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[R2] Add new MiCASA and LPJ datasets and update dataset overview pages to new format #333

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2ce4de4
test new dataset micasa,lpj
siddharth0248 Apr 1, 2024
6ac2204
api endpoint changed
siddharth0248 Apr 1, 2024
1a3a89c
micasa content added
siddharth0248 Apr 3, 2024
60785b5
LPJ-v2 content addded
siddharth0248 Apr 3, 2024
619445f
lpj content update
siddharth0248 Apr 4, 2024
d2aac13
lpj scale values
siddharth0248 Apr 5, 2024
f10b4fa
no value added
siddharth0248 Apr 5, 2024
814d803
data content for new datasets updated
siddharth0248 Apr 8, 2024
0c0f83f
filnames
siddharth0248 Apr 8, 2024
61e14e9
lpj content and unit
siddharth0248 Apr 10, 2024
ca3bb18
emit-change
siddharth0248 Apr 11, 2024
f926356
emit disclaimer addded
siddharth0248 Apr 11, 2024
02cf20e
emit disclaimer confirmed
siddharth0248 Apr 12, 2024
edc6f70
updates on data overview page and new asset for micasa
siddharth0248 Apr 15, 2024
e721036
lpj update
siddharth0248 Apr 15, 2024
cbf00cd
minor changes
siddharth0248 Apr 16, 2024
a6edd6e
contents updated for sharing
siddharth0248 Apr 16, 2024
b72603b
min max values for micasa changed
siddharth0248 Apr 17, 2024
6060a3e
restructured overview page for micasa,lpj
siddharth0248 Apr 17, 2024
852b455
transformation link removed for lp,micasa
siddharth0248 Apr 18, 2024
eb686ea
learn more section added
siddharth0248 Apr 18, 2024
02037f7
general info moved up and scientific details below disclaimer
siddharth0248 Apr 18, 2024
aac1d1d
new structure for overview page for all dataset
siddharth0248 Apr 18, 2024
f6d62bf
lpj units test
siddharth0248 Apr 18, 2024
05b7a46
lpj-links edit
siddharth0248 Apr 22, 2024
acee572
noaa updates
siddharth0248 Apr 23, 2024
629b9ec
noaa transformation notebook
siddharth0248 Apr 23, 2024
7b42cf2
data insight introduction to GHG updated
siddharth0248 Apr 23, 2024
5be215b
env -local update
siddharth0248 Apr 23, 2024
39472d7
env local revert
siddharth0248 Apr 23, 2024
7dd432e
Update .env.local-sample
siddharth0248 Apr 23, 2024
dc2cef8
resolved api issue
siddharth0248 Apr 23, 2024
fac12dc
noaa updates for demo
siddharth0248 Apr 24, 2024
49a3aad
epa content updated
siddharth0248 Apr 24, 2024
d5a2ab9
endpoint: dev changed to prod
siddharth0248 Apr 25, 2024
c188f13
api updated
siddharth0248 Apr 25, 2024
b81a7b6
Add VEDA UI to match develop
j08lue Apr 25, 2024
48fb49a
Merge develop into this branch
j08lue Apr 25, 2024
d67389a
lpj, micasa info description for card added
siddharth0248 Apr 25, 2024
68aaa86
alligned ecco darwin information
siddharth0248 Apr 25, 2024
1ca557e
lpj-eosim-monthly data added
siddharth0248 Apr 25, 2024
1cf5805
lpj-eosim-monthly
siddharth0248 Apr 25, 2024
e0ede8a
duplicate layer removed
siddharth0248 Apr 25, 2024
971a03c
LPJ-EOSIM for review
siddharth0248 Apr 25, 2024
d1181be
micasa-color ramp and content updated
siddharth0248 Apr 26, 2024
e03801a
monthly layer for MiCASA added
siddharth0248 Apr 26, 2024
d276e47
update url of image in intro to ghg data story
siddharth0248 Apr 26, 2024
b6fff80
into to ghg data story update
siddharth0248 Apr 26, 2024
4e66164
update intro data story links
siddharth0248 Apr 26, 2024
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lpj-eosim-monthly data added
siddharth0248 committed Apr 25, 2024
commit 1ca557ed963f3f7b4d676d7d33720fa3209518e2
161 changes: 149 additions & 12 deletions datasets/lpjwsl-wetlandch4-grid-v2.data.mdx
Original file line number Diff line number Diff line change
@@ -34,14 +34,60 @@ taxonomy:
infoDescription: |
::markdown
- Temporal Extent: January 1, 1990 - ongoing
- Temporal Resolution: Daily
- Temporal Resolution: Daily and Monthly
- Spatial Extent: Global
- Spatial Resolution: 0.5° x 0.5°
- Data Units: Grams of methane per meter squared per day(g CH₄/m²/day)
- Data Units: Grams of methane per meter squared per day(g CH₄/m²/day) and grams of methane per meter squared per month (g CH₄/m²/mon)
- Data Type: Research
- Data Latency: Updated monthly with a 2 month latency
- Data Latency: Updated bimonthly with a ~6 week latency
layers:
- id: ch4-wetlands-emissions-m-ens
stacCol: lpjeosim-wetlandch4-monthgrid-v2
name: (Monthly) Ensemble Mean Wetland CH₄ Emissions LPJ-EOSIM Model
type: raster
description: Monthly CH₄ emissions from wetlands constructed using an ensemble of climate forcing data sources input to the LPJ-EOSIM model (mean of ERA5 and MERRA-2 layers)
initialDatetime: newest
projection:
id: 'equirectangular'
zoomExtent:
- 0
- 20
sourceParams:
assets: ensemble-mean-ch4-wetlands-emissions
colormap_name: magma
rescale:
- 0
- 0.02
nodata: -9999
compare:
datasetId: lpjeosim-wetlandch4-grid-v2
layerId: ch4-wetlands-emissions-m-ens
mapLabel: |
::js ({ dateFns, datetime, compareDatetime }) => {
if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`;
}
legend:
unit:
label: g CH₄/m²/mon
type: gradient
min: 0
max: 0.02
stops:
- '#2c115f'
- '#721f81'
- '#b73779'
- '#f1605d'
- '#feb078'
analysis:
metrics:
- mean
info:
source: NASA
spatialExtent: Global
temporalResolution: Monthly
unit: g CH₄/m²/mon

