Jennifer Jacobs, Bryan Carignan, and Carrie Vuyovich. Environmental Research Group University of New Hampshire

Transcription

1 Jennifer Jacobs, Bryan Carignan, and Carrie Vuyovich Environmental Research Group University of New Hampshire New Hampshire Water Conference March 21, 2014 Funding Provided By: NASA 1

2 Precipitation is projected to increase towards the poles and decrease in the mid-latitudes [Solomon, 2007]. Precipitation intensity is projected to increase globally but the interlude between events is expected to lengthen as well [Solomon, 2007]. Climate change simulations have shown that the snow season will shorten due to a later start in the fall and an earlier end in the spring [Jain et al., 2011]. The length of the snow season will be cut in half in the northeast [Frumhoff et al., 2007] NH modeled water equivalent (SWE) is decreasing by mm/decade for ; 3.52 mm/decade from [Hayhoe et al., 2006] NH SWE is predicted to decrease from 11 mm to between 5.5 and 6.6 mm and snow season duration will decrease from 62 days to between 36 and 42 days by [Hayhoe et al., 2006]. 2

3 A study by Hodgkins and Dudley used long-term and short-term historical data from Maine and Northern New Hampshire snow surveys and showed a significant decreasing trend in snowpack depth for many of the sites [Hodgkins and Dudley, 2006]. Lower-snowfall winters (e.g., 2001/2002 and 2006/2007) cost New Hampshire ski resorts an estimated $54.3 million in lost revenue and a 17 percent fewer skier visits compared to highersnowfall winters (e.g., 2007/2008 and 2008/2009). [Burakowski, 2012]. Small-scale comparison studies of GCMs and RCMs to observed data show that models can underestimate many of the snow parameters, especially snow cover duration and SWE [Salzmann and Mearns, 2012]. 3

4 H1: Historical NH observations will show a decrease in SWE. H2: Validation will show that climate model output underestimates observed SWE values. H3: In the future, average modeled SWE will be lower than baseline SWE. H4: In the future, average modeled SWE will arrive later and end earlier than baseline SWE. 4

5 Snow Surveys: Hubbard Brook Experimental Forest NHDES, USACE Maine Study area: New England By watersheds (HUC 6) Aggregation: Average SWE for each HUC Examine differences 5

6 Atmosphere-Ocean General Circulation Models (GCMs) Model the global climate circulation Regional Climate Models (RCMs) Regional models allow for finer scale resolution North American Regional Climate Change Assessment Program (NARCCAP ) Produces high resolution climate change simulations Generates climate change scenarios for use in impacts research National Centers for Environmental Prediction (NCEP) Refers to the NCEP Reanalysis II data Simulated data set that incorporates observations with modeled output 6

7 NARCCAP Models: RCMs (6) driven with NCEP data km resolution 3hr time-intervals RCMs driven with GCMs (12) Baseline: Future: km resolution 3hr time - intervals mb/ncep/tn_pr_udel_djf.png 7

8 : Hubbard Brook Experimental Forest in red; NHDES in blue 8

9 Trend (cm/yr) Total SWE Decrease (cm) HBEF NHDES 30 yrs 60 yrs 70 yrs January February March April Observed data sets are from 1960 to 2012 (53 yrs) Total SWE decreases estimated using the slope of the trend line. Hayhoe et al., 2006 SWE is decreasing by cm/yr from ; SWE is decreasing by cm/yr from

10 NARCCAP Model Data Catalog RCM NCEP GCM CCSM CGCM3 GFDL HADCM3 CRCM X X X ECP2 X X X HRM3 X X X MM5I X X X RCM3 X X X WRFG X X X Note: X indicates available combinations, X indicates a combination that was used. 10

11 ME Snow Survey Model Discrepancy Plots The models were matched to the observed data set by date 11

12 USACE Observations JAN FEB CRCM and RCM3 are the only models that agree with observations This is the same for all observed datasets MAR APR 12

13 MAE (m) Mean Absolute Error Comparison Hubbard Brook NHDES ME SS USACE CRCM RCM3 WRFG MM5I HRM3 ECP2 HB (521 dates, 2990 observations) ME SS (444 dates, observations) NHDES (782 dates, observations) USACE (368 dates, 5395 observations) 13

14 Magnitude of Peak SWE (m) a. Hubbard Brook b. NHDES c. ME Snow Survey d. USACE 14

15 Peak Date Day of Water Year Date Day of Water Year 9/30 0 1/1 93 3/ /1 214 a. Hubbard Brook b. NHDES c. ME Snow Survey d. USACE 15

16 The CRCM and RCM3 regional climate models are the best of the NARCCAP models at predicting SWE The CRCM and RCM3 models predict ALL SWE related variables, including daily average SWE, peak SWE, and peak dates better than the other models 16

17 The simulation of snow processes within a GCM or RCM can be attributed mainly to the land surface scheme (LSS) that the climate model uses [Slater et al., 2001] Model CRCM RCM3 WRFG MM5I HRM3 ECP2 Land Surface Scheme CLASS BATS NOAH NOAH MOSES NOAH 17

