Council Communication

Mt. Ashland Lease analysis Meeting Date: SS 9-6-06 Department: Legal Contributing Departments: Approval: Martha Bennett

Primary Staff Contact: Michael W. Franell E-mail: franellm@ashland.or.us Secondary Staff Contact: E-mail:

Estimated Time: Statement: On August 15, 2006, Cate Hartzell sent the attached letter to the legal department asking several questions in regard to the Mt. Ashland Ski Area lease agreement. This memorandum will try to answer most of those questions.

1. what liability could the City of Ashland have in relation to compliance with the U.S. Forest Service requirements on Mt. Ashland?

The property on which the ski area is located is owned by the United States government and managed by the U.S. Forest Service. The City of Ashland acquired the rights of the special use permit at the time it acquired the right to operate the ski area. All of the City of Ashland’s rights and responsibilities in the ski area are contained within the terms of the Special Use Permit. As the permit holder, the City of Ashland is the party primarily responsible for compliance with the terms of the Special Use Permit. The lease with MAA provides that MAA will be responsible for compliance with the terms and conditions of the Permit. So long as the lease agreement is operative, MAA agrees to indemnify and hold the City harmless for its failure to comply with the terms and conditions of the lease. The biggest risk of liability for the City of Ashland occurs in the event the lease agreement is no longer operative. There are not any survivorship provisions in the lease agreement for MAA’s responsibility for compliance with the terms and conditions of the permit. Therefore, if the lease agreement is no longer valid, neither is MAA’s responsibility for compliance with the permit terms and conditions. To hedge the liability to the City, the lease agreement made two provisions: 1) The lease agreement provides in section 2.1.6 that MAA shall maintain a minimum liquidation value in the assets which revert to the City upon termination of the lease. This value was initially set at $200,000 with a CPI escalator each year. 2) The agreement made provision for a trust fund to be set up and maintained into which regular deposits would be made. The initial contribution was to be made by the City. To my knowledge, the decision was subsequently made to distribute all of the initial funds to MAA to help with start up costs and a trust fund has never since been established. Therefore, the most likely substantial risk of exposure to the City would be in the event of a termination of the special use permit. Section 1 of the lease indicates termination of the permit also terminates the lease. To the extent the costs of required restoration under the permit terms exceed the liquidation value of the assets on the mountain, the City would be responsible.

2. Next you ask if the lease has any provisions for renegotiation in the event of a change in the City’s status as Special Use Permit (SUP) holder.

The answer is no. If the City is no longer the SUP holder, the lease terminates. The lease does not contain any anticipation of other changes in the status of the City being the SUP holder.

3. The next question you pose is whether cutting down the trees in the area of the proposed expansion could be considered to require the written permission of the City under Section 6.1 of the lease.

I believe the answer to your question is no. The operative portion of the lease reads:

Lessee without the written consent of Lessor which consent shall not be unreasonably withheld shall not tear down or materially demolish any of the improvements upon the Permit Property or make any material change or alteration in such improvements which when completed would substantially diminish the value or substantially alter the use of the Leased Property. (emphasis added).

The prohibition applies only to “improvements” on the property. Blacks law dictionary defines improvement as

“A valuable addition made to property (usually real estate) or an amelioration in its condition, amounting to more than mere repairs or replacement, costing labor or capital, and intended to enhance its value, beauty or utility or to adapt it for new or further purposes. Generally has reference to buildings, but may also include any permanent structure or other development, such as street, sidewalks, sewers, utilities, etc. . . .”

The emphasis in the definition is on development, primarily a building or structure. I don’t think the courts would consider the trees naturally existing on the property to be improvements to which the requirement to obtain permission applies. Especially since the first part of section 6.1 provides:

Except as herein provided Lessee may at Lessee’s expense make such alterations improvements additions and changes to the Leased Property as it may deem necessary or expedient in the operation of the Leased Property

granting them explicit authorization to make alterations, improvements or additions.

4. The final question that you pose is who gets the sale value of the timber that would be cut if the expansion proceeds?

I believe there is good argument that the City should be entitled to the proceeds. Paragraph 5 of the lease provides:

Title to Assets. Throughout the entire Lease term the Permit Property and the Equipment shall be and remain the property of the Lessor. “Permit Property” is not defined within the lease agreement, but it is differentiated in the paragraph from the equipment. Therefore, I believe a valid argument can be made the Permit Property refers to interest in the land which includes an interest in the timber. Attachments: Copy of letter from Cate Hartzell, dated August 15, 2006.

