ALBERT

Beschreibung: The Orbiting Carbon Observatory-2 and Orbiting Carbon Observatory-3, launched in 2015 and 2019, respectively, are intended to collect and deliver high-resolution observations of CO2 with unprecedented space and time coverage. Observations of CO2 from these remote-sensing missions (also known as XCO2, or column-based average, dry air mole fraction of CO2) are then used by the global carbon cycle community to answer a wide range of science questions, from the distribution and quantification of global and regional CO2 source-sink patterns to quantification of anthropogenic sources at urban scales. Even though we have had the OCO-2 mission flying for a few years now, the retrieval algorithms are continuously evolving and improving to deliver XCO2 retrievals with very high precision and high accuracy (or low biases). In this presentation, we will discuss a simple yet effective quantitative framework that has been developed by the OCO-2 flux team to evaluate the information content of these XCO2 retrievals as soon as they are released, i.e., with lower latency than full-scale flux inversions. This framework serves as a precursor to advanced inverse modeling frameworks and is intended to provide an early but accurate assessment of the signal present in the satellite retrievals, the robustness of that signal, and the ability of these retrievals to resolve patterns in CO2 surface fluxes that cannot be resolved by our current network of surface sites. Specific results will tackle a tiered set of questions that are being addressed using this framework: (a) what are the distribution of retrievals in the different modes of operation and how do they vary in space and time? (b) what is the information that is being given to the inverse modeling frameworks from the space-based data, information above and beyond what is provided by the in-situ data? and (c) how do these factors influence our choices for doing flux inversions with the satellite retrievals? While the primary focus of the results will be on application of this technique to mature OCO-2 retrievals, we will show early results for a couple of months of OCO-3 retrievals. For the time-period that the retrievals from the two missions overlap, we will highlight how this framework allows us to effortlessly put the information from OCO-3 and OCO-2 on an equal footing, thus enabling easy comparison between the two pioneering missions.

Beschreibung: The Asian Tropopause Aerosol Layer-ATAL is a confined area of enhanced aerosol associated Summer Asia Monsoon spanning from the E. Med Sea to W. China. It essentially extends from top of convective outflow over much of SE Asia Existence recognize through CALIPSO observations.

Beschreibung: Forecast errors with respect to wind, temperature, moisture, clouds, and precipitation largely correspond to the limited capability of current earth system models to capture and simulate land-atmosphere feedback. To facilitate its realistic simulation in next generation models, an improved process understanding of the related complex interactions is essential. To this end, accurate 3D observations of key variables in the land-atmosphere (L-A) system with high vertical and temporal resolution from the surface to the free troposphere are indispensable. Recently, we developed a synergy of innovative ground-based, scanning active remote sensing systems for 2D to 3D measurements of wind, temperature, and water vapor from the surface to the lower troposphere that is able to provide comprehensive data sets for characterizing L-A feedback independently of any model input. Several new applications are introduced such as the mapping of surface momentum, sensible heat, and latent heat fluxes in heterogeneous terrain, the testing of Monin-Obukhov similarity theory and turbulence parameterizations, the direct measurement of entrainment fluxes, and the development of new flux-gradient relationships. An experimental design taking advantage of the sensors' synergy and advanced capabilities was realized for the first time during the Land Atmosphere Feedback Experiment (LAFE), conducted at the Atmospheric Radiation Measurement Program Southern Great Plains site in August 2017. The scientific goals and the strategy of achieving them with the LAFE data set are introduced. We envision the initiation of innovative L-A feedback studies in different climate regions to improve weather forecast, climate, and earth system models worldwide.