Assessing recent declines in Upper Rio Grande River runoff efficiency from a paleoclimate perspective

Transcription

1 Assessing recent declines in Upper Rio Grande River runoff efficiency from a paleoclimate perspective Flavio Lehner, Andrew Wood Eugene Wahl Dagmar Llewellyn, Douglas Blatchford NCAR Research Applications Lab NOAA Paleoclimatology Bureau of Reclamation

2 Upper Rio Grande Basin 2

3 Upper Rio Grande Basin Management goal: Early planning of allocations based on seasonal streamflow forecast Issues: Only mediocre forecast skill prior to critical allocation deadline in April Anecdotal evidence of systematic forecast biases in recent years End goals: Confirm systematic forecast bias Find cause Improve forecasts based on lessons learned 3

4 Motivation streamflow forecasting Apr-Jul streamflow Jan Feb Mar Apr May Jun Jul Aug 2015 Forecast issue month 4

5 Motivation streamflow forecasting Apr-Jul streamflow Streamflow of interest Jan Feb Mar Apr May Jun Jul Aug st week of April: allocations Forecast issue month 5

6 Motivation streamflow forecasting 1 st forecast (based on snowpack and weather climatology ) 90% Apr-Jul streamflow 50% 10% Streamflow of interest Jan Feb Mar Apr May Jun Jul Aug st week of April: allocations Forecast issue month 6

7 Motivation streamflow forecasting 1 st forecast 2 nd 3 rd 4 th last forecast Apr-Jul streamflow Streamflow of interest Jan Feb Mar Apr May Jun Jul Aug st week of April: allocations Forecast issue month 7

8 Motivation streamflow forecasting 1 st forecast 2 nd 3 rd 4 th last forecast Apr-Jul streamflow + Streamflow of interest Observed streamflow volume Apr-Jul Jan Feb Mar Apr May Jun Jul Aug st week of April: allocations Forecast issue month 8

9 Motivation streamflow forecasting Streamflow forecast bounds (NRCS) and observed Apr-Jul value for Otowi Bridge, NM 9

10 Motivation streamflow forecasting Streamflow forecast bounds (NRCS) and observed Apr-Jul value for Otowi Bridge, NM Recent tendency towards overforecasting in early phase of the calendar year 10

11 Decreasing basin efficiency? Wateryear precipitation Wateryear streamflow (x3) 11

12 Decreasing basin efficiency? Wateryear precipitation Wateryear streamflow (x3) 12

13 Decreasing basin efficiency? Similar behavior observed in Upper Colorado basin Woodhouse et al. (2016) 13

14 Upper Rio Grande Basin Management goal: Early planning of allocations based on seasonal streamflow forecast Issues: Only mediocre forecast skill prior to critical allocation deadline in April Anecdotal evidence of systematic forecast biases in recent years Questions: How common are such trends? What role does temperature play? Is this important for forecasting? End goals: Confirm systematic forecast bias Find cause Improve forecasts based on lessons learned 14

15 Reconstructions r =

16 Reconstructions r =

17 Reconstructions r = 0.80 r =

18 Reconstructions r = 0.80 r = 0.78 r =

19 Reconstructions r = 0.80 Probability that this recent trend is the strongest in 445 years: 99.1% r = % r = % 19

20 Reconstructions 20

21 Role of temperature Median precipitation Median temperature 21

22 Role of temperature 22

23 Role of temperature 23

24 Role of temperature 24

25 Role of temperature Very low runoff ratio ~2.5-3 times more likely when temperatures are above-median than when they are below 25

26 Role of temperature 26

27 Role of temperature 27

28 Role of land use change 28

29 Role of temperature 29

30 Role of temperature 1980s 2000s 30

31 Circulation composites CESM 31

32 Circulation composites CESM 57% El Niño events 44% PDO > 1 38% La Niña events 38% PDO < -1 32

33 Upper Rio Grande Basin Management goal: Early planning of allocations based on seasonal streamflow forecast Issues: Only mediocre forecast skill prior to critical allocation deadline in April Anecdotal evidence of systematic forecast biases in recent years Questions: How common are such trends? Answers: Apparently not that common End goals: Confirm systematic forecast bias Find cause Improve forecasts based on lessons learned 33

