PEM-Tropics-A_Merge_Data is the merge data collected during the Pacific Exploratory Mission (PEM) Tropics A suborbital campaign. Data collection for this product is complete.

From 1983-2001, NASA conducted a collection of field campaigns as part of the Global Tropospheric Experiment (GTE). Among those was PEM, which intended to improve the scientific understanding of human influence on tropospheric chemistry. Part of the PEM field campaigns were focused on the tropical Pacific region (PEM-Tropics) which was recognized as a “very large chemical vessel.” The overarching science objective was to assess the anthropogenic impact on tropospheric oxidizing power. A secondary objective was to investigate the impact of atmospheric sulfur chemistry, including oxidation of marine biogenic emission of dimethyl sulfide (DMS) on aerosol loading and radiative effect, which is of critical importance in the assessment of global climate change. The PEM-Tropics mission was conducted in two phases to contrast the influence of biomass burning in the dry season and the “relatively clean” wet season. The first, PEM-Tropics A, was carried out during the end of the dry season (August-September 1996), and the second, PEM-Topics B, was conducted during the wet season (March-April 1999).
To accomplish its objectives, PEM-Tropics enlisted the NASA DC-8 and P-3B aircrafts to carry out longitudinal and latitudinal surveys at various altitudes as well as vertical profile sampling across the Pacific basin. Both aircrafts were equipped with in-situ instruments measuring hydroperoxyl radicals (HOx), ozone (O3), photochemical precursors (including, reactive nitrogen species and non-methane hydrocarbon species), and intermediate products (e.g., hydrogen peroxide (H2O2), formaldehyde (CH2O), and acetic acid (CH3OOH). The P3-B in-situ instrument payload also included a direct measurement of hydroxyl (OH) for both missions, while the OH and hydroperoxyl radical (HO2) measurements were added to DC-8 aircraft for PEM-Tropics B. Taking advantage of its excellent low altitude capability, the P-3B was instrumented with a comprehensive sulfur measurement package and conducted pseudo-Lagragian sampling for evaluating DMS oxidation chemistry, including measurements of DMS, sulfur dioxide (SO2), sulfuric acid (H2SO4), and methylsulfonic acid (MSA) as well as the first airborne measurement of dimethyl sulfoxide (DMSO) during PEM-Tropics B. More importantly, it was the first time that DMS (the source), OH and O3 (primary oxidants), and products (DMSO, MSA, H2SO4, SO2) were measured simultaneously aboard an aircraft in the tropical pacific. These observations, specifically DMSO, presented a substantial challenge to the DMS oxidation kinetics to this day. The DC-8 aircraft was equipped with the Differential Absoprtion Lidar (DIAL) during PEM-Tropics A, and the differential absorption lidars DIAL and LASE during PEM-Tropics B. These lidars provided real-time information for fine tuning the flight tracks to capture sampling opportunities. The lidar data products themselves provide valuable information of vertical profiles of ozone as well as aerosol and water vapor in tropical Pacific Furthermore, both aircrafts were fitted with instruments for aerosol composition and microphysical property measurements. Detailed description related to the motivation, implementation, and instrument payloads are available in the PEM-Tropics A overview paper and the PEM-Tropics B overview paper. Most of the publications based on PEM-Tropics A and B observations are available in the Journal of Geophysical Research special issues: Pacific Exploratory Mission-Tropics A and NASA Global Tropospheric Experiment Pacific Exploratory Mission in the Tropics Phase B: Measurement and Analyses (PEM-Tropics B), while other publications such as Nowak et al. (2001) were published prior to the special issues.