18 Ammann and Vigh,

19 NARCCAP Model Data Catalog RCM NCEP GCM CCSM CGCM3 GFDL HADCM3 CRCM X X X ECP2 X X X HRM3 X X X MM5I X X X RCM3 X X X WRFG X X X Baseline ( ) vs Future (2041 to 2070) 19

20 Significance Test of Monthly SWE decreases Kilometers DEC JAN FEB MAR APR Count of Models Predicting Change

21 Monthly average magnitudes approximate ranges: Month Range of Decrease (%) December January February March April Baseline (1971to 2000) Future (2041 to 2070) 21

22 Peak SWE Magnitudes Most models show significant decreases in peak SWE values Kilometers RCM - GCM Decrease (%) CRCM - CCSM 30 CRCM - CGCM3 30 RCM3 - CGCM3 25 RCM3 - GFDL 25 Count of Models Predicting Change

23 Peak SWE Date The timing of peak SWE may not be significantly affected by climate change RCM - GCM Average # of Days Change CRCM - CCSM -8 CRCM - CGCM3 +10 RCM3 - CGCM3-16 RCM3 - GFDL -3 ± Count of Models Predicting Change

24 SWE Start Dates All models agree that the start dates will be significantly later in the northern watersheds RCM - GCM Average # of Days Change CRCM - CCSM +16 CRCM - CGCM3 +12 RCM3 - CGCM3 +15 RCM3 - GFDL +19 ± Count of Models Predicting Change

25 SWE End Dates All models agree that the end dates will be significantly earlier in the northern watersheds RCM - GCM Average # of Days Change CRCM - CCSM -14 CRCM - CGCM3-18 RCM3 - CGCM3-21 RCM3 - GFDL -16 ± Count of Models Predicting Change

26 Monthly SWE averages will decrease from 25% to 75% depending on the model and the month Peak SWE will decrease 25% to 30% The timing of peak SWE might not be affected Winters will start 2 weeks later Winters will end 2 to 3 weeks earlier 26

27 The length of the snow season in the northeast will be cut in half in the northeast Frumhoff, et al. (2007) Findings: the length of the snow season will shorten by 4 to 5 weeks Climate change simulations have shown that the snow season will shorten due to a later start in the fall and an earlier end in the spring [Jain et al., 2011]. Findings: the snow season will start 2 weeks later and end 2 to 3 weeks earlier in the northeast Small-scale comparison studies of GCMs and RCMs to observed data show that models can underestimate many of the snow parameters, especially snow cover duration and SWE [Salzmann and Mearns, 2012]. Findings: of the 6 RCMs compared, only CRCM and RCM3 were comparable to observed data 27

28 Baseline SWE (cm) Future GCM-RCM Future Historic Trend HBEF NHDES HBEF NHDES HBEF NHDES January February March April Baseline (1971to 2000); Future (2041 to 2070) 28

29 Capacity of regional climate models to model SWE in New England Few RCMs are able to capture SWE dynamics Recommended RCM models: Regional Climate Model 3 (RCM3) Canadian Regional Climate Model (CRCM) Future Forecasts of New England Snow Using Modeled SWE Maximum SWE could decline by 25 to 30% Duration of snow season could decline by 4 to 5 weeks Historical Trends and Forecasts of New England Snow Trends exists and are significant Historical decreases differ from modeled decreases for baseline and future periods 29

30 Barnett, T. P., J. C. Adam, and D. P. Lettenmaier (2005), Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438(7066), Burakowski, E. M., Matthew (2012), Climate Impacts on the Winter Tourism Economy in the United States, NRDC. Frumhoff, et al. (2007) Confronting Climate Change in the U.S. Northeast: Science, Impacts, and Solutions. Synthesis report of the Northeast Climate Impacts Assessment (NECIA). Cambridge, MA: Union of Concerned Scientists. Hayhoe, K., C. Wake, B. Anderson, X.-Z. Liang, E. Maurer, J. Zhu, J. Bradbury, A. DeGaetano, A. Stoner, and D. Wuebbles (2008), Regional climate change projections for the Northeast USA, Mitigation and Adaptation Strategies for Global Change, 13(5), Hodgkins, G. A., and R. W. Dudley (2006), Changes in late-winter snowpack depth, water equivalent, and density in Maine, , Hydrological Processes, 20(4), Jain, S. K., L. N. Thakural, R. D. Singh, A. K. Lohani, and S. K. Mishra (2011), Snow cover depletion under changed climate with the help of remote sensing and temperature data, Natural Hazards, 58(3), Salzmann, N., and L. O. Mearns (2012), Assessing the Performance of Multiple Regional Climate Model Simulations for Seasonal Mountain Snow in the Upper Colorado River Basin, Journal of Hydrometeorology, 13(2), Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (eds.) (2007), Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007Rep., IPCC. 30

31 Wish I was here! Special thanks to Bryan Carignan M.S

32 Hubbard Brook Model Discrepancy Plots 32

33 NHDES Model Discrepancy Plots 33

34 ME Snow Survey Model Discrepancy Plots 34

35 USACE Model Discrepancy Plots (m) The models were matched to the observed data set by date 35