SM_Snow_DroughtQuiring.ppt [Read-Only] - Drought Research ...

What Causes Drought
An Examination of the Role of
Land Surface Conditions
Steven Quiring
DRI Workshop
January 12, 2007
Consul, Saskatchewan (April, 2002)
Ted Banks

Motivation
Koster et al. (2004)

Research Objectives
I. Examine the importance of land
surface conditions (snowfall and soil
moisture) in initiating and/or
exacerbating drought conditions in
the Northern Great Plains (NGP)
II.
Can we use snowfall and soil
moisture conditions prior to the
growing season to forecast drought

Evaporation
3) Increased Precipitation
Recycling
Transpiration
Snowfall-Soil
moisture-
Precipitation
Feedback
2b) Increased E + T (ET)
POSITIVE
2a) Increased soil
moisture recharge
1) High Winter/Spring Snowfall
(or Fall precipitation)

3) Decreased Precipitation
Recycling
Transpiration
Snowfall-Soil
moisture-
Precipitation
Feedback
“Drought begets drought”
Namias (1960)
Evaporation
2b) Decreased E + T (ET)
2a) Decreased soil
moisture recharge
NEGATIVE
1) Low Winter/Spring Snowfall
(or Fall precipitation)

Study Region
55°0'0"N
110°0'0"W
105°0'0"W
100°0'0"W
95°0'0"W
55°0'0"N
•NGP = encompasses
portions of Manitoba,
Saskatchewan, Alberta & 12
US States
50°0'0"N
50°0'0"N
45°0'0"N
40°0'0"N
Moisture Anomaly
< -3
-2 to -3
-1 to -2
0 to -1
0 to 1
1 to 2
2 to 3
> 3
110°0'0"W
105°0'0"W
100°0'0"W
95°0'0"W
Summer (JJA) moisture
anomalies associated
with the 5 driest between
1929 and 1999
45°0'0"N
40°0'0"N
•Drought data based on
Palmer’s Moisture Anomaly
Index calculated from station
and climate division data
(interpolated to a 1 by 1
grid)
•Monthly data (1929-1999),
only summer (JJA) moisture
anomalies were analyzed

Snowfall Data
•North American gridded
(1 by 1 ) snowfall and
snow cover developed by
T. Mote (Univ. Georgia)
•Interpolated from U.S.
National Weather Service
(NWS) cooperative stations
and the Canadian daily
surface observations
•Daily data (1900-2000)

Soil Moisture
•Variable Infiltration Capacity
(VIC) macroscale hydrological
model
•Developed by Lettenmaier’s
hydrology group at University
of Washington
•3 layer soil water model that
utilizes a soil-vegetationatmosphere
transfer scheme to
account for land-atmosphere
interactions
•Daily simulation over CONUS
at (0.5 by 0.5 ) (1915-2005)

1) Does decreased snowfall lead to
decreased soil moisture recharge
Climatic Water Budget for Northern Minnesota

NGP Snowfall & June 1 Soil Moisture
r = 0.43 (similar correlation between seasonal snowfall and May 1 SM)

NGP Soil Moisture Composite

2) Are droughts associated with
reduced precipitation recycling
• Recycled precipitation = water from ET that falls
again as rain within the same area (strongly
influenced by size of region)
• Estimates of summer recycling ratios in the NGP
vary (L = 500 km):
– 12% (Trenberth, 1999)
– 14-17% (Dominguez et al., 2006)
– 21% (Raddatz, 2006)
• Local ET provides water vapor and CAPE, linked to
increased convection

Dominguez et al. (2006)

0.19 0.16 0.16 0.13
0.14 0.12
0.16 0.14
Dominguez et al. (2006)

Recycled Precipitation (1980–1999)
r = 0.73

Recycling Ratio (1980–1999)
Compare to Raddatz (2006):
r = 0.43
Drought = 0.17
Pluvial = 0.24

3) Are snowfall/SWE anomalies related
to drought

Snowfall Composites
Winter
Spring
Dry
Wet
-67 mm -63 mm

NGP Drought Composites

NGP April-May Snowfall & Drought
Snowfall (blue)
Summer drought (red)
r = 0.22

Temporal Variability
Winter (DJF) (blue line) and April-May (green line) snowfall anomalies and
summer moisture anomalies (Z-index) calculated for all 15 yr time periods
between 1929 and 1999. Dashed lines indicate the 95% significance level.

Summary & Conclusions
• Below (above) normal snowfall in winter/spring is
generally associated with anomalously dry (wet) soil
moisture in May through July and lower (higher)
than normal summer precipitation
• The strength of the relationship between
winter/spring snowfall and summer moisture
anomalies varies significantly over space and time
• Lack of spatial and temporal stability in the snowfalldrought
and soil moisture-drought relationships
have significant implications for understanding and
forecasting these events

Acknowledgements:
T. Mote (University of Georgia)
D. Kluver (University of Delaware)
F. Dominguez (University of Illinois)
E. Wood (University of Washington)
Consul, Saskatchewan (April, 2002)
Ted Banks

4) Can we use soil moisture data to
forecast drought
r = 0.51

Future Research
• Further analysis of snow and soil moisture
data
• Examine causes of spatial and temporal
variability
• Modeling land-atmosphere interactions
using regional climate model
• Developing hindcast and predictive drought
models for the NGP