Extremes Seminar: Tornadoes

Transcription

1 Dec. 01, 2014

2 Outline Introduction 1 Introduction 2 3 4

3 Introduction 101: What is a tornado? According to the Glossary of Meteorology (AMS 2000), a tornado is a violently rotating column of air, pendant from a cumuliform cloud or underneath a cumuliform cloud, and often (but not always) visible as a funnel cloud.

4 3-Papers: 1 Does Global Warming Influence Tornado Activity? (by N. Diffenbaugh, R. Trapp and H. Brooks 2008) 2 Severe thunderstorms and climate change. (by H. Brooks 2012) 3 Robust increases in severe thunderstorm environments in response to greenhouse forcing. (by N. Diffenbaugh, M. Scherer and R. Trapp)

5 Introduction Main question: does global warming influence Tornado activity? Tornadoes (+other severe thunderstorms) frequently cause as much annual property damage in the U.S. as do hurricanes In fact, often cause more fatalities In 2008: there were 2176 preliminary tornado reports logged through mid-december, with 1600 actual counts (duplicate reports removed) through September This is the highest total in the past half century (Figure 1)

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7 These may be potentially linked to anthropogenic global warming Recent research has yielded insight into the connections between global warming and tornado and severe thunderstorm forcing But these relationships remain mostly unexplored: largely because of the challenges in observing and numerically simulating tornadoes Paper explores the challenges and opportunities in pursuing possible research areas (trends and causes of Tornado occurrence)

8 Tornado Trend Detection The number of tornadoes reported in the United States per year has been increasing steadily ( 14 per year) over the past half century (below: Figure 2)

9 Difficulties in Tornado trend detection: 1 short historical record, 1950s 2 nonuniform in space and time redords 3 observational record based on a reporting system designed essentially for the verification of forecasts rather than for research-quality climate studies 4 reliance on human reports leaves trends subject to external influences (e.g. population growth) although some regions such as the southern Great Plains do not reflect the congruous long-term trends in tornado occurrence and population growth comapred to the entire U.S. (Figure 2)

10 The number of tornadoes classified as the most damaging (rated F2 F5 on Fujita scale) appears to have decreased over the period (Figure 2)? Generally, Tornado trend detection is complex: may require appropriate statistical models and developement of other analysis approaches(e.g. coupling climatological information with tornado-report proxies)

11 Tornado Trend Attribution: a review Changes in seasonal tornado activity can plausibly be explained by shifts in the mean jet stream position associated with the ENSO (e.g. see Cook and Schaefer 2008) Yet the literature does not provide clear consensus about the nature of links between tornadoes and natural climate variability Also global warming could affect the frequency, seasonality, and spatial distribution of severe thunderstorms and tornadoes

12 Severe thunderstorms that spawn tornadoes arise in larger-scale environments characterized by large vertical Wind Shear and Convective Available Potential Energy (CAPE) More generally, global warming is expected to increase CAPE by increasing temperature and humidity within the atmospheric boundary layer while simultaneously weakening vertical wind shear by decreasing the pole-to- equator temperature gradient (e.g. see Trapp et al. 2007a)

13 The regions that experience peak tornado occurrence at present could therefore see reductions due to weakened small Shear But the reductions could be offset by increased CAPE, which could lead to increased tornado occurrence Also changes in Shear and CAPE can modify the seasons of tornado forcing: e.g. with enhanced cool-season activity

14 Warming can potentially shift the regions of greatest tornado occurrence poleward by shifting peak Shear poleward while simultaneously increasing CAPE in those same regions Generally, Tornado trend attribution is complex: may require the consideration of other facets e.g. the effect of global warming on the initiation of the deep convective clouds that become tornadic storms Future Changes in Tornado Activity: limitations in current knowledge and climate model resolution + uncertainty pose challenges for projecting future changes

15 Introduction Examines distribution of severe thunderstorms =f(large-scale environmental conditions /Warming) Preview of findings: (i) severe thunderstorms are much more likely to form in environments with large values of deep-tropospheric wind Shear and CAPE (ii) Tornadoes and hail and their intensities tends to entirely be a function of the Shear and weakly depends on the thermodynamics Caveat: Climate model simulations suggest that CAPE will increase and wind Shear will decrease -> the directions of future Tornadoes and hail changes is open to question

16 While global average temperature may be of less importance to most of society, changes in local weather events (particularly extreme events) are of greater concern Tropical cyclones(hurricanes) have received significant research attention in the last decade, but Limited research attention on severe thunderstorms (Tornadoes and large hail) and their linkages with global climate (1. data/report limitations, and 2. small horizontal nature makes it difficult to analyse with large grid global models) Therefore: IPCC Assessment Reports on thunderstorms is marginal; tend to be a paragraph or two

17 Reports: Typically target of opportunity observations: limited data report systems; available systems collect information mainly for forecasting purposes -> so posses data interpretation problems with inhomogeneities Pointed out that: previous studies (e.g. Xie et al. 2008) found evidence of larger Hail formation in higher CAPE environments Problems: these are mall pockets of studies; only go back yrs -> so hard to have confidence in the long term trends

18 Environmental-Estimates: Utilize meteorological covariates approach to circumvent use of reports challenges Covariates relate environmental conditions (may be well-observed) to weather events of greater interest (but are not well-observed) Pointed out that: previous studies have used reanalysis data (env. conditions) to estimate distribution of severe thunderstorms and tornadoes E.g. Allen et al. (2011) did analysis for Australia and found a roughly parallel discrimination line for dataset, approx. CAPE SHR6 1.6 = k where k is some constant: -> deep Shear is more important than CAPE for discriminating between severe and non-severe thunderstorms