September 6 2006

To Ashland City Council

From Tom Rose

430 Wiley St

Ashland OR 97520

Re Mt Ashland Study Session Sept 2005 Resolution

As I amunable to attend the meeting tonight I amasking that this letter be read into the publicrecord

I strongly urge the Council to fmd that the Mt Ashland Association has failed tomeet the goalsof the September 2005 Resolution in the following ways

1 Restoration The Mt Ashland Association and the Forest Service have made no effort to

estimate the cost ofrestoration ofthe current ski area plus the expansion area The Forest

Service maintains that 200 000 is adequate That figure is at between 12 to 110 ofthe actual

cost of restoration

2 Business Plan The one page document submitted to the City by the Mt Ashland Association

in no way complies with the request of the City regarding a Business Plan The document does

not as requested

Project construction expenditures for each year of the expansion build out

Instead the document only discusses the cost for Phase 1 The estimated 3 7 million cost is

1 6 million more than a fund raising study said the MAA could reasonably expect to raise

Nevertheless the MAA s document states that they will fund raise 3 2 million This is totallyunsupported and has no basis in fact Nothing is said about the remaining 133 million needed

to complete the expansion How will Phase 2 and 3 be funded How can the ski area build runs

add a lift project a 50 increase in visitation and not build the infrastructure required for these

additional visitors The reality is that the MAA cannot fund the entire project and cannot even

fund Phase 1 with any reasonable expectation Why

The MAA has lost money for all or nearly all ofthe past five years and will not be able

to put annual revenues towards the project simply because there are no annual revenues

lIi

The MAA s cash available for expansion has dwindled toa few hundred thousand

dollars from a high of 14 million in 1992

The MAA has never explained how they will pay for the expansion not in the EIS andnot in the document that they have provided toyou

The MAA has become very shy about their finances Where historically theypublished their revenues and expenditures in their newsletter the Mountain Voice and

supplied the City and the State with their Accountants Review Reports in a timelymanner they no longer do so They are not evenwilling to share a reasonable businessplan with the City

This is important because the MAA s inability to complete the entire project or even Phase 1 isin doubt Their inability tocomplete the project only makes it more likely that the City willhave tospend hundreds ofthousand ofdollars maybe even millions of taxpayers money to

dismantle the ski area and restore the municipal watershed

Project sources of funds for rmancing the expansion for each year ofthe buildout

You won t find this in the document The proposed fundraising is unreasonable and the

documents leaves out how they will pay for the remaining 15 million cost

Projected operating revenues and expenses reflecting historic skier visitation

variability for at least a 10 yeartime frame during and after the expansion buildout

There is nothing in the document regarding historic skier visitation variability Instead thedocument assumes a straight line increase with no off years This is financially imprudent and

historically inaccurate The Ski Area has either gone bankrupt andor been sold at least threetimes due to the variability ofskier visitation Just this year MAA has announced visitation10 lower than last year Yet the MAA did not find it prudent to consider historic variabilityin their financial calculations

Sources of funding for financing restorationrehabilitation reserves

Nothing Does MAA even have the money to finance these reserves If so then why don t

they do so adequately so that the taxpayers ofAshland are adequately protected

Sources of funding for rmancing the QAlQC team

Nothing

3 OAlOC Team

Nothing has been done to implement the QAlQC team portion of the Resolution Hiring Michael

Hogan in no way meets this requirement

I strongly urge you toprotect the taxpayers ofthe City ofAshland Tell MAA not to proceedwith cuttingconstruction prior to the City certifying that the MAA has complied with all partsofthe September 2005 Resolution and that the City finds that the Business Plan and Restoration

Plan adequately protect the City from financial liability Lastly the QAlQC team must have

been formed as per the staff report and approved all ofthe construction plans and other

construction related documents prior tocuttingconstruction taking place

Thank you very much

Tom Rose

September 6 2006

TO ASHLAND CITY COUNCIL

FROM TOM DIMITRE

The Mt Ashland Association on 815 told the City Council that they could begin cutting the skiruns in the expansion area as early as 9 15 and that they would take the advice oftheir attorneyon whether or not to proceed at that time

This is disingenuous and shows that the MAA is not willing to work as apartner with the CityProceeding prematurely as proposed puts Ashland taxpayers at risk in at least 6 ways

