought duration

Based on the definition by McKee et al. (1993), we define an event as a drought when the

SPI reaches a certain level (i.e., -0.84 for moderate, -1.28 for severe and -1.65 for extreme

droughts) or less. This drought begins when the SPI first goes negative and ends when the SPI

goes back to 0 or above.

Figure 6 shows time series of the mean duration of the eight GCMs, for the all three

categories of 3-month droughts. This figure essentially shows that there is less variation among

the model results (except NCAR1) in the case of mean duration than of frequency. The figure

also shows that drought duration ranges from about 7 months to 18 months from moderate to

severe intensity. There are no significant changes with time. The ensemble average of model

outputs shows slight changes from 7.4 to 7.5 months (+1%) and 7.0 (-5%) for the first two

quarters of this century for moderate drought; about 6% and 4% increases for the severe droughts

and around 8% decrease and 1% increase separately for the extreme events. In all the three cases

the observed durations of drought events are generally less than what are indicated by models;

observations also indicate a large decrease of drought duration from the first quarter of last

century to the rest of that century.

Figure 6 is a graph of time series of mean duration for 12-month droughts. Similarly the

duration is larger for more intense droughts, from about 25 months for moderate drought to 35

months for severe ones to around 45months for extreme events. Again the drought durations

given by models are generally longer than observations and the difference are even larger.

Models show a larger variation among 12-month drought durations as compared to those of the

3-month droughts. The ensemble averages drop slightly from the last century to the first quarter

of this century and then increase back to the mean durations of last century for all the three cases.

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5. Conclusions

In this study we used the standardize precipitation index to study drought frequency,

intensity, and duration changes from the last century to the first half of this century in the

Northeast of the United States. The ensemble averages the eight recent GCM results indicate

that all of the categories of droughts will occur less frequently in the first half this century,

especially the second quarter, 2026-2050. No significant changes of drought intensity were

found, except for a decrease of the 12-month droughts during 2026-2050. The duration stays

almost the same for all the six different classes of droughts.

There are some differences between the model results and observations, which we think

is related to the model’s incapability of reproducing the precipitation accurately, since the quality

of SPI depends on the quality of the data that produce it. While the models we used are the latest

output currently available to the impacts community, new models are currently being developed

by several modeling groups around the world, and our same analysis should be repeated

periodically. In particular, most of the models used in this study used simple land surface

schemes that do not accurately simulate evapotranspiration or soil moisture (Srinivasan et al.

2000). Models which more accurately simulate precipitation and land surface processes may

produce different results.

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Acknowledgments. We thank Katie Hirschboeck and David Robinson for valuable

comments on drought indices, Georgiy L. Stenchikov for valuable suggestions on the analysis,

NOAA’s Geophysical Fluid Dynamics Laboratory and the Data Distribution Center of the

Intergovernmental Panel for Climate Change for model outputs, and the Climatic Research Unit

(CRU) for precipitation data. We also thank the modelers for developing the models, conducting

the experiments and providing the output to the scientific community, and CRU for collecting,

analyzing, and providing the precipitation data. Supported by contract SR-02-082 from the New

Jersey Department of Environmental Protection.

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References

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in the United States. 77th AMS Annual Meeting, Long Beach, CA, 129-139.

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Comparison of observations with HadCM2 simulations. Geophys. Res. Lett., 25, 3379-3382.

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Report. IPCC Technical Paper II, WMO/UNEP, Geneva, 47pp.

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Keyantash, J., and J. A. Dracup, 2002: The quantification of drought: An evaluation of drought

indices. Bull. Amer. Meteor. Soc., 83, 1167-1180.

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duration to time scales. Preprints, Eighth Conf. on Applied Climatology, Anaheim, CA,

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Table 1. Classification of droughts.

SPI value McKee et al. (1995)

drought classes SPI value Agnew (2000) drought classes

< 0 Mild drought > -0.84 No drought < -1.0 Moderate drought < -0.84 Moderate drought < -1.5 Severe drought < -1.28 Severe drought < -2.0 Extreme drought < -1.65 Extreme drought

Table 2. List of GCMs experiments and the corresponding resolutions and references.