19 Examine WMAX-SHR6 space (Gaussian Kernel smoother), where from parcel theory: WMAX = 2 CAPE The distribution of sounding values shows that most thunderstorm soundings occur for combinations/(joint) of relatively small WMAX and SHR6 Extremes (above: Seminar: Tornadoes Fig.1)

20 The distribution in WMAX-SHR6 of significant severe thunderstorm soundings shows that they tend to occur off of the WMAX or SHR6= 0 axes (below: Fig. 2)

21 Gaussian Kernel Smoother The probability of a significant severe thunderstorm shows much higher probabilities as the WMAX and SHR6 increase

22 There are similarities in the distribution for the ESWD data (below Fig. 4) but: the distribution does not extend to as high of values of WMAX ( 65); conditional probability for severe much higher( 4%)

23 Next, (below: Fig. 5) Probability of a significant severe thunderstorm producing tornado or hail incr. with incr. in SHR6; probability of wind incr. with decr. in SHR6; insignificant for WMAX

24 Summarize observed relationship using Clearly, dividing line between greater and lesser probability compared to base rate is almost the same line for all 3 threats over a broad rangefrancis of WMAX Annan

25 Modelling-Studies:review Number studies carried out to quantify climate change impacts on severe thunderstorms Different conclusions or evidence in some parts of the world, e.g. Southern Australia but, Consistent results found in the U.S.: 1 CAPE (or WMAX) increasing over most of the US east of the Rockies: driven by increases in boundary layer moisture as surface temperatures warm 2 SHR6 decreasing over much of the US: driven mainly by a reduction in temperature differences(equator-to-pole) and thermal wind changes Climate model simulations suggest increase in CAPE and decrease in Shear -> the directions of future Tornadoes and hail changes is open

26 Introduction Motivation: Severe thunderstorms are one of the primary causes of catastrophic loss in the U.S.; yet their response to greenhouse forcing is uncertain for CC impact assessments Model severe thunderstorms =f(greenhouse forcing) Preview of findings: (i) Evidence of robust increases in occurrence of severe thunderstorm environments (over eastern U.S.) in response to further global warming (ii) For spring and autumn: these robust increases emerge before mean global warming of 2 0 C

27 (iii) Find that days with high CAPE and strong low-level wind Shear increase in occurrence. This suggests an incr. chance of atmospheric conditions that trigger severe events, e.g Tornado (iv) Find that decreases in Shear are concentrated in days with low CAPE and therefore do not decrease the total occurrence of severe environments Evidences are: robust across a sequel of climate models & occur in response to moderate g-warming

28 Classified modelling approaches into 2: explicit and implicit Explicit approaches: use horizontal and vertical resolutions that permit an explicit representation of deep convective storms and their implied characteristics Con: limited to short integrations of a single model or simulations of individual events over relatively small computational domains Implicit approaches: (Covariates?) examine atmospheric environments that are known to support severe thunderstorm formation in the current climate Con: arguments around decreasing Shear creates uncertainty about the response of severe thunderstorm

29 Here (use mplicit approach) to analyze severe thunderstorm environments in Coupled Model Intercomparison Project, Phase 5 (CMIP5) global climate model ensemble Focus on representative concentration pathway (RCP) 8.5 this covers the full range of 21st century radiative forcing and global warming spanned by the illustrative RCPs Defined a severe Thunderstorm day =vertical wind Shear(over a 6km layer, S06) CAPE

30 Results Introduction Ensemble-mean number of days with severe thunderstorm environments (NDSEV) increases over the eastern US. in all 4-seasons in response to the RCP8.5 forcing pathway (below: Fig. 1) Winter (DJF) exhibits the largest relative increase in regional mean NDSEV Spring (MAM) exhibits the most consistent response across the ensemble, with all models exhibiting positive multidecadal anomalies

31 Evidence of spatial pattern and seasonal variations of NDSEV changes: largest and most robust increases in occur over central US in spring(fig B)

32 The NDSEV changes in are linked with ensemble-mean increases in seasonal CAPE and ensemble-mean decreases in seasonal Shear(S06) for all nearly areas and seasons (below: Fig. 2)

33 Changes in CAPE and Shear in the different seasons may be explained in part by changes in the Vertical structure of the atmosphere(fig. 3) negligible change in spring(mam)-season zonal wind below 8 km -> explain lack of robust change in spring S06 (Fig. 2F) robust decreases in summer(jja)-season zonal wind around 6 km -> explain the robust decrease in summer S06 (Fig. 2G) robust warming below 300 mb ( 9 km) over the eastern US + robust increases in specific humidity at lowest atm levels

34 The influence of changing CAPE and Shear on total # of days with severe environments arise from changes in daily-scale combinations of CAPE and shear (Fig. 4) Difference in daily-scale CAPE-Shear distribution between the and periods reveals that daily CAPE-S06 distribution shifts toward increasing occurrence of high CAPE in spring, summer, and autumn: So 1 The occurrence of days in which NDSEV threshold is met increases 2 The number and fraction of severe days (SEVs) that exhibit high CAPE increases

35 Decreases in S06 are concentrated almost entirely in the low-cape/high-shear portion of the CAPE-S06 distribution Implication: Since severe environments require sufficient levels of both CAPE and Shear, loss of high-shear days at very low levels of CAPE has no effect NDSEV occurrence (see black curves).therefore NDSEV increases over the eastern U.S. in all four seasons