I The proposal puts taxpayers at risk because the MAA has publicly stated that they plan to

proceed clearcutting ski runs PRIOR to the court case being decided by the local court and

appellate court Leslie Adams provided the Council with an example of the problem this maycause 35 acres of clearcuts in the watershed and acourt injunction prohibiting further cuttingWho will pay for cleaning up this mess and the rehabilitation and restoration that would be

required My guess is the City

2 The proposal puts taxpayers at risk because the MAA has not raised the 3 4 million

required for Phase 1 construction nor 17 for the entire project They have clearly stated that

they plan to begin loggingconstruction before they have raised any money Beginning aprojectwithout full financing in place risks an incomplete project The City should insist that the MAAshow that full funding 17 million is in place IfMAA is unable to fundraise or otherwiseobtain loans or other fmancing the City will be on the hook for the rehabilitation and restorationcosts While Mr Little told you what would not be used to pay for the expansion what the

City taxpayers skiers and the rest of us are waiting to hear is how MAA IS going to pay for theentire expansion The information provided by the MAA does not answer this questionTaxpayers and the City have aright to know

3 The proposal puts taxpayers at risk because the MAA has not complied with Resolution2005 35 The Resolution would help ensure to the City s satisfaction that the MAA expansionplan is financially sound The City requested aBusiness Plan Instead the MAA has providedthe City with one page that answers none ofthe questions in the Resolution provides no

assurance that the MAA can finance any phases in the expansion provides no basis for revenue

projections doesntaccount for variability in skier visitation a historic fact and also does not

project expenses and revenues over ten years The MAA has completely failed to comply withthe City s request Allowing the MAA to proceed with loggingconstruction without theinformation requested being received and analyzed puts City taxpayers at risk and is not fiscally

responsible

4 The MAA has put City taxpayers at risk because it has not agreed to increase the amount set

aside for restoration funding Instead the historic figure of 200K is still being used It is clearthat 200K is woefully inadequate This unreasonably low amount again puts the Citytaxpayers at risk

5 The MAA has lost money for all ofmost ofthe past five years and is in no position to fund

an expensive expansion again putting City taxpayers at risk

6 Proceeding to commence logging without a QAQC team as proposed in the staff report andwithout the QAQC team analyzing the Operations Plan Erosion Control Plan and Stormwater

Management Plan and other construction documents and plans again puts the taxpayers at risk

As of two weeks ago none of these plans had evenbeen submitted to the Forest Service

The MAA has made it clear that they are going to proceed tobegin clearcutting runs in the

watershed despite their failure toprovide information that their expansion plan will not puttaxpayer money at risk In fact they have gone so far as to try and bully the council with claims

that the City is interfering in their business This is hogwash The City and City Council must

act firmly and decisively to protect taxpayer money by adopting in full City staff s excellent

recommendations I urge you toadopt Staff s fmdings and to send a very strong message to the

MAA that they should not proceed prior tocomplying with Resolution 2006 35 and the Staff

Report

Thank you

PREPRINT VERSIONThis paper has been accepted for publication in the The Joumal of

Hydrometeorology The official version of this paper will be the one that ispublished and may be contain minor edits that do notappear in this

version of the paper

Mapping At Risk Snow in the Pacific Northwest U S A

Anne W Nolin and Christopher Daly

Oregon State University Corvallis Oregon USA

Submitted 30 September 2005

RevisedJanuary 19 2006

Accepted January 30 2006

Correspondence to

Anne W Nolin

Department of Geosciences

Wilkinson 104

Oregon State University

Corvallis OR 97331 U S A

Email nolina fcscicn orcgonstate cdu

Phone 541 737 8051

Fax 541 737 8051

1

ABSTRACT

One of the most visible and widely felt impacts of climate warming is the change mostly loss

of low elevation snow cover in the mid latitudes Snow cover that accumulates at temperatures

close to the ice water phase transition is at greater risk to climate warming than cold climate

snowpacks because it affects both precipitation phase and ablation rates This study maps areas

in the Pacific Northwest region of the United States that are potentially at risk of converting

from a snow dominated to a rain dominated winter precipitation regime under a climate

warming scenario We use adata driven climatological approach ofsnow cover classification to

reveal these at risk snow zones and also to examine the relative frequency of warm winters for

the region For a rain vs snow temperature threshold of OoC the at risk snow class covers an

area ofabout 9200 km2 in the Pacific Northwest region and represents approximately 6 5 km3 of

water Many areas ofthe Pacific Northwest would see an increase in the number ofwarm winters

but the impacts would likely be concentrated in the Cascade and Olympic Ranges A number of

lower elevation ski areas could experience negative impacts because of the shift from winter

snows to winter rains The results of this study point to the potential for using existing data sets

to better understand the potential impacts of climate warming

Keywords climate change snow hydrology PRISM PacificNorthwest

2

1 Introduction

One of the most visible and widely felt impacts ofclimate warming is the change mostly

loss of low elevation snow cover in the mid latitudes Temperature trends in the northwestern