- id: ch4-wetlands-emissions-d-ens
stacCol: lpjeosim-wetlandch4-daygrid-v2
name: Ensemble Mean Wetland CH₄ Emissions LPJ-EOSIM Model
@@ -88,6 +134,51 @@ layers:
temporalResolution: Daily
unit: g CH₄/m²/day

- id: ch4-wetlands-emissions-m-era
stacCol: lpjeosim-wetlandch4-monthgrid-v2
name: (Monthly) (ERA5) Wetland CH₄ Emissions LPJ-EOSIM Model
type: raster
description: Monthly CH₄ from wetlands constructed using ERA5 climate forcing data input to the LPJ-EOSIM model
initialDatetime: newest
projection:
id: 'equirectangular'
zoomExtent:
- 0
- 20
sourceParams:
assets: era5-ch4-wetlands-emissions
colormap_name: magma
rescale:
- 0
- 0.02
nodata: -9999
compare:
datasetId: lpjeosim-wetlandch4-grid-v2
layerId: ch4-wetlands-emissions-m-era
mapLabel: |
::js ({ dateFns, datetime, compareDatetime }) => {
if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`;
}
legend:
unit:
label: g CH₄/m²/mon
type: gradient
min: 0
max: 0.02
stops:
- '#2c115f'
- '#721f81'
- '#b73779'
- '#f1605d'
- '#feb078'
analysis:
metrics:
- mean
info:
source: NASA
spatialExtent: Global
temporalResolution: Monthly
unit: g CH₄/m²/mon
- id: ch4-wetlands-emissions-d-era
stacCol: lpjeosim-wetlandch4-daygrid-v2
name: (ERA5) Wetland CH₄ Emissions LPJ-EOSIM Model
@@ -132,12 +223,59 @@ layers:
source: NASA
spatialExtent: Global
temporalResolution: Daily
unit: g CH₄/m²/day
unit: g CH₄/m²/day

- id: ch4-wetlands-emissions-m-merra
stacCol: lpjeosim-wetlandch4-monthgrid-v2
name: (Monthly) (MERRA-2) Wetland CH₄ Emissions LPJ-EOSIM Model
type: raster
description: Monthly CH₄ emissions from wetlands constructed using MERRA-2 climate forcing data input to the LPJ-EOSIM model
initialDatetime: newest
projection:
id: 'equirectangular'
zoomExtent:
- 0
- 20
sourceParams:
assets: merra2-ch4-wetlands-emissions
colormap_name: magma
rescale:
- 0
- 0.02
nodata: -9999
compare:
datasetId: lpjeosim-wetlandch4-grid-v2
layerId: ch4-wetlands-emissions-m-merra
mapLabel: |
::js ({ dateFns, datetime, compareDatetime }) => {
if (dateFns && datetime && compareDatetime) return `${dateFns.format(datetime, 'LLL yyyy')} VS ${dateFns.format(compareDatetime, 'LLL yyyy')}`;
}
legend:
unit:
label: g CH₄/m²/mon
type: gradient
min: 0
max: 0.02
stops:
- '#2c115f'
- '#721f81'
- '#b73779'
- '#f1605d'
- '#feb078'
analysis:
metrics:
- mean
info:
source: NASA
spatialExtent: Global
temporalResolution: Monthly
unit: g CH₄/m²/mon