Institution_Model Reference Number of ensemble

experimentsPeriod

Length of control run (yr)

Resolution

GFDL_R30c Knutson et al. (1999) 3 1901-2050 400 R30, 96×72 MPI_ECHAM4 Stendel et al. (2000) 1 1901-2050 200 T42, 128×64 NCAR_NCAR1 Washington et al. (1996) 1 1901-2035 125 R15, 48×40 UKMO_HADCM Gordon et al. (1998) 3 1901-2050 200 R30, 96×73 CCCma_CGCM1 Flato et al. (2000) 3 1901-2050 200 T32, 96×48 CCSR_NIES Emori et al. (1999) 1 1901-2050 200 T21, 64×32 CSIRO_Mk2 Gordon et al. (1997) 1 1901-2050 200 R21, 64×56 GISS Hansen et al. (1998) 3 1951-2050 150 72×46

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Table 3. Average frequencies (per 25 yr) of 20th century droughts, changes during the first two

quarters of 21st century, and mean (µ) and standard deviation (σ) of frequency changes across

the models for the 6 classes of drought events. Ī is the average drought frequency during the

20th century; ∆N1, ∆N2 are the frequency changes from the 20th century to the period of 2001-

2025 and 2026-2050, respectively.

3-month moderate 3-month severe 3-month extreme Model Ī ∆N1 ∆N2 Ī ∆N1 ∆N2 Ī ∆N1 ∆N2

CCCma 19.5 2.5 0.5 11 3 3 5.75 4.25 3.25 CCSR 20.25 -4.25 -2.25 14.25 -6.25 -5.25 7.25 -0.25 -0.25 CSIRO 24.25 -2.25 -2.25 16 -3 -3 9.75 -1.75 -1.75

ECHAM4 21.5 -3.5 -6.5 13.5 0.5 -2.5 6.5 4.5 -0.5 GFDL 20.5 -2.5 0.5 13 -1 0 8.25 -0.25 -0.25

HADCM 21 -1 -5 14.25 -3.25 -5.25 9.25 -0.25 -3.25 GISS 24.5 -1.5 -6.5 17.5 -3.5 -6.5 11 -4 -4

NCAR 19.75 -8.75 N/A 13.25 -9.25 N/A 7.5 -5.5 N/A µ -2.66 -3.07 -2.84 -2.79 -0.41 -0.96 σ 3.2 3 3.82 3.35 3.52 2.38

12-month moderate 12-month severe 12-month extreme

Model Ī ∆N1 ∆N2 Ī ∆N1 ∆N2 Ī ∆N1 ∆N2

CCCma 4.75 4.25 2.25 3 3 1 2 2 1 CCSR 5 1 1 3.5 1.5 -0.5 2.75 0.25 -0.75 CSIRO 7.25 -0.25 -3.25 5.25 -2.25 -3.25 3.5 -2.5 -3.5

ECHAM4 6.75 0.25 -1.75 4.5 0.5 -1.5 2.5 1.5 -0.5 GFDL 6.75 0.25 0.25 4.5 0.5 -0.5 2.75 1.25 -0.75

HADCM 7.25 -1.25 -3.25 5.25 -3.25 -3.25 3.25 -1.25 -2.25 GISS 9 -3 -5 7 -2 -4 4.5 -1.5 -1.5

NCAR 5.25 -2.25 N/A 4.25 -3.25 N/A 2.5 -1.5 N/A µ -0.125 -1.39 -0.66 -1.71 -0.22 -1.18 σ 2.23 2.64 2.34 1.84 1.68 1.43

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Table 4. Estimated probabilities of model simulated frequency changes that will occur due to

natural variability. µ is the mean frequency for 20th century, σ is the standard deviation of the

20th century mean, ∆µ1 is the frequency for 2001-2025, P1 is the probability of ∆µ1 being less

than its value by chance, ∆µ2, is the frequency for 2026-2050, and P2 is the probability of ∆µ2

being less than its value by chance.

µ σ ∆µ1 P1 ∆µ2 P2

3-month moderate 20.2 2.97 18.8 0.33 18.6 0.30

3-month severe 13.0 2.76 11.3 0.27 11.4 0.28

3-month extreme 7.9 2.19 7.8 0.47 7.3 0.39

12-month moderate 6.3 1.67 6.4 0.64 5.3 0.27

12-month severe 4.2 1.44 4.0 0.45 3.0 0.20

12-month extreme 3.0 1.19 2.8 0.42 1.9 0.17

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Figure 1. The 30-year (1961-1990) mean precipitation climatology for the study region, 60-83°W, 30-50°N (Hulme, 1998).

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Figure 2. Observed SPI values calculated from CRU climatological data (Hulme, 1998) for the study region (Figure 1).

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3 month moderate drought frequencies

0

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1901-1925 1926-1950 1951-1975 1976-2000 2001-2025 2026-2050

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3 month severe drought frequencies

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Figure 3. Time series of observed and modeled 3-month drought frequencies.

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12 month moderate drought frequencies

0123456789

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1901-1925 1926-1950 1951-1975 1976-2000 2001-2025 2026-2050

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1901-1925 1926-1950 1951-1975 1976-2000 2001-2025 2026-2050

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Figure 4. Time series of observed and modeled 12-month drought frequencies.