United States show a warming of 1 20C since the middle ofthe last century and related declines

in snow cover Karl et at 1993 Lettenmaier et at 1994 Changes in snow cover are particularly

pronounced in the Pacific Northwest region ofthe United States Using measurements ofApril 1

snow water equivalent SWE dating back to 1950 Mote et at 2005 noted that the Pacific

Northwest has experienced the largest declines in snowpacks in the western United States This

change can be primarily attributed to an increase in winter temperatures Mote 2003 Mote et at

2005 Phenological shifts of earlier blossoming as well as earlier spring snowmelt are further

evidence ofa winter warming trend in the region Cayan et at 2000 Stewart et at 2004 2005

examined discharge data from 1948 2000 and found a 9 to 11 day earlier snowmelt runoff in the

Pacific Northwest that they attributed to an increase in winter temperatures It is important to

recognize that all of the trend analyses discussed above were limited to the latter half of the

twentieth century because data were generally insufficient before about 1950 Given that

climatic conditions within this fifty year period exhibited complex and non linear variations over

various time scales it is unclear how representative the reported trends would be for different

time periods both past and future

Climate impacts on snow hydrology are important throughout the western United States

but Pacific Northwest water budgets are particularly sensitive because total annual precipitation

is highly concentrated in the winter months Furthermore snow cover that accumulates at

temperatures near OoC is at greater risk to climate warming than cold climate snowpacks because

temperature affects both precipitation phase snow vs rain and the rate of snowpack ablation

3

Wanner winter temperatures will lead to more of the precipitation falling as rain than as snow

and earlier snowmelt Changes in such climatologically sensitive winter precipitation can impact

management strategies for reservoir storage and hydropower generation the frequency of rain

on snow floods and winter recreation

Climate models are in general agreement that temperatures will continue to rise over the

next century Future climate scenarios show continued rising winter temperatures in the Pacific

Northwest with estimates ranging from 0 2o6C per decade Mote et al 2003 As we

endeavor to gage the potential consequences of climate change we need to understand the

impacts not only on a regional scale but also on watershed scales For many applications climate

model output is too coarse and even the downscaled hydrologic simulations are at resolutions no

finer than 10 kIn Mote et al 2005 Furthermore the projected temperature changes would not

be uniform from year to year and need to be understood in the context of the relative frequency

ofwanner winters

With this in mind the goals ofthis investigation are to

1 Map areas of seasonal snow cover in the Pacific Northwest that are at risk of converting

to arainfall dominated winter precipitation regime under projected climate warming

2 Quantify the current and projected relative frequencies of warm winters in the Pacific

Northwest

The data and methodology used are described in section 2 Section 3 describes and discusses the

results from the decision tree classification the relative frequency analysis and implications for

ski resorts in the region Results are summarized in section 4

2 Data and Methodology

4

a Justificationfor using asnow classification approach

A climatologically based classification of seasonal snow covers provides a physically

based and widely applicable means ofcharacterizing snow classes Sturm et at 1995 developed

a snow classification system that uses temperature precipitation and wind speed as the relevant

climate parameters for discriminating snow classes Values of temperature and precipitation are

easily obtained but accurate wind speed data are generally not available and therefore they used

vegetation type as aproxy for wind speed Sturm et at reasoned that the presence or absence of

trees determined whether or not and area is a low or high wind environment It is well

established that wind speeds typically decrease as vegetation density increases Pomeroy and

Gray 1995 Sturm et at 2001 Walker et at 2001 Essery and Pomeroy 2004 For instance wind

speed is the factor that distinguishes between the taiga boreal forest wind speeds ofless than

0 2 m Sl and tundra low tussocks wind speeds of 2 to 5 m S

isnow classes Validation of

this classification system showed that these three variables related closely to the physical

properties of the snowpack This original classification was produced globally at 0 50 x 0 50

resolution

Aside from producing maps of snow cover classes a climatologically based snow cover

classification system can also be used to explore how changes in climate might alter the

distribution of snow classes Of particular interest in the Pacific Northwest is the distribution of

maritime snow that is areas with high snowfall but relatively warm winter temperatures Within

the classification of Sturm et at maritime snow falls into a winter precipitation regime of

greater than 2 mm day1 and high winter temperatures near OOC For this class wind speed is

not a relevant parameter because it does not significantly influence snowpack physical properties

such as density and depth

5

Using climate data to classify snow cover types provides an additional advantage in that