34 Upper Rio Grande Basin Management goal: Early planning of allocations based on seasonal streamflow forecast Issues: Only mediocre forecast skill prior to critical allocation deadline in April Anecdotal evidence of systematic forecast biases in recent years Questions: How common are such trends? What role does temperature play? Answers: Apparently not that common Acts to make low runoff ratio years even lower End goals: Confirm systematic forecast bias Find cause Improve forecasts based on lessons learned 34

35 Upper Rio Grande Basin Management goal: Early planning of allocations based on seasonal streamflow forecast Issues: Only mediocre forecast skill prior to critical allocation deadline in April Anecdotal evidence of systematic forecast biases in recent years Questions: How common are such trends? What role does temperature play? Is this important for forecasting? Answers: Apparently not that common Acts to make low runoff ratio years even lower Adds additional skill End goals: Confirm systematic forecast bias Find cause Improve forecasts based on lessons learned 35

36 Thank you Lehner, F., E. R. Wahl, A. W. Wood, D. B. Blatchford, D. Llewellyn (submitted): Assessing recent declines in Upper Rio Grande River runoff efficiency from a paleoclimate perspective

37 Supplementary slides 37

38 Role of temperature Relationship mainly driven by low precipitation years 38

39 Internal variability or climate change or both? Water year precipitation trend Sea level pressure trend 39

40 Internal variability or climate change or both? Water year precipitation trend

41 Internal variability or climate change or both? Water year precipitation trend

42 Internal variability or climate change or both? Water year precipitation trend

43 Climate change: predictable? RCP 2.6 RCP 8.5 Number of models (CMIP5) IPCC AR5 WG1 (2013) 43

44 Climate change: predictable? Hatching = signal < 1 σ RCP 2.6 RCP 8.5 IPCC AR5 WG1 (2013) 44

45 Internal variability: predictable? Wallace and Gutzler (1981) and others Atmospheric pressure indices are (anti-)correlated afar Modes of atmospheric circulation variability Emerge from a sufficiently large sample size Hoskins and Karoly (1981), Trenberth et al. (1998) and others Tropical heating is balanced by divergence aloft Pressure anomalies alter jet stream and incite Rossby waves Affects weather in mid-latitudes Barsugli and Battisti (1998) and others Coupling of ocean and atmosphere increases variance in both Deser et al. (2012) and others The butterfly effect works on decadal time scales, and not only on synoptic Barnes and Screen (2015), Shaw et al. (2016) and others Tug of war between opposing effects of climate change on mid-latitude jet position 45

46 Pacific Decadal Oscillation (PDO) and ENSO 46

47 Pacific Decadal Oscillation (PDO) and ENSO

48 PDO and ENSO teleconnections Correlation Observations M. Newman et al. (2016) 48

49 PDO and ENSO teleconnections Correlation Observations Newman et al. (2016) 49

50 PDO CESM Large Ensemble Ensemble member

51 PDO Pacemaker simulations Observations

52 PDO Pacemaker simulations Ensemble member Observations

53 PDO Pacemaker simulations Ensemble member

54 (Forced) internal variability Water year precipitation trend

55 (Forced) internal variability 56

56 Contributions from (forced) internal variability Pacemaker simulations Rio Grande basin Free-running simulations Observations 57

57 Contributions from (forced) internal variability Pacemaker simulations Rio Grande basin Free-running simulations Observations Confirms earlier results based solely on observations Hamlet et al. (2005) 58

58 Contributions from (forced) internal variability Rio Grande basin Observations 59

59 Rio Grande seasons 60

60 Tug of war 61

61 62

62 63

63 64

64 65