气候变化背景下人工造雪技术提升对中国滑雪季节长度的影响

doi:10.18402/resci.2020.06.17

资源科学 ›› 2020, Vol. 42 ›› Issue (6): 1210-1222.doi: 10.18402/resci.2020.06.17

• 旅游资源 • 上一篇

气候变化背景下人工造雪技术提升对中国滑雪季节长度的影响

方琰¹(), DanielScott², RobertSteiger³, 吴必虎⁴(), 蒋依依¹

1.北京体育大学体育休闲与旅游学院,北京 100084
2.滑铁卢大学地理与环境管理学院,加拿大安大略 N2L3G1
3.因斯布鲁克大学公共财政系,奥地利因斯布鲁克 526020
4.北京大学城市与环境学院旅游研究与规划中心,北京 100871

收稿日期:2019-07-25 修回日期:2020-01-16 出版日期:2020-06-25 发布日期:2020-08-25
通讯作者: 吴必虎
作者简介:方琰,女,江西上饶人,师资博士后,博士,主要从事气候变化与旅游、冰雪产业研究。E-mail: yanfang113@126.com
基金资助:
北京体育大学校自主课题(校2020027);北京体育大学高层次人才科研启动项目“中国冰雪运动与文化旅游产业协同路径研究”

Impact of snow-making technology improvement on ski season length in China under climate change

FANG Yan¹(), Daniel SCOTT², Robert STEIGER³, WU Bihu⁴(), JIANG Yiyi¹

1. School of Recreational Sports and Tourism, Beijing Sport University, Beijing 100084, China
2. Geography and Environmental Management, University of Waterloo, Waterloo, Ontario N2L3G1, Canada
3. Department of Public Finance, University of Innsbruck, Innrain 526020 Innsbruck, Austria
4. International Center for Recreation and Tourism Research, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China

Received:2019-07-25 Revised:2020-01-16 Online:2020-06-25 Published:2020-08-25
Contact: WU Bihu

摘要/Abstract

摘要：

在全球气候变暖背景下,人工造雪是滑雪场经营者有效应对气候变化的重要措施。本文假定人工造雪适宜温度由现有的-5℃提升到-2℃,基于气象站点观测数据（1981—2010年）和IPCC AR5的RCPs未来情景数据,通过改进的SkiSim 2.0模型评估气候变化背景下人工造雪技术提升对中国滑雪季节长度的影响。研究表明：①在气候变化背景下,人工造雪技术提升将使得中国平均滑雪季节长度增加3%~12%,即使在2080s时期最高温室气体排放情景下（RCP 8.5）,78%的滑雪场能拥有超过100 d的滑雪季节长度;②受气候变化影响越大的滑雪场（如华北、华东、华中）,人工造雪技术提升使其滑雪季节长度增加越多;而人工造雪技术提升对受气候变化影响小的滑雪场（如东北、西北）作用有限;③地理环境条件是影响滑雪季节长度的根本因素,无论人工造雪技术是否提升,气候变化背景下中国100 d滑雪季节长度的地理分界线均为长白山—阴山—祁连山—天山。为适应及减缓气候变化的潜在影响,相关部门应致力于提升人工造雪技术,从供给侧保证中国滑雪旅游产业的可持续发展。

关键词: 气候变化, 滑雪场, 技术提升, 减缓措施, SkiSim 2.0, 中国

Abstract:

Under global warming conditions, artificial snowmaking has proved to be an effective adaptation measure to climate change for ski resorts. Based on the surface climate dataset (1981-2010) and new Intergovernmental Panel on Climate Change (IPCC) RCPs scenarios, this study assessed the impact of snow-making technology improvement (snow could be produced at -2℃ rather than -5℃) on ski season length in China under climate change using the SkiSim 2.0 model. The results show that average ski season length in China would increase by 3%~12% with improved snowmaking machine, and 78% of ski areas in China could maintain a ski season of over 100 days even under the RCP 8.5 scenario in the 2080s. Ski resorts that are highly affected by climate change (for example, north, east and central regions) would receive more benefits from new technology than slightly affected areas (for example, northeast and northwest). Furthermore, geographical environmental conditions are the fundamental factors that affect the length of ski season. No matter whether snow-making technology is improved or not, the dividing line for 100-day ski season in China under climate change is Changbai Mountain-Yinshan Mountain-Qilian Mountain-Tianshan Mountain. For mitigating and adapting to climate change, more attention should be paid to technological innovation in artificial snowmaking to ensure sustainable development of China’s ski industry from the supply side.

