LBA-ECO CD-32 LBA Model Intercomparison Project (LBA-MIP) Forcing Data
简介
该数据集填补了 1999 年至 2006 年间巴西九座通量塔的气象观测数据空白。测量数据包括：气温、比湿、风速模量、地面向下长波和短波辐射、地面气压、降水量以及二氧化碳（CO2）。这些大气数据以 1 小时为时间步长提供。这些数据被用作 LBA 模式比对项目（LBA-MIP）的标准化强迫数据输入。
摘要
Column Column Heading Units/format Description Range
1 Year YYYY Year of measurement (YYYY) 1999-2006
2 DoY DD Day of year (DD) 0-366
3 Hour HH Hour (HH) 0-23
4 Minute MM Minute (MM) 0-0
5 Tair K Near surface air temperature (degrees K)
6 GF Gap filled: 0=original, 1=filled (See NaN note)
7 Qair kg/kg Near surface specific humidity (kg/kg) 0.000-0.030
8 GF Gap filled: 0=original, 1=filled (See NaN note)
9 Wind m2/s Near surface module of the wind (m2/s) 0-9
10 GF Gap filled: 0=original, 1=filled (See NaN note)
11 Rainf kg/m2/s Rainfall rate (kg/m2/s) 0-0.02
12 GF Gap filled: 0=original, 1=filled (See NaN note)
13 PSurf Pa Surface pressure (Pa) 93000-100000
14 GF Gap filled: 0=original, 1=filled (See NaN note)
15 SWdown W/m2 Surface incident shortwave radiation (W/m2) 0-1500
16 GF Gap filled: 0=original, 1=filled (See NaN note)
17 LWdown W/m2 Surface incident longwave radiation (W/m2) 270-540
18 GF Gap filled: 0=original, 1=filled (See NaN note)
19 CO2air ppmv Near surface CO2 concentration (ppmv). CO2 set at constant 375--not measured 375-375
20 GF Gap filled: 0=original, 1=filled (See NaN note)
Missing values represented as -999.00. Years have 365 or 366 days, depending on if the year is or is not a leap year.
NaN note: In several of the data files, the flags (GF) that indicate whether a meteorolgical value is an original or a gap-filled number do not have consistent values. The majority of the GF fields have correct values, either 0 for an orginal value or 1 for a gap-filled value. A few GF fields have values of "NaN" and inspection reveals that the correct GF value could be either 0 or 1. The meterological values are unaffected by the GF flag inconsistency.
Example file: Reserva_Jaru_2000uaz.100217LWnet.leap.csv
Year,DoY,Hour,Minute,Tair,GF,Qair,GF,Wind,GF,Rainf,GF,PSurf,GF,SWdown,GF,LWdown,GF,CO2air,GF
2000,1,0,0,298.82,0,0.01596846,1,2.78049685,0,0.000150426,NaN,100538.3333,NaN,0,0,415.055,0,375,NaN
2000,1,1,0,297.8607782,0,0.016135424,1,1.994083389,0,0.000413556,NaN,100643.3333,NaN,0,0,442.59,0,375,NaN
...
2000,196,4,0,290.24,0,0.008681715,0,4.16,0,0,0,101745,0,0,0,354.735,0,375,1
2000,196,5,0,289.39,0,0.00844715,0,4.18,0,0,0,101725,0,0,0,351.17,0,375,1
...
2000,366,22,0,300.8085515,0,0.018639643,1,0.74,0,0,1,100492.4609,1,33.15678571,1,445.5732047,1,375,1
2000,366,23,0,300.1969176,0,0.018303222,1,0.28,0,0,1,100577.4609,1,0.010535714,1,428.7657042,1,375,1
Site boundaries:(All latitude and longitude given in decimal degrees)
Site (Region) Westernmost Longitude Easternmost Longitude Northernmost Latitude Southernmost Latitude Geodetic Datum
Para Western (Santarem) - km 67 Primary Forest Tower Site (Para Western (Santarem)) -54.95900 -54.95900 -2.85700 -2.85700 World Geodetic System, 1984 (WGS-84)
Para Western (Santarem) - km 77 Pasture Tower Site (Para Western (Santarem)) -54.88850 -54.88850 -3.02020 -3.02020 World Geodetic System, 1984 (WGS-84)
Para Western (Santarem) - km 83 Logged Forest Tower Site (Para Western (Santarem)) -54.97070 -54.97070 -3.01700 -3.01700 World Geodetic System, 1984 (WGS-84)
Amazonas (Manaus) - ZF2 km 34 (Amazonas (Manaus)) -60.20910 -60.00000 -2.50000 -2.60900 World Geodetic System, 1984 (WGS-84)
Para Eastern (Belem) - FLONA Caxiuana (Para Eastern (Belem)) -51.45360 -51.45360 -1.74830 -1.74830 World Geodetic System, 1984 (WGS-84)
Rondonia - Fazenda Nossa Senhora (Rondonia) -62.35720 -62.35720 -10.76180 -10.76180 World Geodetic System, 1984 (WGS-84)
Rondonia - Jaru Biological Reserve Tower B (Rondonia) -61.93310 -61.93310 -10.07800 -10.07800 World Geodetic System, 1984 (WGS-84)
Tocantins - Ilha do Bananal (Tocantins) -50.1591111 -50.1591111 -9.824416667 -9.824416667 World Geodetic System, 1984 (WGS-84)
Sao Pablo - Reserva Pe-de-Gigante (Sao Pablo) -47.6498889 -47.6498889 -21.61947222 -21.61947222 World Geodetic System, 1984 (WGS-84)
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"
df = pd.read_csv(url, sep="\t")
df
leafmap.nasa_data_login()
results, gdf = leafmap.nasa_data_search(
short_name="CD32_LBA_MIP_Drivers_1177",
cloud_hosted=True,
bounding_box=(-62.36, -21.62, -47.65, -1.75),
temporal=("1999-01-01", "2006-12-31"),
count=-1, # use -1 to return all datasets
return_gdf=True,
)
gdf.explore()
leafmap.nasa_data_download(results[:5], out_dir="data")
引用
de Goncalves, L.G.G., N. Restrepo-Coupe, H.R. da Rocha, S.R. Saleska, and R. Stockli. 2013. LBA-ECO CD-32 LBA Model Intercomparison Project (LBA-MIP) Meteorological Forcing Data. Data set. Available on-line [http://daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA
