拓冰网站定制 
ACT-America: L2 In Situ Atmospheric CO2, CO, CH4, and O3 Concentrations, Eastern USA简介该数据集提供了大气中二氧化碳 (CO2)、一氧化碳 (CO)、甲烷 (CH4)、水蒸气 (H2O) 和臭氧 (O3) 的浓度这些浓度是在大气碳和运输-美国 (ACT-America) 项目开展的空中活动期间收集的。ACT-America 的任务持续了 4 年包括五次为期 6 周的空中活动覆盖美国中部和东部的所有 4 个季节和 3 个地区。该数据集提供了所有五次活动的结果包括 2016 年夏季、2017 年冬季、2017 年秋季、2018 年春季和 2019 年夏季。两个仪器飞机平台即 NASA 兰利比奇 B200 空中国王和 NASA 戈达德太空飞行中心的 C-130H 大力神用于收集各种大陆表面和大气条件下的高质量现场测量数据。采用红外腔衰荡光谱仪系统CRDSPicarro Inc.收集二氧化碳、一氧化碳、甲烷和水。采用双光束差分紫外吸收臭氧监测仪型号 2052B Technologies收集臭氧数据。两架飞机均安装了相同的原位传感器阵列。此外还提供了完整的飞机飞行信息包括但不限于纬度、经度、海拔和气象条件。ACT-America 的整个任务持续了四年包括覆盖美国中部和东部地区所有四个季节的空中活动。ACT-America 的目标是研究大气中 CO2 和 CH4 的输送和通量。两个仪器飞机平台NASA 兰利比奇 B-200 空中国王和 NASA 瓦洛普斯飞行设施的 C-130 大力神用于收集各种大陆表面和大气条件下的高质量现场测量数据。有时它们直接飞过轨道碳观测站-2 (OCO-2) 立交桥以评估 OCO-2 观测高分辨率大气 CO2 变化的能力。C-130 飞机还配备了主动遥感仪器用于行星边界层高度探测和柱状温室气体测量。摘要Table 1.Names and descriptions for variables in respective instrument files.InstrumentVariable nameUnitsDescriptionPICARRO (Summer 2016 campaign only)CH4_PIC_ppmv, CO_PIC_ppmv, CO2_PIC_ppmvparts per million volumeMethane mixing ratio, Carbon monoxide mixing ratio, Carbon dioxide mixing ratioPICARRO-CH4CH4_PIC_ppmvparts per million volumeMethane mixing ratioPICARRO-COCO_PIC_ppmvparts per million volumeCarbon monoxide mixing ratioPICARRO-CO2CO2_PIC_ppmvparts per million volumeCarbon dioxide mixing ratioPICARRO-H2OH2O_PIC_pctpercentWater vapor volume mixing ratioPICARRO-H2OH2O_PIC_gkggrams per kilogramWater vapor mass mixing ratioPICARRO-H2OeH2O_PIC_mbarmillibarsDerived water vapor pressurePICARRO-H2ORHi_PIC_pctpercentDerived relative humidity wrt icePICARRO-H2ORHw_PIC_pctpercentDerived relative humidity wrt liquid waterPICARRO-H2ODP_PIC_degCCelsiusDerived dew pointOzoneO3_ppbvparts per billion volumeOzone mixing ratioTable 2.Names and descriptions of navigation and meteorological variables. These variables are present in the netCDF files.Variable nameUnitsDescriptiontimesecondsseconds since 2016-01-01 00:00:00.0 UTCtime_bndsboundary (start and end time) of each time stepStart_UTCsecondsstart UTC time of day for measurementStop_UTCsecondsstop UTC time of day for measurement intervalMid_UTCsecondsmean UTC time of day of measurement intervalFlight_IDFlight identification (aircraft and flight date)Aircraft_Sun_AzimuthdegreePlatform azimuth angleAircraft_Sun_ElevationdegreeSolar elevation angleCabin_PressuremillibarsAir pressure of cabinDay_of_YeardayDay of year starting Jan 1 UTCDew_PointCelsiusDew point temperatureDrift_AngledegreeDrift angleGPS_AltitudemetersGlobal Positioning System altitudeGPS_Timehours since 2016-01-01 00:00:00.0 UTCTimeGround_Speedmeters per secondPlatform speed with respect to groundIndicated_Air_SpeedknotsIndicated air speedLatitudedegree northLatitude, EPSG: 4326Longitudedegree eastLongitude, EPSG: 4326Mach_NumberMach numberMixing_Ratiograms per kilogramH2O mixing ratioPart_Press_Water_VapormillibarsWater vapor partial pressure