This dataset provides dissolved carbon dioxide (CO2) and methane (CH4) concentrations alongside their stable and radiocarbon isotopic compositions within the Arctic Sagavanirktok and Kuparuk River watersheds located on the North Slope of Alaska. The data were collected during the spring, fall, and summer seasons in 2022. In field separation of the bulk gaseous components (N2, CO2, and CH4) from the liquid phase was achieved using a degassing membrane contactor. Laboratory isotopic analyses were conducted at the W. M. Keck Carbon Cycle Accelerator Mass Spectrometer facility at UC Irvine. This collection aims to provide insights into the seasonal dynamics of greenhouse gas emissions in these critical Arctic environments, thereby contributing valuable information for climate change research and monitoring programs. The data are provided in comma separated values (CSV) format.

The Space-based Imaging Spectroscopy and Thermal pathfindER (SISTER) activity originated in support of the NASA Earth System Observatory's Surface Biology and Geology (SBG) mission to develop prototype workflows with community algorithms and generate prototype data products envisioned for SBG. SISTER focused on developing a data system that is open, portable, scalable, standards-compliant, and reproducible. This collection contains EXPERIMENTAL workflows and sample data products, including (a) the Common Workflow Language (CWL) process file and a Jupyter Notebook that run the entire SISTER workflow capable of generating experimental sample data products spanning terrestrial ecosystems, inland and coastal aquatic ecosystems, and snow, (b) the archived algorithm steps (as OGC Application Packages) used to generate products at each step of the workflow, (c) a small number of experimental sample data products produced by the workflow which are based on the Airborne Visible/Infrared Imaging Spectrometer-Classic (AVIRIS or AVIRIS-CL) instrument, and (d) instructions for reproducing the sample products included in this dataset. DISCLAIMER: This collection contains experimental workflows, experimental community algorithms, and experimental sample data products to demonstrate the capabilities of an end-to-end processing system. The experimental sample data products provided have not been fully validated and are not intended for scientific use. The community algorithms provided are placeholders which can be replaced by any user's algorithms for their own science and application interests. These algorithms should not in any capacity be considered the algorithms that will be implemented in the upcoming Surface Biology and Geology mission.

This dataset provides estimates of carbon dioxide (CO2) and methane (CH4) diffusive fluxes from waterbodies, and watershed landcover data for the central-interior of the Yukon-Kuskokwim Delta (YK delta), Alaska. Dissolved concentrations of methane and carbon dioxide were predicted using an integrated terrestrial-aquatic approach to scale observations based on landscape and waterbody remote sensing drivers. The observations include ~300 samples of surface water dissolved gases collected in July 2016-2019 from the central region of the YK Delta, Alaska. A machine learning model was used to generate estimated fluxes. Model inputs include Sentinel-2 MSI with derived normalized difference vegetation index (NDVI) and normalized difference water index (NDWI), an Arctic digital elevation model (DEM) with derived slope and flow accumulation, Sentinel-1 C-band July and December VV and VH composites, and a landcover map. Waterbody size, shape, and reflectance were determined using object-based image analysis in Google Earth Engine. Landscape-level input data were averaged in non-nested sub-basins calculated using the System for Automated Geoscientific Analyses (SAGA) "channel network" algorithm at three threshold sizes. Cross validation was used to tune and select variables for gradient boosting models. The trained gradient boosting models were then used to predict dissolved methane and carbon dioxide in all waterbodies (~17,000) in the region. These aquatic concentrations were converted to fluxes using an average gas transfer velocity from observations (0.33 m/d). The data are provided in GeoTIFF and shapefile formats.

The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site.

The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site.

The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site.

The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site.

The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site.

The Inland Waters dataset (ILW) provides data for lakes and other water bodies across the contiguous United States (CONUS) and Alaska. ILW significantly reduces the processing effort required by end users and is a standardized community resource for lake and reservoir algorithm development and performance assessment. The data is provided for 15,450 CONUS waterbodies with a size of at least one 300 m pixel and over 2,300 resolvable lakes with sizes greater than three 300 m pixels. Alaska has 5,874 lakes resolvable lakes. ILW was developed in collaboration with the Cyanobacteria Assessment Network (CyAN). Additional inland water details and resources, including maps of resolvable lakes and additional inland water products, such as true color imagery, are available at the CyAN site.