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NASA NTRS2021

Using Satellite Data to Identify the Methane Emission Controls of South Sudan's Wetlands

The TROPOspheric Monitoring Instrument (TROPOMI) provides observations of atmospheric methane (CH4) at an unprecedented combination of high spatial resolution and daily global coverage. Hu et al. (2018) reported unexpectedly large methane enhancements over South Sudan in these observations. Here we assess methane emissions from the wetlands of South Sudan using 2 years (December 2017–November 2019) of TROPOMI total column methane observations. We estimate annual wetland emissions of 7.4 ± 3.2 Tg yr−1, which agrees with the multiyear GOSAT inversions of Lunt et al. (2019) but is an order of magnitude larger than estimates from wetland process models. This disagreement may be explained by the underestimation (by up to 4 times) of inundation extent by the hydrological schemes used in those models. We investigate the seasonal cycle of the emissions and find the lowest emissions during the June–August season when the process models show the largest emissions. Using satellite-altimetry-based river water height measurements, we infer that this seasonal mismatch is likely due to a seasonal mismatch in inundation extent. In models, inundation extent is controlled by regional precipitation scaled to static wetland extent maps, whereas the actual inundation extent is driven by water inflow from rivers like the White Nile and the Sobat. We find the lowest emissions in the highest precipitation and lowest temperature season (June–August, JJA) when models estimate large emissions. In general, our emission estimates show better agreement in terms of both seasonal cycle and annual mean with model estimates that use a stronger temperature dependence. This suggests that temperature might be a stronger control for the South Sudan wetlands emissions than currently assumed by models. Our findings demonstrate the use of satellite instruments for quantifying emissions from inaccessible and uncertain tropical wetlands, providing clues for the improvement of process models and thereby improving our understanding of the currently uncertain contribution of wetlands to the global methane budget.

methane emission↗
NASA NTRS2021

Fairfax County Urban Development: Identifying Urban Heat Mitigation Strategies for Climate Adaptation Planning in Fairfax County, Virginia

Extreme high temperatures lead to increased instances of cardiovascular disease, pulmonary disease, and even death, as well as increased energy consumption and infrastructure costs. People in urbanized areas experience higher temperatures than rural areas due to diminished vegetation and increased impervious surfaces which absorb and radiate heat. Fairfax County, Virginia has embarked on Resilient Fairfax, a program aimed at addressing climate adaptation and resilience. The DEVELOP team partnered with the Fairfax County Office of Environmental and Energy Coordination (OEEC) to assess the extent of the urban heat island effect on the county and its most vulnerable populations. The team used data from Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), as well as the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) for the years 2013 to 2021 and found that the hottest spots were in densely urbanized areas, with temperatures as much as 47°F above that of undeveloped reference areas. The team used the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model and determined that areas with higher tree canopy cover had greater heat mitigation capacity. Estimates from the InVEST model showed that a 4.5% increase in canopy cover across the county could result in a temperature reduction of up to 2.4°F in some areas. The results will allow partners to assess heat distribution across Fairfax County and implement effective mitigation strategies, including locating prime locations for cooling centers and increasing canopy cover.

W. Pierce Holloway↗