in airPitch_AngledegreePlatform pitch anglePotential_TempCelsiusPotential temperaturePressure_AltitudefeetBarometric altitudeRelative_HumiditypercentRelative humidityRoll_AngledegreePlatform roll angleSat_Vapor_Press_H2OmillibarsH2O saturation vapor pressure of waterSat_Vapor_Press_IcemillibarsH2O saturation vapor pressure of iceSolar_Zenith_AngledegreeSolar zenith angleStatic_Air_TempCelsiusStatic air temperatureStatic_PressuremillibarsAir pressureSun_AzimuthdegreeSolar azimuth angleTotal_Air_TempCelsiusTotal air temperatureTrack_AngledegreeTrack angleTrue_Air_SpeedknotsPlatform speed with respect to airTrue_HeadingdegreePlatform yaw angleVertical_Speedfeet per minuteVertical speedWind_DirectiondegreeWind directionWind_Speedmeters per secondWind speedAltitude_AGL_mmetersAircraft altitude above ground levelGround_Elevation_mmetersGround elevation above mean sea level代码!pip install leafmap !pip install pandas !pip install folium !pip install matplotlib !pip install mapclassify import pandas as pd import leafmap url https://github.com/opengeos/NASA-Earth-Data/raw df pd.read_csv(url, sep\t) df leafmap.nasa_data_login() results, gdf leafmap.nasa_data_search( short_nameACTAMERICA_PICARRO_1556, cloud_hostedTrue, bounding_box(-110.0, 25.0, -70.0, 50.55), temporal(2016-07-11, 2019-07-27), count-1, # use -1 to return all datasets return_gdfTrue, ) gdf.explore() #leafmap.nasa_data_download(results[:5], out_dirdata) ACT-America：L2 美国东部大气 CO2、CO、CH4 和 O3 浓度现场
ACT-America: L2 In Situ Atmospheric CO2, CO, CH4, and O3 Concentrations, Eastern USA简介该数据集提供了大气中二氧化碳 (CO2)、一氧化碳 (CO)、甲烷 (CH4)、水蒸气 (H2O) 和臭氧 (O3) 的浓度这些浓度是在大气碳和运输-美国 (ACT-America) 项目开展的空中活动期间收集的。ACT-America 的任务持续了 4 年包括五次为期 6 周的空中活动覆盖美国中部和东部的所有 4 个季节和 3 个地区。该数据集提供了所有五次活动的结果包括 2016 年夏季、2017 年冬季、2017 年秋季、2018 年春季和 2019 年夏季。两个仪器飞机平台即 NASA 兰利比奇 B200 空中国王和 NASA 戈达德太空飞行中心的 C-130H 大力神用于收集各种大陆表面和大气条件下的高质量现场测量数据。采用红外腔衰荡光谱仪系统CRDSPicarro Inc.收集二氧化碳、一氧化碳、甲烷和水。采用双光束差分紫外吸收臭氧监测仪型号 2052B Technologies收集臭氧数据。两架飞机均安装了相同的原位传感器阵列。此外还提供了完整的飞机飞行信息包括但不限于纬度、经度、海拔和气象条件。ACT-America 的整个任务持续了四年包括覆盖美国中部和东部地区所有四个季节的空中活动。ACT-America 的目标是研究大气中 CO2 和 CH4 的输送和通量。两个仪器飞机平台NASA 兰利比奇 B-200 空中国王和 NASA 瓦洛普斯飞行设施的 C-130 大力神用于收集各种大陆表面和大气条件下的高质量现场测量数据。有时它们直接飞过轨道碳观测站-2 (OCO-2) 立交桥以评估 OCO-2 观测高分辨率大气 CO2 变化的能力。C-130 飞机还配备了主动遥感仪器用于行星边界层高度探测和柱状温室气体测量。摘要Table 1.Names and descriptions for variables in respective instrument files.InstrumentVariable nameUnitsDescriptionPICARRO (Summer 2016 campaign only)CH4_PIC_ppmv, CO_PIC_ppmv, CO2_PIC_ppmvparts per million volumeMethane mixing ratio, Carbon monoxide mixing ratio, Carbon dioxide mixing ratioPICARRO-CH4CH4_PIC_ppmvparts per million volumeMethane mixing ratioPICARRO-COCO_PIC_ppmvparts per million volumeCarbon monoxide mixing ratioPICARRO-CO2CO2_PIC_ppmvparts per million volumeCarbon dioxide mixing ratioPICARRO-H2OH2O_PIC_pctpercentWater vapor volume mixing ratioPICARRO-H2OH2O_PIC_gkggrams per kilogramWater