Wolfram 语言™

气象预测

Wolfram Knowledgebase 不仅包含了静态知识和实时数据，还可以对诸如与气候相关的未来事件进行预测. 该范例使用 WeatherForecastData 提取预测，将其与 AirTemperatureData 中已知的历史数值进行比较，并提供多个可视化结果.

用自然语言输入指定格陵兰首都，给出本周的平均温度预测.

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forecast = WeatherForecastData[\!\(\* NamespaceBox["LinguisticAssistant", DynamicModuleBox[{Typeset`query$$ = "greenland capital", Typeset`boxes$$ = RowBox[{ TemplateBox[{"\"Greenland\"", RowBox[{"Entity", "[", RowBox[{"\"Country\"", ",", "\"Greenland\""}], "]"}], "\"Entity[\\\"Country\\\", \\\"Greenland\\\"]\"", "\"country\""}, "Entity"], "[", TemplateBox[{"\"capital city\"", RowBox[{"EntityProperty", "[", RowBox[{"\"Country\"", ",", "\"CapitalCity\""}], "]"}], "\"EntityProperty[\\\"Country\\\", \\\"CapitalCity\\\"]\""}, "EntityProperty"], "]"}], Typeset`allassumptions$$ = {}, Typeset`assumptions$$ = {}, Typeset`open$$ = {1}, Typeset`querystate$$ = { "Online" -> True, "Allowed" -> True, "mparse.jsp" -> 0.449168`6.10395380181902, "Messages" -> {}}}, DynamicBox[ToBoxes[ AlphaIntegration`LinguisticAssistantBoxes["", 4, Automatic, Dynamic[Typeset`query$$], Dynamic[Typeset`boxes$$], Dynamic[Typeset`allassumptions$$], Dynamic[Typeset`assumptions$$], Dynamic[Typeset`open$$], Dynamic[Typeset`querystate$$]], StandardForm], ImageSizeCache->{121., {7., 16.}}, TrackedSymbols:>{ Typeset`query$$, Typeset`boxes$$, Typeset`allassumptions$$, Typeset`assumptions$$, Typeset`open$$, Typeset`querystate$$}], DynamicModuleValues:>{}, UndoTrackedVariables:>{Typeset`open$$}], BaseStyle->{"Deploy"}, DeleteWithContents->True, Editable->False, SelectWithContents->True]\), "Temperature"]

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提取过去 10 年的周平均温度，并与前 10 年进行比较

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history = Table[TimeSeriesShift[ AirTemperatureData[ Entity["Country", "Greenland"][ EntityProperty["Country", "CapitalCity"]], With[{past = Today - y}, {past, past + Quantity[1, "Weeks"], All}]], y], {y, Quantity[Range[10], "Years"]}]

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Show[DateListPlot[forecast /. Interval[x_] :> Mean[x], PlotStyle -> Red], DateListPlot[history, PlotStyle -> Opacity[0.5], PlotRange -> Full, PlotLegends -> {Table[ DatePlus[DateObject[Today], -Quantity[x, "Years"]]["Year"], {x, 10}]}]]

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调查并测试两个不同城市周边的地区的温度范围差别.

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Table[WeatherForecastData[ GeoDisk[city[EntityProperty["City", "Position"]], Quantity[100, "Miles"]], "Temperature", DateObject[ Tomorrow, {12}]], {city, {Entity[ "City", {"Champaign", "Illinois", "UnitedStates"}], Entity["City", {"SanFrancisco", "California", "UnitedStates"}]}}]

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列出德国最大的 6 个城市并获取今天的最高温度预测.

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cities = EntityClass[ "City", {"Country" -> "Germany", "Population" -> TakeLargest[6]}] // EntityList

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In[6]:=

data = {CityData[#, "Coordinates"], CityData[#, "Name"], WeatherForecastData[#, "MaxTemperature"]["FirstValue"]} & /@ cities;

在地图上可视化.

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GeoGraphics[{ GeoStyling["ReliefMap"], EdgeForm[Thin], Opacity[0.5], Polygon[Entity["Country", "Germany"]], PointSize[Large], Opacity[1], {Black, Text[#2, GeoPosition[#1], {-1.5, 0}], Red, Point[GeoPosition[#1]], Inset[IconData["AirTemperature", #3], GeoPosition[#1], Bottom, 1]} & @@@ data}]

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