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11.24 14.21 17.18 20.15 23.12 26.09 29.06

-3 -2 -1 0 1 2 30.0

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Standard deviations

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1.33 3.00 4.67 6.34 8.01 9.68 11.35

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3 month severe

2122

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4.72 7.48 10.24 13.00 15.76 18.52 21.28

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3 month extreme

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1.36 3.55 5.74 7.93 10.12 12.31 14.50

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-3 -2 -1 0 1 2 30.0

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0.62 1.81 3.00 4.19 5.38 6.57

Frequency

Figure 5. Probability distributions of drought frequencies (number of droughts in each 25-year interval) for models’ control experiments. The actual number of drought events in each frequency bin is indicated on the top of each bar.

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3 month moderate drought durations

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1901-1925 1926-1950 1951-1975 1976-2000 2001-2025 2026-2050

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obs avg

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Figure 6. Time series of observed and modeled 3-month drought durations.

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12 month moderate drought average durations

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1901-1925 1926-1950 1951-1975 1976-2000 2001-2025 2026-2050

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1901-1925 1926-1950 1951-1975 1976-2000 2001-2025 2026-2050

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atio

n (m

onth

s)

12 month extreme drought average durations

0

10

20

30

40

50

60

70

80

1901-1925 1926-1950 1951-1975 1976-2000 2001-2025 2026-2050

Dur

atio

n (m

onth

s)

Figure 7. Time series of observed and modeled 12-month drought durations.

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Appendix

Table A1. Event amounts at each time interval for all six classes of droughts. T1 - T6 stand for the periods 1901-1925, 1926-1950, 1951-1975, 1976-2000, 2001-2025, 2026-2050, respectively. 3-month moderate drought (SPI < -0.84) 3-month severe drought (SPI < -1.28) 3-month extreme drought (SPI < -1.65) Model T1 T2 T3 T4 T5 T6 T1 T2 T3 T4 T5 T6 T1 T2 T3 T4 T5 T6 CCCma 19 19 22 18 22 20 11 12 11 10 14 14 6 6 5 6 10 9 CCSR 20 26 18 17 16 18 17 19 9 12 8 9 10 9 3 7 7 7 CSIRO 24 29 21 23 22 22 18 20 10 16 13 13 13 11 7 8 8 8 ECHAM4 18 24 22 22 18 15 12 12 12 18 14 11 5 5 6 10 11 6 HADCM 17 21 22 22 18 21 9 12 16 15 12 13 6 8 9 10 8 8 GFDL 20 22 21 21 20 16 14 15 14 14 11 9 8 8 10 11 9 6 GISS N/A N/A 24 25 23 18 N/A N/A 17 18 14 11 N/A N/A 11 11 7 7 NCAR 19 18 22 20 11 N/A 14 10 16 13 4 N/A 7 5 9 9 2 N/A average 19.6 22.8 21.5 21.0 18.8 18.6 13.6 14.3 13.1 14.5 11.3 11.4 7.9 7.5 7.5 9.0 7.8 7.3 observations 20 27 22 20 N/A N/A 11 18 16 16 N/A N/A 7 10 10 12 N/A N/A

12-month moderate drought (SPI < -0.84) 12-month severe drought (SPI < -1.28) 12-month extreme drought (SPI < -1.65)Model T1 T2 T3 T4 T5 T6 T1 T2 T3 T4 T5 T6 T1 T2 T3 T4 T5 T6 CCCma 4 6 4 5 9 7 3 4 3 2 6 4 2 3 1 2 4 3 CCSR 5 5 4 6 6 6 5 4 1 4 5 3 4 3 1 3 3 2 CSIRO 7 9 4 9 7 4 6 7 2 6 3 2 5 2 3 4 1 0 ECHAM4 8 5 6 8 7 5 4 5 5 4 5 3 0 3 5 2 4 2 HADCM 5 6 8 8 7 7 3 4 5 6 5 4 2 2 3 4 4 2 GFDL 6 8 7 8 6 4 5 6 6 4 2 2 3 2 4 4 2 1 GISS N/A N/A 9 9 6 4 N/A N/A 7 7 5 3 N/A N/A 5 4 3 3 NCAR 8 3 6 4 3 N/A 7 2 5 3 1 N/A 3 1 4 2 1 N/A average 6.1 6.0 6.0 7.1 6.4 5.3 4.7 4.6 4.3 4.5 4.0 3.0 2.7 2.3 3.3 3.1 2.8 1.9 observations 8 9 5 7 N/A N/A 5 3 4 4 N/A N/A 4 2 2 2 N/A N/A