vapor mass mixing ratioPICARRO-H2OeH2O_PIC_mbarmillibarsDerived water vapor pressurePICARRO-H2ORHi_PIC_pctpercentDerived relative humidity wrt icePICARRO-H2ORHw_PIC_pctpercentDerived relative humidity wrt liquid waterPICARRO-H2ODP_PIC_degCCelsiusDerived dew pointOzoneO3_ppbvparts per billion volumeOzone mixing ratioTable 2.Names and descriptions of navigation and meteorological variables. These variables are present in the netCDF files.Variable nameUnitsDescriptiontimesecondsseconds since 2016-01-01 00:00:00.0 UTCtime_bndsboundary (start and end time) of each time stepStart_UTCsecondsstart UTC time of day for measurementStop_UTCsecondsstop UTC time of day for measurement intervalMid_UTCsecondsmean UTC time of day of measurement intervalFlight_IDFlight identification (aircraft and flight date)Aircraft_Sun_AzimuthdegreePlatform azimuth angleAircraft_Sun_ElevationdegreeSolar elevation angleCabin_PressuremillibarsAir pressure of cabinDay_of_YeardayDay of year starting Jan 1 UTCDew_PointCelsiusDew point temperatureDrift_AngledegreeDrift angleGPS_AltitudemetersGlobal Positioning System altitudeGPS_Timehours since 2016-01-01 00:00:00.0 UTCTimeGround_Speedmeters per secondPlatform speed with respect to groundIndicated_Air_SpeedknotsIndicated air speedLatitudedegree northLatitude, EPSG: 4326Longitudedegree eastLongitude, EPSG: 4326Mach_NumberMach numberMixing_Ratiograms per kilogramH2O mixing ratioPart_Press_Water_VapormillibarsWater vapor partial pressure in airPitch_AngledegreePlatform pitch anglePotential_TempCelsiusPotential temperaturePressure_AltitudefeetBarometric altitudeRelative_HumiditypercentRelative humidityRoll_AngledegreePlatform roll angleSat_Vapor_Press_H2OmillibarsH2O saturation vapor pressure of waterSat_Vapor_Press_IcemillibarsH2O saturation vapor pressure of iceSolar_Zenith_AngledegreeSolar zenith angleStatic_Air_TempCelsiusStatic air temperatureStatic_PressuremillibarsAir pressureSun_AzimuthdegreeSolar azimuth angleTotal_Air_TempCelsiusTotal air temperatureTrack_AngledegreeTrack angleTrue_Air_SpeedknotsPlatform speed with respect to airTrue_HeadingdegreePlatform yaw angleVertical_Speedfeet per minuteVertical speedWind_DirectiondegreeWind directionWind_Speedmeters per secondWind speedAltitude_AGL_mmetersAircraft altitude above ground levelGround_Elevation_mmetersGround elevation above mean sea level代码!pip install leafmap !pip install pandas !pip install folium !pip install matplotlib !pip install mapclassify import pandas as pd import leafmap url https://github.com/opengeos/NASA-Earth-Data/raw df pd.read_csv(url, sep\t) df leafmap.nasa_data_login() results, gdf leafmap.nasa_data_search( short_nameACTAMERICA_PICARRO_1556, cloud_hostedTrue, bounding_box(-110.0, 25.0, -70.0, 50.55), temporal(2016-07-11, 2019-07-27), count-1, # use -1 to return all datasets return_gdfTrue, ) gdf.explore() #leafmap.nasa_data_download(results[:5], out_dirdata)