Key words: climate change, ski resort, technology improvement, mitigation measures, SkiSim 2.0, China

方琰, DanielScott, RobertSteiger, 吴必虎, 蒋依依. 气候变化背景下人工造雪技术提升对中国滑雪季节长度的影响[J]. 资源科学, 2020, 42(6): 1210-1222.

FANG Yan, Daniel SCOTT, Robert STEIGER, WU Bihu, JIANG Yiyi. Impact of snow-making technology improvement on ski season length in China under climate change[J]. Resources Science, 2020, 42(6): 1210-1222.

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参考文献 41

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度日因子/（mm ℃^{-1 .}d^-1）	区域	文献
1.4~6.9	中国东北（洮儿河流域）	尹雄锐等^[23]
3.1	乌鲁木齐河源1号冰川	刘时银等^[24]
3.4	天山（琼台兰冰川）	张勇等^[22]
5.9	横断山
8.5	唐古拉山（冬克玛底冰川）	谯程骏等^[25]
5.3	扎当冰川	吴倩如等^[26]
1.7	河西内陆河流域（石羊河）	高鑫等^[27]
4.0	河西内陆河流域（黑河）
2.4	河西内陆河流域（北大河）
3.4	河西内陆河流域（疏勒河）
4.1	河西内陆河流域（党河）

气温/℃	区域	文献
1.9~6.0	中国	韩春坛等^[28]
1.0~7.8	中国	Chen等^[29]
0.0~2.0	长江源区	刘俊峰等^[30]
0.0~3.0	三江源区	冯曦等^[31]
0.0 (1000 hPa)	北京	张琳娜等^[32]
-4.0 (850 hPa)
1.9~5.7	天山	张雪婷等^[33]

参数	设置	资料来源
滑雪所需的积雪深度（包括自然降雪和人工造雪）	30 cm	访谈;Scott等^[15];Abegg等^[34]
人工造雪时期	11月1日—次年4月1日	访谈;网络资料^?
人工造雪适宜温度	-5℃（现有）/-2℃（提高）	访谈;Snowathome^[5]
人工造雪量	10 cm/d	访谈;Steiger^[14]

气候变化背景下人工造雪技术提升对中国滑雪季节长度的影响

Impact of snow-making technology improvement on ski season length in China under climate change

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区域	省份	RCP 4.5							RCP 8.5
		2020s		2050s		2080s			2020s		2050s		2080s
				现有技术	提升技术		现有技术	提升技术		现有技术	提升技术		现有技术	提升技术	现有技术	提升技术	现有技术	提升技术
华北	北京	-19	-7	-61	-21	-80	-39		-22	-8	-79	-37	-97	-86
	山西	-8	-4	-23	-11	-40	-16		-8	-5	-40	-17	-68	-54
	天津	-5	-4	-14	-10	-22	-15		-6	-5	-23	-16	-64	-35
	内蒙古	-1	-1	-4	-4	-6	-6		-1	0	-6	-6	-13	-12
	河北	-7	-3	-15	-7	-20	-13		-7	-2	-19	-13	-31	-27
东北	黑龙江	-1	-1	-4	-3	-5	-4		-2	-1	-6	-5	-10	-8
	吉林	-2	-1	-5	-3	-9	-6		-2	-1	-9	-5	-17	-14
	辽宁	-4	-4	-13	-10	-19	-13		-6	-5	-19	-14	-33	-32
西北	新疆	-2	-2	-5	-4	-7	-6		-2	-2	-8	-6	-16	-13
	甘肃	-5	-3	-9	-8	-13	-12		-4	-3	-13	-11	-25	-22
	宁夏	-3	-3	-10	-10	-14	-14		-3	-4	-14	-14	-30	-25
	青海	-1	-1	-5	-4	-8	-6		-6	-2	-8	-6	-21	-17
	陕西	-8	-5	-23	-11	-34	-17		-9	-6	-36	-17	-65	-41
华东	山东	-18	-7	-54	-23	-76	-39		-23	-7	-75	-38	-95	-85
华中	河南	-21	-8	-51	-20	-66	-33		-22	-8	-68	-35	-92	-75

区域	省份	RCP 4.5			RCP 8.5
区域	省份	2020s	2050s	2080s	2020s	2050s	2080s
华北	北京	29	47	45	31	46	12
	山西	13	22	34	13	33	20
	天津	8	11	15	9	15	35
	内蒙古	4	5	5	6	5	7
	河北	15	20	17	15	17	12
东北	黑龙江	4	4	5	4	4	6
	吉林	5	7	7	5	9	8
	辽宁	11	14	16	12	16	10
西北	新疆	5	6	7	5	7	8
	甘肃	10	10	9	10	10	11
	宁夏	11	11	10	11	11	15
	青海	5	7	8	6	8	10
	陕西	13	23	29	14	31	34
华东	山东	32	41	41	34	41	11
华中	河南	32	42	41	32	41	19

[1]	赵娜娜, 王志宝, 李鸿梅. 中国能耗模式演变及其对经济发展的影响[J]. 资源科学, 2021, 43(1): 122-133.
[2]	纪晓萌, 秦伟山, 李世泰, 刘肖梅, 王秋贤. 中国地级单元旅游业发展效率格局及影响因素[J]. 资源科学, 2021, 43(1): 185-196.
[3]	刘传瀛, 黄季夏, 王利, 杨林生, 葛全胜. 俄罗斯滑雪场空间格局及可达性[J]. 资源科学, 2021, 43(1): 197-208.
[4]	孙艺璇, 程钰, 刘娜. 中国经济高质量发展时空演变及其科技创新驱动机制[J]. 资源科学, 2021, 43(1): 82-93.
[5]	韩璟, 陈泽秀, 卢新海. 中国海外耕地投资发展的时空格局演变与影响因素[J]. 资源科学, 2020, 42(9): 1715-1727.
[6]	王萍萍, 韩一军, 张益. 中国农业化肥施用技术效率演变特征及影响因素[J]. 资源科学, 2020, 42(9): 1764-1776.
[7]	罗屹, 苗海民, 黄东, 武拉平, 朱俊峰. 农户仓类设施采纳及其对玉米储存数量和损失的影响[J]. 资源科学, 2020, 42(9): 1777-1787.
[8]	周美静, 黄健柏, 邵留国, 杨丹辉. 中国稀土政策演进逻辑与优化调整方向[J]. 资源科学, 2020, 42(8): 1527-1539.
[9]	董娟, 郑明贵, 钟昌标. 中国稀土产业发展财政支持效应及其影响因素[J]. 资源科学, 2020, 42(8): 1551-1565.
[10]	杨宇, 何则. 中国海外油气依存的现状、地缘风险与应对策略[J]. 资源科学, 2020, 42(8): 1614-1629.
[11]	侯娟, 周为峰, 王鲁民, 樊伟, 原作辉. 中国深远海养殖潜力的空间分析[J]. 资源科学, 2020, 42(7): 1325-1337.
[12]	张博胜, 杨子生. 中国城乡协调发展与农村贫困治理的耦合关系[J]. 资源科学, 2020, 42(7): 1384-1394.
[13]	张雯熹, 邹金浪, 吴群. 生产要素投入对城市土地利用效率的影响——基于不同工业化阶段省级数据[J]. 资源科学, 2020, 42(7): 1416-1427.
[14]	闫庆友, 桂增侃, 张文华, 陈立忠. 中国能源影子价格和能源环境效率省际差异[J]. 资源科学, 2020, 42(6): 1040-1051.
[15]	郑德凤, 王燕燕, 曹永强, 王燕慧, 郝帅, 吕乐婷. 基于生态系统服务的生态福祉分类与时空格局——以中国地级及以上城市为例[J]. 资源科学, 2020, 42(6): 1110-1122.