it allows one to test the impacts of projected temperature change on Pacific Northwest snow

packs By imposing projected changes in temperature on the climate data one can examine the

potential effects ofclimate change at higher resolution In this study we use aprojected climate

change of 2 0oC well within the projected range ofincrease of 1 5 3 20C by the year 2040 for

the Pacific Northwest Mote et al 2003 The Pacific Northwest region as defined in this study

includes the states of Oregon Washington Idaho and western Montana Figure 1 Below we

describe the data sets decision tree classification method and a frequency analysis used to better

understand possible changes in interannual variability

FIGURE 1

b Precipitation and temperature data

We extend the work ofSturm et al by using the Parameter elevation Regressions on

Independent Slopes Model pRISM data set Daly et al 1994 2002

http wwwocs oregonstate edulprismThis is awidely used high quality topographically

sensitive data set ofprecipitation and temperature with agrid resolution of2 5 min 4km two

orders ofmagnitude higherspatial resolution than the original snow classification

We used historical monthly averages ofmean temperature and precipitation for

December January and February from 1971 2000 PRISM provides values for mean monthly

maximum temperature Tmax and mean monthly minimum temperature Tmin and from this we

computed the monthly mean temperature Tmean where Tmean Tmin Tmax 2

c Vegetation cover data

Since 2000 global maps ofvegetation cover fraction have been produced using data from

the Moderate Resolution Imaging Spectroradiometer MODIS Hansen et al 20003 These

6

vegetation cover fraction maps provide measures of percent tree cover for each 500 m grid cell

and have been aggregated to the 4 km PRISM resolution For inferring high wind vs low wind

snow environments tree cover fraction is preferred over biome maps which provide no

information on forest density For completeness we have produced a full snow cover

classification that includes temperature precipitation and wind speed

d Decision tree classification and thresholds

The new seasonal snow cover classification can be readily applied using a decision tree

approach a binary classification system that assigns classes based on whether the snow exists in

a cold or warm climate a wet or dry climate and awindy or calm climate The structure ofthe

decision tree is shown in Figure 2 and the threshold values are listed in Table l

To discriminate whether agrid cell is considered to have any accumulation of seasonal

snow it must have a mean monthly temperature ofless than or equal to a selected temperature

threshold for each ofthe core winter months December January February DJF This is the rain

vs snow threshold temperature and for individual storms is not a constant value and depends on

a variety ofcomplex factors Snow can fall at temperatures above OoC such as when a cold

precipitating layer lies above a warmer surface layer In this case latentheat exchange caused by

the melting snowflakes near the ground will lead to cooling ofthe lower layer other factors

aside Conversely rain can fall at temperatures below OoC such as when a warmer precipitating

layer lies above astable cold layer at the surface This freezing rain phenomenon is a self

limiting process because latent heat is released warming the cold layer to OoC Lackmann et at

2002 In this study we use monthly mean temperatures in which these transitory threshold

phenomena should average out However to address the inherent uncertainty in selecting a

single value we perform our analysis using a range ofrain vs snow temperature threshold

7

values from 2 0 to 2 0oC

For the high vs low winter precipitation threshold we use the Sturm etal value of2mm

dayI for each ofthe three corewinter months This allowed us to map areas where winter

precipitation is significant In the Pacific Northwest the majority ofprecipitation falls during the

winter and we are mainly concerned with changes in seasonal snow in areas where there is

significant precipitation A change in seasonal snow in a region ofhigh winter precipitation and

low summer precipitation is far more important than such achange in adrier climate or one that

has more of a balance ofwinter and summer precipitation

There is no clear evidence onthe density ofvegetation that is required to establish a low

wind environment Therefore for this study the threshold value is arbitrarily set at a forest cover

density of35

FIGURE 2

TABLE 1

e Relative Frequency Analysis

The impact of climate warming should be recognized within the context of climate

variability Indeed year to year variability in average winter temperature is typically larger than

the temperature changes projected by climate models Therefore we include a analysis of the

relative frequency ofwarm winters and use that as a guide to estimate the increased frequency of

warm winters in a projected climate warming scenario

Relative frequency is defmed as the number of times N an event occurs within a

number ofN trials and it is empirically similar to probability Thus the relative frequency ofan

event is N IN For the 30 year time series 1971 2000 we compute the average winter

temperature over the DJF period for each winter Gridded time series data were again obtained

8

from the PRISM data sets http wwwocs oregonstate eduprisml For each grid cell we

compute the relative frequency of winters with a mean temperature less than a specified

temperature threshold fC 0 50C 10oC 150C 2 fC This approach allows us to examine

the spatial variability ofwinter temperatures over the region and the number ofwarm winters for

arange oftemperature threshold values under the 20C projected climate warming scenario

