CARVE是一个由美国国家航空航天局（NASA）资助的项目，旨在研究北极地区的碳储量及其对气候变化的脆弱性
【摘要】 CARVE: Fire-Related Aerosol and Soil Elemental and Isotopic Composition, Alaska, 2013简介CARVE（Carbon in Arctic Reservoirs Vulnerability Experiment）是一个由美国国家航空航天局（NASA）资助的项目，旨在研究北极地区的碳储量及其对气候变化的脆弱性。...
CARVE: Fire-Related Aerosol and Soil Elemental and Isotopic Composition, Alaska, 2013
简介
CARVE（Carbon in Arctic Reservoirs Vulnerability Experiment）是一个由美国国家航空航天局（NASA）资助的项目，旨在研究北极地区的碳储量及其对气候变化的脆弱性。其中，CARVE项目围绕着火灾相关的气溶胶和土壤元素以及同位素组成展开研究。这些数据主要针对阿拉斯加地区的火灾相关气溶胶和土壤元素进行了采样和分析，时间跨度为2013年。
摘要
Spatial Coverage: Interior Alaska, USA
Spatial Resolution: Point locations
Temporal Coverage: 20130627 to 20130810
Temporal Resolution: Variable
Study Area: (Latitude and longitude given in decimal degrees)
|
Site (Region) |
Westernmost Longitude |
Easternmost Longitude |
Northernmost Latitude |
Southernmost Latitude |
|
Interior Alaska, US |
-168 |
-140 |
70.5 |
61.5 |
Table 1. Data files
|
File Name |
Description |
|
aerosol_C_N_composition.csv |
Carbon and nitrogen composition and isotopic data from summer 2013 aerosol sampling |
|
fire_derived_14C_endmember.csv |
Isotopic analysis of total carbon in aerosols |
|
BC_modeled_emissions.csv |
Black carbon emissions modeled by combining the Alaska Fire Emissions Database with the coupled WRF-STILT model of Henderson et al (2015) |
|
soil_core_C_N_composition.csv |
Carbon and nitrogen composition and isotopic data from soil cores taken by Rogers et al. (2014) |
|
soil_depth_integrated_C_N_composition.csv |
Depth-integrated soil core composition and carbon loss due to fires |
Table 2. Data fields in aerosol_C_N_composition.csv. Missing data are coded as -999.
|
Field name |
Units |
Description |
|
Sampling begin date |
yyyymmdd |
Date aerosol sampling began |
|
Sampling end date |
yyyymmdd |
Date aerosol sampling ended |
|
Station |
Aerosol sampling location |
|
|
Sample description |
Description of fire conditions during sample collection |
|
|
Day of year |
Day |
Sampling period in day of year 2013 |
|
BC |
Micrograms per cubic meter of air |
Black carbon aerosols |
|
BC_14C |
Per mil |
BC radiocarbon measurement raw data |
|
BC_14C_fire |
Per mil |
BC radiocarbon measurement after background subtraction via isotope mass balance |
|
TC |
Micrograms per cubic meter of air |
Total carbon aerosol |
|
TC_14C |
Per mil |
TC radiocarbon measurement raw data |
|
TC_14C_fire |
Per mil |
TC radiocarbon measurement after background subtraction via isotope mass balance |
|
OC |
Micrograms per cubic meter of air |
Organic carbon aerosol |
|
OC_14C |
Per mil |
OC radiocarbon measurement raw data |
|
OC_14C_fire |
Per mil |
OC radiocarbon measurement after background subtraction via isotope mass balance |
|
delta13C |
Per mil |
Stable carbon isotope |
|
Nitrogen |
Micrograms per cubic meter of air |
Nitrogen content |
|
delta15N |
Per mil |
Nitrogen stable isotope raw data |
|
delta15N_fire |
Per mil |
Nitrogen stable isotope measurement after background subtraction via isotope mass balance. Background measurements are listed as ‘bkg’. |
|
Carbon:Nitrogen |
n/a |
Total carbon to nitrogen ratio raw data |
|
C:N_fire |
n/a |
Total carbon to nitrogen ratio after separately subtracting carbon background and nitrogen background and calculating new background corrected ratio. Background measurements are listed as ‘bkg’. |
Table 3. Data fields in fire_derived_14C_endmember.csv. Missing data are coded to -999.
|
Field name |
Units |
Description |
|
Method and Station |
n/a |
Method of background subtraction and sampling station. |
|
BC_14C_fire |
Per mil |
Fire-derived 14C of BC. Average of all fire samples at corresponding station and for applied method |
|
BC_fire_Stdev |
Per mil |
Standard deviation of all fire 14C BC samples at corresponding station and for applied method |
|
TC_14C_fire |
Per mil |
Fire-derived 14C of TC. Average of all fire samples at corresponding station and for applied method |
|
TC_fire_Stdev |
Per mil |
Standard deviation of all fire 14C TC samples at corresponding station and for applied method |
|
OC_14C_fire |
Per mil |
Fire-derived 14C of OC. Average of all fire samples at corresponding station and for applied method |
|
OC_fire_Stdev |
Per mil |
Standard deviation of all fire 14C OC samples at corresponding station and for applied method |
*Note: The last row in fire_derived_14C_endmember.csv contains values averaged over both stations and both methods.