- id: ch4-wetlands-emissions-d-merra
stacCol: lpjeosim-wetlandch4-daygrid-v2
name: (MERRA-2) Wetland CH₄ Emissions LPJ-EOSIM Model
type: raster
description: emissions from wetlands constructed using MERRA-2 climate forcing data input to the LPJ-EOSIM model
description: Daily CH₄ emissions from wetlands constructed using MERRA-2 climate forcing data input to the LPJ-EOSIM model
initialDatetime: newest
projection:
id: 'equirectangular'
@@ -183,14 +321,14 @@ layers:
<Block>
<Prose>
**Temporal extent:** January 1, 1990 - ongoing<br />
**Temporal resolution:** Daily
**Temporal resolution:** Daily and Monthly
**Spatial extent:** Global
**Spatial resolution:** 0.5° x 0.5°<br />
**Data units:** Grams of methane per meter squared per day(g CH₄/m²/day)
**Data units:** Grams of methane per meter squared per day(g CH₄/m²/day) and grams of methane per meter squared per month (g CH₄/m²/mon)<br />
**Data type:** Research <br />
**Data Latency:** Updated monthly with a 2 month latency <br />
**Data Latency:** Updated bimonthly with a ~6 week latency <br />

Methane (CH₄) emissions from vegetated wetlands are estimated to be the largest natural source of methane in the global CH₄ budget, contributing to roughly one third of the total of natural and anthropogenic emissions. Wetland CH₄ is produced by microbes breaking down organic matter in the oxygen deprived environment of inundated soils. Due to limited data availability, the details of the role of wetland CH₄ emissions have thus far been underrepresented. Using the Earth Observation SIMulator version (LPJ-EOSIM) of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) global CH₄ emissions from wetlands are estimated at 0.5 x 0.5 degree spatial resolution. By simulating wetland extent and using characteristics of inundated areas, such as wetland soil moisture, temperature, and carbon content, the model provides estimates of CH₄ quantities emitted into the atmosphere. This dataset shows concentrated methane sources from tropical and high latitude ecosystems. The LPJ-EOSIM Wetland Methane Emissions dataset consists of global daily model estimates of terrestrial wetland methane emissions from 1990 to the present, with data added bimonthly. The estimates are regularly used in conjunction with NASA’s Goddard Earth Observing System (GEOS) model to simulate the impact of wetlands and other methane sources on atmospheric methane concentrations, to compare against satellite and airborne data, and to improve understanding and prediction of wetland emissions. This is a new version and replaces the LPJ-wsl dataset previously available in the GHG Center.
Methane (CH₄) emissions from vegetated wetlands are estimated to be the largest natural source of methane in the global CH₄ budget, contributing to roughly one third of the total of natural and anthropogenic emissions. Wetland CH₄ is produced by microbes breaking down organic matter in the oxygen deprived environment of inundated soils. Due to limited data availability, the details of the role of wetland CH₄ emissions have thus far been underrepresented. Using the Earth Observation SIMulator version (LPJ-EOSIM) of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) global CH₄ emissions from wetlands are estimated at 0.5 x 0.5 degree spatial resolution. By simulating wetland extent and using characteristics of inundated areas, such as wetland soil moisture, temperature, and carbon content, the model provides estimates of CH₄ quantities emitted into the atmosphere. This dataset shows concentrated methane sources from tropical and high latitude ecosystems. The LPJ-EOSIM Wetland Methane Emissions dataset consists of global daily and monthly model estimates of terrestrial wetland methane emissions from 1990 to the present, with data added bimonthly. The estimates are regularly used in conjunction with NASA’s Goddard Earth Observing System (GEOS) model to simulate the impact of wetlands and other methane sources on atmospheric methane concentrations, to compare against satellite and airborne data, and to improve understanding and prediction of wetland emissions. This is a new version and replaces the LPJ-wsl dataset previously available in the GHG Center.