3 Results and Discussion

a Snow Cover Classification

The decision tree classifier was implemented using the various thresholds listed in Table

1 Figure 3 shows the results of the snow cover classification for a rain vs snow temperature

threshold of OOC Shown in red is the area of snow cover representing that which is currently

maritime snow with an average winter temperature less than OOC but exceeding 2 0oC This

snow class represents the area that for a projected warming of 2 0oC would convert from

predominantly snowfall to predominantly rainfall The total area represented by this snow class

is 9200 knrz To consider this in terms of snow water equivalent we assume an annual average

peak SWE of 684 cm for this snow area This is amean value computed from the climatological

mean peak SWE values 1971 2000 of eleven SNOTEL sites that fall within the area covered

by this snow class For this temperature threshold the total volume ofwater represented by this

snow class as roughly 6 5 km3 Results for the other temperature threshold values are shown in

Figure 4 We see that the area of the at risk snow cover class ranges from a minimum of 6080

km2 for a rain vs snow temperature threshold of 2 0oC to a maximum of 10 832 km2 for a rain

vs snow threshold of 0 50C Figure 4 also shows that the area of the at risk snow cover class

comprises less than 2 5 of all snow cover in the region However at risk snow is

9

disproportionately concentrated in the Cascade Range Using the OoC threshold case as an

example 51 of all at risk snow in the Pacific Northwest is in the Oregon Cascades and 21 8

ofall snow covered area in the Oregon Cascades falls into the at risk snow class By comparison

12 5 of all snow covered area in the Washington Cascades is in the at risk category The

Olympic Range is another mountain region with a large proportion 61 of its snow covered

area in the at risk class

FIGURE 3

FIGURE 4

b Relative Frequency Analysis and Potential Impacts on the Ski Industry

Figure 5 shows the spatial variability of the relative frequency of winters with mean

temperatures below OoC As expected the mountain regions have a much higher frequency of

winters with a mean temperature below OoC than do lower elevations Figure 5 also shows the ski

areas in the region and while most ofthem are outside the at risk snow class anumber ofthem

negatively impacted by the projected warming Using the 30 year temperature record we

compute the relative frequency of warm winters Even for those ski areas that are outside the at

risk snow class there would be an increase in the frequency ofwarm winters InTable 2 we have

listed 19 ski areas in the Pacific Northwest that would experience asignificant number of warm

winters defined as having a relative frequency greater than 03 for the mean DJF temperature

exceeding 20C under a climate warming scenario The location of each ski area corresponds to

the center ofthe grid cell in which the main lodge is located In some cases the elevation of the

PRISM grid cell was significantly higher or lower than the base elevation ofthe ski area If the

elevation difference between the PRISM data and the base elevation ofthe ski area exceeded 100

m a search was performed within a radius of three grid cells to locate the cell with the closest

10

match to the ski area elevation Given that temperature is strongly influenced by elevation and

that there are uncertainties in the ski area location and DEM terrain representation selecting a

nearby grid cell with the closest elevation is likely to give a more accurate result than selecting

the grid cell with the closest geographic coordinates

There are a number of relevant questions to consider when assessing the potential

impacts of climate change on the ski resorts These include How will the projected changes

described earlier affect ski areas at different elevations and at different latitudes How would an

increase in the frequency ofwarm winters influence the number of skier days for particular ski

areas How would climate warming affect the length and quality of the ski season One might

also consider whether climate warming would have indirect but undesirable impacts such as an

increase in the frequency offorest fires in resort areas An economic assessment ofthese impacts

is beyond the scope ofthis research but this points to the need for further study of such potential

impacts

FIGURE 5

TABLE 2

Clearly this approach does not address potential changes in atmospheric circulation

patterns patterns of year toyear persistence or the effects of individual cold storms that may

occur within an otherwise warm winter However it does provide a rough idea of the projected

change in the number ofwarmerwinters for the region

4 Conclusions

A climatological approach to snow cover classification reveals not only patterns ofsnow

cover but also an area ofwinter precipitation and relatively warm snow temperatures that would

11

be at risk of converting to rainfall under a projected 20C winter warming While the impacts

depend on the rain vs snow temperature threshold that is used they are not insubstantial For a

rain vs snow temperature threshold ofOoC the at risk snow class covers an area of about 9200

km2 and represents approximately 6 5 km3 of water equivalent to about one third the volume of

