Transcript Powerpoint - Hawai`i Conservation Alliance

Precipitation Extremes in the Hawaiian
Islands under a changing climate
Pao-Shin Chu
Ying Chen, Chase Norton, Tom Schroeder
Department of Meteorology and
Hawaii State Climate Office
University of Hawaii-Manoa
February 29, 2012 (Hawaii Conservation Alliance)
Outline
1. Trends in climate change indices
2. Projection of future heavy rainfall
events for Oahu
3. Hawaii State Climate Office
Heavy rainfall events are common in
Hawaii
• The interaction of synoptic systems (cold fronts,
kona storms, upper level troughs) with local
topography often results in heavy rainfall events that
cause damage to properties, agriculture, and public
facilities.
• Pollutants carried away by stream flows during
heavy rainfall events are one of the major threats to
marine ecosystems, especially coastal coral reefs.
Heavy rainfall events in the past 8 years
• The Halloween flood of 2004 at the UHManoa (damage ~$80 million for UH)
• The extensive 2006 flood events (The
Ka Loko dam on Kauai burst and killed
7 people; the Kahala Mall flooded)
• The December 2008 flood on
Kauai/Oahu (damage ~$50 million and
garnered a federal disaster declaration
from the US President)
• The December 2010 floods on Oahu/
Hawaii (The Ala Moana Shopping
Center was closed because of power
outage by excess rainwater)
Drought
• Drought in Hawaii has
been a recurrent and
troublesome problem
for the State. Drought
reduced crop yields,
diminished livestock
herds, depleted
groundwater supplies,
and led to forest and
brush fires.
Drought History since 1980 (Hawaii
Drought Monitor –DLNR/CWRM)
• 1980-81 Hawaii and Maui declared disaster; heavy agri and cattle
losses; damages at least $1.4 million
• 1983-85 El Niño effect; State declared disaster; crop production
reduced by 80% in Waimea and Kamuela areas
• 1996 Hawaii, Maui, and Molokai declared drought emergency;
losses in agri and cattle industries around $9.4 million
• 1998-99 El Niño effect; Hawaii and Maui declared drought
emergency; statewide cattle losses estimated at $6.5 million
• 2000-2002: Governor proclaims statewide drought emergency;
Secretary of Interior designates all counties as primary disaster
areas; statewide cattle losses estimated at $9 million
•
1. Trends in climate change
indices
● Long-term winter (Nov-Mar) rainfall variations in Hawaii from
1905 to 2009; winter is the rainy season
● HRI stands for the Hawaii Rainfall Index (9 stations from each of
three islands, Kauai, Oahu, and Hawaii)
● The original rainfall data are standardized (Chu and Chen, 2005)
El Niño and Hawaii rainfall
1. Trends in climate change
indices
● How was the change in precipitation extremes?
Will they be similar or different from the total
winter rainfall?
● How about changes from one island to another?
Definition of the five climate change
indices (WMO/CLIVAR)
Perspective Index Definition
Unit
Intensity
SDII
Average precipitation intensity in wet days
mm/day
Frequenc
R25
Annual total number of days with precipitation 25.4 mm
days
y
Magnitude R5d
Annual maximum consecutive 5-day precipitation amount mm
Magnitude R95p Fraction of annual total precipitation due to events
Drought
%
exceeding the 1961-90 95th percentile
The first four indices are related to the wetness conditions; CDD
defines
the maximum
duration ofnumber
excessive
dryness. dry days
CDD
Annual
of consecutive
days
Precipitation Intensity
The overall
data set is
split into 2
epochs:
1950-79 vs
1980-2007
Peak around 9-11 days; 35-80 CDD occur
more often in the last 3 decades (i.e.,
consecutive dry days near 35-80 days window
are happening more often since 1980s)
Used a nonparametric Mann-Kendall
method with the Sen’s test (MKS) to
investigate trends in precipitation
extremes (e.g., precipitation intensity,
consecutive dry days). The MKS is
robust against outliers and skewed
distribution (a robust trend detection
method).
SDII: rainfall
intensity
Long-term Spatial Features
trends from the 1950s to
2007, triangles
•
•
Intensity
Frequency
R25: total number of days with
daily rainfall ≥ 1 in
Downward trends in SDII and
R25 for Kauai and Oahu (Rainfall
became less intense since 1950)
Upward trends in SDII for Big
Island (more intense rainfall)
R5d: consecutive 5
day rainfall totals
Long-term Spatial Features
• For CDD, overall upward
trends. Most islands tend to
show longer, consecutive
periods of no precipitation
days since 1950s.
Magnitude
Drought
CDD: Consecutive dry days
Summary for Part 1
• Trends of five climate change indicators are
examined over the last 60 years. Results reveal
a regional pattern. Oahu and Kauai are
dominated by long-term downward trends for 4
precipitation related indices, while increasing
trends (SDII, R5d, and R95p) are noted over the
Big Island (e.g., more intense rainfall, more 5-d
rainfall amounts). East-West difference.
• Long-term upward trends of drought conditions
(CDD) are observed on all the major islands
(longer consecutive dry days since 1950s) .
Part 2. Estimating Future Heavy
Rainfall Events for Oahu
GCM (General Circulation Model)
simulates the physical processes
of the atmosphere and ocean
given initial and boundary
conditions
• GCM uses mathematics and the law of physics
to describe the behavior of the climate– GCM
represents the atmosphere and ocean by
dividing it up into grid squares.
• For GCMs, the horizontal grid spacing is coarse
and presents a problem for Hawaii because of
the small size of the islands.
• Need to “downscale” simulations from GCM for
Hawaii. Downscaling is the process for making a
link between the large-scale atmospheric
circulation and local rainfall.
• Statistical downscaling is to find an
empirical relation between circulation and
local rainfall via statistical methods.
• Dynamical downscaling is a method for
obtaining high-resolution climate
information from coarse resolution GCMs.
This is achieved by using a high resolution
regional climate model that is initialized
with the output from GCMs.
- Computationally demanding
Statistical Downscaling
Station Rainfall Data
• Stations with at least 30 yrs of daily rainfall data
• After some quality control, only 16 stations for Oahu
(1979-2008) are used
GCM Data
• 24 GCMs available (impractical and inefficient)
• Evaluate appropriateness of GCMs for use in Hawaii (a
baseline test – compare the averaged observed rainfall during
1979-2008 with GCM back projections of the same period, a future
projection test – compare each GCM to filter outliers and ranked
according to absolute difference from the mean)
• These 2 tests are combined to find an overall high ranked
model among all 24 GCMs (ECHAM5 A2)
• Neural network model (a nonlinear
method) because heavy rainfall events (>
90th percentile) may not respond linearly to
atmospheric forcings. The advantage is its
ability to find maximum relation between
predictors and local rainfall.
• Four predictors are chosen (low-level wind
components, sea level pressure, and
relative humidity in the lower atmosphere)
• Only seven stations show strong
correlations.
Figure 1
Changes in heavy rainfall frequency
HIA: 47 43 57
ECHAM5 slightly underestimates the frequency of events under the present-day
climate; more heavy rainfall events are projected in the future
Changes in heavy rainfall intensity
HIA: 79 73 64 mm/day
Model shows a
dry bias
The projected average heavy rainfall intensity is lower than those from the
observations and model simulations under the present-day climate.
Summary for Part 2
• A statistical model based on neural
networks is used to downscale daily
extreme precipitation events in Oahu from
GCM outputs and projected into the future.
• Increased frequency of heavy precipitation
events but a decrease in precipitation
intensity for the southern shoreline of
Oahu for the next 30 years (2011-2040).
3.
Hawaii State Climate Office (HSCO)
[email protected]
• Fully recognized by AASC (American Association of State
Climatologists) in 2002 and in partnership with NOAA/NCDC
• Serving as an official clearinghouse for climate/weather records in
Hawaii and USAPI
• Providing climate data to users on a timely basis; users include civil
and environmental engineers or planners, insurance companies,
government agencies (e.g., DOH, HPD), researchers/students,
individuals
• Providing current and emerging news to newspapers, TV, and radio
• Consulting (e.g., rain storm and flood in January 2002 at Manele Bay
on Lanai)
• Drought risk assessment and GIS mapping for
the Hawaiian Islands (DLNR funded)
• Kona coffee and climate project (NOAA funded)
• Providing data to update rainfall-frequency atlas
for Hawaii by NOAA (funded by DOH)
• Protocol Development for Monitoring Climate for
the Pacific Islands (NPS funded)
• Updating rainfall station index and atlas
(funded by four counties in Hawaii)
References ([email protected])
Chu, 1995: Hawaii rainfall anomalies and El Niño.
J. Climate, 8, 1697-1703.
Chu/Chen, 2005: Interannual and interdecadal rainfall
variations in the Hawaiian Islands.
J. Climate, 18, 4796-4813.
Chu/Chen/Schroeder, 2010: Changes in precipitation
extremes in the Hawaiian Islands in a warming climate.
J. Climate, 23, 4881-4900.
Norton/Chu/Schroeder, 2011: Projecting changes in future
heavy rainfall events for Oahu, Hawaii: A statistical
downscaling approach. J. Geophys. Res., 116, D17110.
Mahalo!