</Prose>
</Block>
@@ -202,10 +340,9 @@ layers:
## Version History
The current dataset version is v2, which replaced v1 (named LPJ-wsl) in the US GHG Center in April 2024. Summary of version 2 update changes:
- Model updates and improvements, including improved data latency with more regular updates and driver-specific model recalibration
- Removal of monthly data layer
- Addition of two new data layers: LPJ-EOSIM model estimated wetland methane emissions using ERA5 climate input forcing data, and using the mean of both MERRA-2 and ERA5 climate input forcing data (mean ensemble). For the daily data layer, the v1 dataset only provided LPJ-EOSIM estimates using MERRA-2 climate input forcing data until the end of 2021.
- v2 data is delivered to the US GHG Center in Cloud Optimized GeoTIFF (COG) format (v1 data was in NetCDF format and transformed to COG)
- v2 data is provided in units of g CH₄/m²/day
- v2 data is provided in units of g CH₄/m²/day and g CH₄/m²/mon
- v1 data remains accessible from the [GMAO website](https://gmao.gsfc.nasa.gov/gmaoftp/lott/CH4/wetlands/)

## Dataset Accuracy
@@ -214,7 +351,7 @@ layers:
The wetland CH₄ data presented here have been subjected to rigorous quality checks, including comprehensive benchmarking against ground-truth model simulations and observations. Each file has been visually and programmatically checked for outliers or missing data, but errors can still occur. In the event of a reprocessing, a note will be posted on this website and the dataset will be updated.

## Scientific Details
For this dataset, wetlands are defined as land areas that are either permanently or seasonally saturated, excluding small ponds, lakes, and coastal wetlands. Permanent wetlands comprise three general types: mineral wetlands (swamps and marshes), peatlands (permafrost, bog, fens), and seasonally flooded shallow water (floodplains). The methane-producing area is thus linked to inundation and freeze−thaw dynamics, which change geographically and temporally in response to soil water dynamics. Wetland emissions of CH₄ are estimated as a function of substrate, soil temperature, and soil moisture. The net flux of CH₄ is defined as the heterotrophic respiration for the area of a grid cell covered by wetland, scaled by a fixed ratio of soil carbon to CH₄ emissions and by a modifier that varies the CH₄ emission intensity for different biomes. The LPJ-EOSIM land surface model uses a two-layer bucket model to simulate soil hydrology and uses a modified version of the topography-based hydrological model (TOPMODEL) to determine the likely distribution and dynamics of permafrost and inundated areas. Input climate forcing data comes from two different data products: the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) data and the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA5). This LPJ-EOSIM dataset contains 3 data layers: two wetland methane emission estimates forced by MERRA-2 and ERA5 respectively, and a mean ensemble data layer which is computed as the mean of the two wetland datasets forced by MERRA-2 and ERA5 layers. The ERA5 and MERRA-2 reanalysis datasets differ in how they represent variables such as precipitation and temperature, which affects wetland methane estimates in LPJ-EOSIM. The ensemble mean product is recommended for use as it has performed better against known data, as measured by the [ILAMB](https://www.ilamb.org/) benchmarking tool, than the two constituent MERRA-2 and ERA5 data products.
For this dataset, wetlands are defined as land areas that are either permanently or seasonally saturated, excluding small ponds, lakes, and coastal wetlands. Permanent wetlands comprise three general types: mineral wetlands (swamps and marshes), peatlands (permafrost, bog, fens), and seasonally flooded shallow water (floodplains). The methane-producing area is thus linked to inundation and freeze−thaw dynamics, which change geographically and temporally in response to soil water dynamics. Wetland emissions of CH₄ are estimated as a function of substrate, soil temperature, and soil moisture. The net flux of CH₄ is defined as the heterotrophic respiration for the area of a grid cell covered by wetland, scaled by a fixed ratio of soil carbon to CH₄ emissions and by a modifier that varies the CH₄ emission intensity for different biomes. The LPJ-EOSIM land surface model uses a two-layer bucket model to simulate soil hydrology and uses a modified version of the topography-based hydrological model (TOPMODEL) to determine the likely distribution and dynamics of permafrost and inundated areas. Input climate forcing data comes from two different data products: the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) data and the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA5). This LPJ-EOSIM dataset contains 3 data layers: two wetland methane emission estimates forced by MERRA-2 and ERA5 respectively, and a mean ensemble data layer which is computed as the mean of the two wetland datasets forced by MERRA-2 and ERA5. The ERA5 and MERRA-2 reanalysis datasets differ in how they represent variables such as precipitation and temperature, which affects wetland methane estimates in LPJ-EOSIM. The ensemble mean product is recommended for use as it has performed better against known data, as measured by the [ILAMB](https://www.ilamb.org/) benchmarking tool, than the two constituent MERRA-2 and ERA5 data products.

## Key Publications
Zhang, Z., Zimmermann, N.E., Stenke, A., Li, X., Hodson, E.L., Zhu, G., Huang, C., & Poulter, B. (2017). Emerging role of wetland methane emissions in driving 21st century climate change. *Proceedings of the National Academy of Sciences, 114(36), 9647–9652*. [https://doi.org/10.1073/pnas.1618765114](https://doi.org/10.1073/pnas.1618765114)