Table 4. Data fields in BC_modeled_emissions.csv. Missing data are coded to -999.
|
Field name |
Units |
Description |
|
Day of Year |
Fractional day |
Fractional Julian day of 2013 at a 6-h time step |
|
BC Caribou |
Micrograms per cubic meter of air |
Modeled BC concentrations at Caribou sampling station |
|
BC Delta |
Micrograms per cubic meter of air |
Modeled BC concentrations at Delta sampling station |
Table 5. Data fields in soil_core_C_N_composition.csv. Missing data are coded to -999.
|
Field name |
Units |
Description |
|
Identifier |
n/a |
Soil core collection location identifier from Rogers et al., 2014 |
|
Core |
n/a |
Soil core description. A-F denotes different cores within each collection area from Rogers et al., 2014. |
|
Soil_Horizon |
n/a |
Soil horizon description: LD - top live layer; F - fibric; M - mesic & humic; H - mineral soil with possibly some humic |
|
Upper_depth |
cm below surface |
Upper depth of soil layer |
|
Lower_depth |
cm below surface |
Lower depth of soil layer |
|
Weight |
g |
Weight of soil horizon samples |
|
Volume |
cm3 |
Volume of soil horizon sample |
|
Bulk_Density |
g/cm3 |
Bulk density of soil horizon sample |
|
pct_C |
% |
Percent carbon content of soil horizon sample |
|
pct_N |
% |
Percent nitrogen content of soil horizon sample |
|
C/N |
n/a |
Carbon to nitrogen ratio of soil horizon sample |
|
mgC/g soil |
mg/g |
Calculated soil horizon carbon content per soil mass |
|
mgN/g soil |
mg/g |
Calculated soil horizon nitrogen content per soil mass |
|
mgC/cm3 soil |
mg/cm3 |
Calculated soil horizon carbon content per soil volume |
|
mgN/cm3 soil |
mg/cm3 |
Calculated soil horizon nitrogen content per soil volume |
|
d15N |
Per mil |
Nitrogen stable isotope content of soil horizon |
|
13C |
Per mil |
Carbon stable isotope content of soil horizon, measured via gas bench |
|
14C |
Per mil |
Radiocarbon content of soil horizon, measured by AMS |
|
14C_err |
Per mil |
Radiocarbon measurement uncertainty, measured by AMS |
Table 6. Data fields in soil_depth_integrated_C_N_composition.csv. Missing data are coded to -999.
|
Field name |
Units |
Description |
|
Depth |
cm |
Soil depth, measured from top of soil. We used 0.5 cm intervals to integrate cumulative elemental and isotopic composition at depth. For depths >29 cm, values were calculated by assuming a linear relationship within the last few layers and propagating it to depth. |
|
14C |
Per mil |
Cumulative radiocarbon content of soil integrated with depth |
|
13C |
Per mil |
Cumulative stable carbon isotopic content of soil integrated with depth |
|
15N |
Per mil |
Cumulative stable nitrogen isotopic content of soil integrated with depth |
|
C_loss |
Kg C/ m2 |
Carbon loss per m2 integrated with depth |
*Note: At the bottom of the table, average values are provided for all black spruce land cover types (average of data from cores COO2, COO5, and COO6). A weighted average contribution from black spruce and white spruce/mixed aspen land cover types is also provided for each soil horizon. The weighting was 0.7 black spruce + 0.3 white spruce.
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/main/nasa_earth_data.tsv"
df = pd.read_csv(url, sep="\t")
df
leafmap.nasa_data_login()
results, gdf = leafmap.nasa_data_search(
short_name="BC_Aerosol_Dynamics_Alaska_1340",
cloud_hosted=True,
bounding_box=([-168.0, 61.5, -140.0, 70.5]),
temporal=("2013-06-27", "2013-08-10"),
count=-1, # use -1 to return all datasets
return_gdf=True,
)
gdf.explore()
#leafmap.nasa_data_download(results[:5], out_dir="data")
引用
Mouteva, G.O., C.I. Czimczik, S.M. Fahrni, E.B. Wiggins, B.M. Rogers, S. Veraverbeke, X. Xu, G.M. Santos, J. Henderson, C.E. Miller, and J.T. Randerson. 2016. CARVE: Fire-Related Aerosol and Soil Elemental and Isotopic Composition, Alaska, 2013. ORNL DAAC, Oak Ridge, Tennessee, USA.
网址推荐
知识星球
机器学习
干旱监测平台
【声明】本内容来自华为云开发者社区博主，不代表华为云及华为云开发者社区的观点和立场。转载时必须标注文章的来源（华为云社区）、文章链接、文章作者等基本信息，否则作者和本社区有权追究责任。如果您发现本社区中有涉嫌抄袭的内容，欢迎发送邮件进行举报，并提供相关证据，一经查实，本社区将立刻删除涉嫌侵权内容，举报邮箱：
cloudbbs@huaweicloud.com
- 点赞
- 收藏
- 关注作者
作者其他文章
评论（0）