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LEST anyone doubt the speed with which a brush fire can strike, consider how rapidly flames engulfed Mati, a seaside resort near Athens, on July 23rd. Less than 90 minutes after fire was reported, flames had reached densely populated areas. Hordes of people fled into the sea, the only refuge, to escape. At least 91 were killed.如果有人置疑灌丛火灾蔓延的速度，那就想想 7月 23日发生在马蒂(Mati)的火灾。那天，这个雅典附近的海滨度假胜地转眼间就被大火吞噬。发现火情后不到 90分钟，大火就已经烧到了人口密集区。大海成了唯一的避难所，成群的人涌向海里逃生。至少 91人丧生。That toll could have been avoided, says Gavriil Xanthopoulos, a wildfire expert at Greeces Ministry of Rural Development and Food, if proper use had been made in advance of fire-simulation software. Fed with data on the areas vegetation, building materials, paved surfaces, paths to the sea and weather patterns, such software would have suggested, he says, those places where trees and brush should have been removed, roads widened and evacuation paths builtnot to mention how zoning laws could have been better devised in the face of fire risk.希腊农村发展和粮食部的山火专家加夫里尔克桑索普洛斯(Gavriil Xanthopoulos)表示，如果事先好好利用火灾模拟软件，这样的人员伤亡本可避免。他说，向这种软件输入该地区的植被、建筑材料、路面铺筑、通向大海的道路以及天气模式等相关数据，就能得到哪些地方该清除树丛、拓宽道路以及建设疏散路径的建议更不必说还能根据火灾风险设计更合理的区域规划法规。Greece, Dr Xanthopoulos laments, has been slow to adopt such software. Others are not so dilatory. Americas Forest Service, for instance, uses a model developed by Esri, a geographic-information firm in Redlands, California, to assess fire risk. This model feeds on data on the distribution and types of trees, bushes and other vegetable ground cover, and on construction materials used in an area.希腊迟迟没有采用这种软件，克桑索普洛斯很是痛惜。其他国家就没有如此拖拉。位于加州雷德兰兹市(Redlands)的地理信息公司 Esri开发了一种模型，被美国林务局用来评估火灾风险。这种模型以两类数据为依托：某一地区的树木、灌木和其他地被植物的类型与分布，以及该地区使用的建筑材料。These data are collected mainly by satellites and aircraft, but rangers and crews of firefighters contribute detail from the ground. According to Chris Ferner, a wildland-fire technology specialist at Esri, even entering the diameters of tree trunks and the sites of clogged culverts (which alter patterns of water flow) is grist to the softwares accuracy.这些数据主要由卫星和飞机收集，但也需要由护林员和消防队员提供地面细节。Esri 的野外火灾技术专家克里斯费尔纳(Chris Ferner)指出，即便录入的是树干直径和堵塞的涵洞(这些涵洞会改变水流的模式)位置，都能提高软件的准确性。Fire! Take aim.失火了!瞄准Once a piece of fire-forecasting software such as Esris knows how much inflammable stuff there is on the land, it can bring in data on rainfall, snowfall, sunshine, temperature and the like, to work out how this might change in the future, as well as how much moisture the vegetation holds. It can also take into account past fires and the lie of the land. A south-facing slope, for example, dries out faster (at least, in the northern hemisphere) than one facing north.一旦一款像 Esri这样的火灾预报软件了解了陆地上有多少易燃物，它便可以结合降雨、降雪、阳光、温度等数据计算出易燃物在未来的变化趋势，以及植被的含水量。软件同时还能把以往的火灾和地形等因素考虑进去。例如，南坡比北坡更容易变干，至少在北半球是如此。Another model, developed at the University of California, Santa Barbara, by Christina Tague, is called RHESSys. Dr Tague has loaded RHESSys with fuel- and moisture-data for roughly 800 square kilometres of wildland, most of it in California. This shows forestry officials where best to bulldoze fire breaks, cut down trees or clear scrub.加州大学圣芭芭拉分校的克里斯蒂娜塔格(Christina Tague)开发了另一个名为 RHESSys的模型。塔格向 RHESSys输入了约 800平方公里林野(大部分在加州)的易燃物及湿度数据，为林业官员指明最好在哪些地方开辟防火带、砍倒树木或者清除灌木丛。Rod Linn of Los Alamos National Laboratory, in New Mexico, who helped design yet another piece of modelling software, FIRETEC, describes this as “engineering” the behaviour of wildfires. FIRETEC is so sophisticated that it even models how the flames of a planned burn, intended to clear vegetation in a controlled way, will be fed by the wind they generate. This lets users (who include the forest services of Canada and France, as well as the United States) design precise patterns for planned burns, in order to clear surface vegetation without destroying tree canopies.新墨西哥州洛斯阿拉莫斯国家实验室(Los Alamos National Laboratory)的罗德林(Rod Linn)帮助设计了另一款模拟软件 FIRETEC。他把火灾建模描述为“设计”山火的延烧模式。FIRETEC 非常复杂，甚至可以模拟出在林业人员为减灾而开展的预防性燃烧(以可控方式清除植被)中，火焰产生的风力如何助长了火情。除了美国，加拿大和法国的林业机构也在使用这款软件，为预防性燃烧设计出精准的模式，以便在不毁坏树冠的情况下清除地表植被。All of which is well and good for the purposes of prevention. But, if prevention fails, the question remains of whether software can then be used to forecast a fires spread, assisting those fighting it, and helping those threatened get out in time.所有这些作为预防措施当然很好。但如果预防失败，接下来的问题是：软件能否用来预报火灾的蔓延情况，协助灭火人员，并帮助人们及时脱险。This is a more challenging problem, for forecasting a fires behaviour requires a staggering number of calculations. FIRETEC, for example, divides the fire-threatened space under analysis into one-metre cubes called voxels, and then crunches estimates for each voxel of fuel, moisture, temperature and airflow, taking into account drag created by foliage and other objects. As a simulation progresses, the values in each voxel affect adjacent ones, thus creating feedback which produces impressive verisimilitude. Unfortunately, it does not do so quickly. FIRETECs simulations run more slowly than real fires burn, making it useless for real-time forecasting.这就更具挑战性了，因为预测火势需要执行数量惊人的计算。以 FIRETEC为例，它将受火灾威胁的空间划分为一个个一米见方的立方体称之为“体素”，然后计算出各个体素内的易燃物、湿度、温度和气流等估计值，同时还要考虑到叶子和其他物体产生的阻力。随着模拟的推进，相邻体素中的值会相互影响，从而产生反馈，形成非常逼真的模拟。遗憾的是，模拟的速度不够快。FIRETEC 的模拟速度比真实火灾燃烧的速度要慢，也就起不到实时预报的作用。To calculate, in a useful amount of time, the spread of a fire that has already started thus requires compromise. A model called CAWFE has voxels with sides 370 metres by 370 metres by ten metres. That makes it less accurate than FIRETEC, but according to Janice Coen, of the National Centre for Atmospheric Research, in Boulder, Colorado, who is leading the development of the software, it spits out a forecast of a wildfire in just a quarter of the time that the fire takes to burn.因而，要在有效的时间范围内对业已发生的火灾做出估测需要折中方案。一个名为 CAWFE的模型采用了长宽高分别为370米、370 米和 10米的体素，所以不如 FIRETEC精确。但是，该软件的研发主管、来自科罗拉多州博尔德市(Boulder)的国家大气研究中心(National Centre for Atmospheric Research)的贾尼丝科恩(Janice Coen)表示，这款软件的预测速度是火势蔓延速度的四倍。Such forecasts are about to get better. Using infrared images captured by aircraft, Dr Coen is training CAWFE to predict when and where a wildfire is likely to produce several infrequent but terrifying types of tendrils that reach out beyond the fire line. These include “fire whirls” (see picture), which can snap and hurl trees; pairs of counter-rotating “horizontal roll” fire vortices that form in mid-air but can collapse onto the ground; and “flame fingers” that have smitten firefighters even 100 metres from a fires edge.这类预报会越来越先进。利用飞机捕捉到的红外图像，科恩正在训练 CAWFE预测山火可能会在何时何地产生几种虽不常见但非常可怕、延伸到防火带之外的火羽流。它们包括可将树木折断并抛出的“火旋风”(见图);成对的反向旋转“水平滚动”的火旋涡它们在半空中形成，但可能会突然跌至地面;以及甚至能从距火场边缘 100米开外的地方伤害消防员的“火焰手指”。The most extreme 1% or so of wildfires, however, are likely to remain unmodellable for some time. These include the “explosive” wildfires that ravaged central Portugal last year. On June 17th 2017 wildfires broke out around Pedrgo Grande, near Coimbra. Initially, meteorologists reckoned that these fires would advance at about 3kph, but the soaring flames soon changed direction and accelerated to six times that speed. Sixty-seven people died, nearly half of them trapped motorists.然而，约 1%最异乎寻常的山火可能一时还无法模拟。去年肆虐葡萄牙中部的“爆炸性”山火就属于此类。2017 年 6月17日，科英布拉市(Coimbra)附近的大佩德罗冈市(Pedrgo Grande)周围爆发山火。起初，气象学家认为火势会以大约每小时 3公里的速度蔓延，但猛烈的火焰很快改变方向，并加快到预期速度的六倍。67 人死亡，其中近一半是受困的司机。Flames that rose roughly 100 metres into the sky during these fires generated a gale and searing “pyrocumulus” clouds, a process too complex for todays best software to model, according to Marc Castellnou, a member of the technical commission that studied the disaster. Francisco Castro Rego, an expert on fire forecasting at the University of Lisbon, reckons that at least two more years of development will be needed to model such fires.在那次火灾中，约 100米高的火柱直冲天空，其间产生了狂风和灼热的“火积云”。研究这场灾难的技术委员会成员马克卡斯泰尔努(Marc Castellnou)表示，这一过程过于复杂，当今最先进的软件也无法模拟。里斯本大学的火灾预测专家弗朗西斯科卡斯特罗雷戈(Francisco Castro Rego)认为，要模拟此类火灾至少还需要两年的研发时间。Fire-modelling is, however, getting better all the time. New satellites, with shortwave-infrared sensors, can detect fires as small as a backyard barbecue. Satellites and aircraft with rangefinders that use lidar, an optical version of radar, can map the height of vegetation precisely, which helps forecasting
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