Crater Lake Oregon While the fraction of total snow cover represented by this at risk class is

small overall it is concentrated in the western mountains of the study area particularly the

Cascade and Olympic Ranges This at risk area of snow cover is not well sampled by existing

SNOTEL or snow course sites and would benefit from additional regular measurements

Examination ofthe relative frequency of warm winters shows that in many parts of the

Cascade Range the number of warm winters is likely to increase significantly though not

uniformly over the Pacific Northwest region Socioeconomic impacts would include an increase

in the number of warm winters affecting ski resorts especially those at lower elevations where

the temperatures are generally warmer Additional impacts of these changes would likely be felt

in reduced mountain front recharge of groundwater and hence summer low flow levels in

streams and rivers ofthe region

The results of this data driven approach point to the potential for using existing data sets

to better interpret potential impacts of climate model output Furthermore such an approach can

help point the way for additional high spatial resolution modeling activities for watershed level

analysis and simulations that would allow estimates of projected changes in the frequencies of

warm vs cold winters

Acknowledgments This study was funded in part by agrants from USGS Water Resources

Research 20050R65B and NASA Cooperative Agreement NNG04GC52A PRISM data were

obtained through the Spatial Climate Analysis Service Oregon State University The 500 m

12

MODIS Vegetation Continuous Fields imagery were obtained through the University of

Maryland Global Land Cover Facility

13

References

Cayan D R S Kammerdiener M D Dettinger 1 M Caprio and D H Peterson 2001

Changes in the onset ofspring in the western United States Bull Amer Meteorol 82

399 415

Daly C R P Neilson D LPhillips 1994 A statistical topographic model for mapping

climatological precipitation over mountain terrain J Appl Meteorol 33 140 158

Daly C W P Gibson G H Taylor G LJohnson P Pasteris 2002 A knowledge based

approach to the statistical mapping ofclimate Climate Research 22 99 113

Essery R and J Pomeroy 2004 Vegetation and topographic control ofwind blown snow

distributions in distributed and aggregated simulations for an Arctic tundra basin J

Hydrometeorol S 735 744

Hansen M R DeFries J R Townshend M Carroll C Dimiceli and R Sohlberg 2003 500m

MODIS Vegetation Continuous Fields College Park Maryland The Global Land Cover

Facility

Karl T R P Ya Groisman R W Knight and R R Heim 1993 Recent variations ofsnow

cover and snowfall in North America and their relation to precipitation and temperature

variations J Climate 6 1327 1344

Lackmann G M K Keeter L G Lee and M B Ek 2002 Model representation of freezing

and melting precipitation Implications for winter weather forecasting Weather and

Forecasting 17 10161033

Lettenmaier D P E F Wood and J R Wallis 1994 Hydro climatological trends in the

continental United States 1948 88 J Climate 7 586 607

14

Mote P W 2003 Trends in snow water equivalent in the Pacific Northwest and their climatic

causes Geophys Res LeUs 30 DOl 1O 10292oo3GLOl7258

Mote P W E AParson A F Hamlet W S Keeton D Lettenmaier N Mantua E LMiles

D W Peterson D L Peterson R Slaughter A K Snover 2003 Preparing for climatic

change The water salmon and forests ofthe Pacific Northwest Climatic Change 61

45 88

Mote P W A F Hamlet M P Clark and D L Lettenmaier 2005 Declining mountain

snowpack in western North America Bull Amer Meteor Soc 86 39 49

Pomeroy 1 W and D M Gray 1995 Snowcover accumulation relocation and management

National Hydrology Research Institute Science Rep 7 Environment Canada Saskatoon

SK Canada 134 pp

Stewart 1 D R Cayan and M Dettinger 2004 Changes in snowmelt runoff timing in western

North America under a business as usual climate change scenario Climatic Change 62

217 232

Stewart 1 D R Cayan M D Dettinger 2005 Changes toward earlier streamflow timing

across western North America J Climate 18 11361155

Sturm M 1 Holmgren and G E Liston 1995 A seasonal snow cover classification for local to

global applications J Climate 8 1261 1283

Sturm M J P McFadden G E Liston F S Chapin III C H Racine and J Holmgren 2001

Snow shrub interactions in Arctic tundra Ahypothesis with climatic implications J

Climate 14 336 344

15

Walker D A W D Billings and J G de Molenaar 2001 Snow vegetation interactions in

tundra environments Snow Ecology H G Jones et aI Eds Cambridge University

Press 398 pp

16

List of Figures

Figure 1 Shaded relief locator map ofthe Pacific Northwest region used in this study

Figure 2 The decision tree structure used in the snow cover classification

Figure 3 Snow cover classification using a rain snow threshold ofOoC At risk snow is shown

in red

Figure 4 Total area ofat risk snow in the Pacific Northwest study area and the percent oftotal

snow covered area comprised by the at risk class for the different rain vs snow temperature

thresholds

Figure 5 Relative frequency ofwinters with amean DJF temperature less than O OoC with the

at risk snow cover class shown in red and ski areas indicated by the green dots

17

List of Tables

Table 1 Threshold values used in the decision tree classifier

Table 2 List ofPacific Northwest ski areas that are projected to experience asignificant increase

in the relative frequency ofwarm winters for arange of temperature thresholds

18

Map of Pacific Northwest Study Area

II o 137 5 275 550Kilometers D StudyArea

Figure 1 Shaded relief locator map ofthe PacificNorthwest region used in this study

19

All Data

Snow

No Snow

Maritime At Risk Snow

Lo WindHI Precl

HI wid I

I IWarm Snow

La WindLo Precip

Hi Wind

La WindHi Precip

Hi Wind

Cold Snow

La WindLo Precip

Hi Wind

Figure 2 The decision tree structure used in the snow cover classification

20

Snow Classification

Legend

snow free

cold snow low precip high Nind

cold snow low precip low wind

cold snow high precip lowwind

cold snow high precip high wind

wann snow low precip low wind

wann snow low precip high wind

wann snow hi precip

Figure 3 Snow cover classification using a rain snow threshold ofOoC At risk snow is shownin red

21

15000

14000

13000N

E12000

Jg 11000

ft

i 10000

ii9000

o

III 8000

fc

7000

6000

5000

2 5

of PNW snow at risk

area of PNW

at risk snow

2 15 1 0 5 0 0 5 1 15

Rain Snow Temperature Threshold oC

2 5

VI

2 ii

c

o15 U

Jocft

1

A

o

C

0 5 8CDa

2

o

2 5

Figure 4 Total area ofat risk snow in the PacificNorthwest study area and the percent ofPacificNorthwest total snow covered area comprised by the at risk class for the different rain vs snow

temperature thresholds

22

Relative Frequency of Mean DJF Temperature Less Than OOC

Legendrelative frequency

110at risk snow

ski areas

Figure 5 Relative frequency ofwinters with a mean DJF temperature less than O OoC with theat risk snow cover class shown in red and ski areas indicated by the green dots

23

Table 1 Threshold values used in the decision tree classifier

Criteria Threshold

ram VS snow DJF Tmean S 2 00C to 2 00C in 0 50 increments

cold snow VS warm snow climate rain VS snow threshold minus 20C

high VS low winter precipitation climate DJF Pmean 2mmday

low wind VS high wind climate tree cover fraction 35

24

Table 2 List ofPacific Northwest ski areas that are projected toexperience a significantincrease in the relative frequency ofwarm winten for a range of temperature thresholds

Relative frequency of winters with amean DJF

temperature exceeding

Ski Areas by Base

2 0 C 1SOC lO C O S C O OoC

Region Elevation m

Oregon Cascades

Timberline 1509 0 43 030 013 0 10 0 07

Mt Hood047 040 023 0 13 0 07

Meadows 1379

Mt Hood Ski Bowl 1082 0 73 0 63 0 63 053 0 30

Cooper Spur 1219 0 73 0 67 0 63 0 57 0 40

Hoodoo 1423 0 67 0 57 0 43 0 27 0 07

Mt Bachelor 1920 033 0 13 0 07 0 00 0 00

Willamette Pass 1561 0 67 0 50 037 027 0 03

Warner Canyon 1606 0 63 0 60 0 50 033 020

Mt Ashland 1935 0 40 040 0 27 0 17 0 07

Eastern Oregon and Washington

1

Spout Springs 1478 0 40 0 30 017 0 00 0 00

Mount Spokane 1164 057 0 53 0 50 033 027

Bluewood 1385 0 53 040 033 0 27 0 03

Washington Cascades

Mt Baker 1082 033 0 13 0 03 0 03 0 03

Mission Ridge 1393 037 0 27 017 0 07 0 07

Crystal Mountain 1341 0 47 027 013 0 03 0 00

White Pass 1372 0 47 030 0 20 0 07 0 00

The Summit at

057 0 53 0 43 033 027

Snoqualmie 866

Stevens Pass 1238 037 0 27 0 10 0 03 0 03

Olympic Range

Hurricane Ridge 1463 0 77 0 63 0 57 043 0 33

2

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