ALBERT

Description: At the NASA Goddard Earth Sciences (GES) Data and Information Service Center (DISC), we have archived and distributed more than 2,400 Earth science data products, from different missions or projects containing more than 100 M data files/granules with a total volume size nearly 2 PB that broadly serve user needs in science areas such as Atmospheric Composition, Water & Energy Cycles and Climate Variability. To date, GES DISC has developed many pertinent services to facilitate the usage of data products by our research communities, represented by approximately 24,000 registered users. We are facing the big data with increasingly archival volume and data types, moreover, we also encounter increasing users' demands and the demands are more diversified. It is still a challenge for us to better understand exactly what our users' needs are, even after developing more than 70 services, including well-known online tools such as Giovanni and MERRA subsetter. In this presentation, we will try to address how we can accommodate the users' needs from two applicational user communities, Air Quality and Wind Energy, from data or service discovery to guide them properly utilize the data and services to fit their needs.

Description: Global simulations of atmospheric chemistry are commonly conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it incurs errors due to temporal averaging in the meteorological archive and the inability to reproduce the GCM transport algorithms exactly. The CTM simulation is also often conducted at coarser grid resolution than the parent GCM. Here we investigate this cascade of CTM errors by using (exp 222)Rn(exp 210)Pb(exp 7)Be chemical tracer simulations off-line in the GEOS-Chem CTM at rectilinear 0.250.3125 (25km) and 22.5 (200km) resolutions and online in the parent GEOS-5 GCM at cubed-sphere c360 (25km) and c48 (200km) horizontal resolutions. The c360 GEOS-5 GCM meteorological archive, updated every 3h and remapped to 0.250.3125, is the standard operational product generated by the NASA Global Modeling and Assimilation Office (GMAO) and used as input by GEOS-Chem. We find that the GEOS-Chem (exp 222)Rn simulation at native 0.250.3125 resolution is affected by vertical transport errors of up to 20% relative to the GEOS-5 c360 online simulation, in part due to loss of transient organized vertical motions in the GCM (resolved convection) that are temporally averaged out in the 3h meteorological archive. There is also significant error caused by operational remapping of the meteorological archive from a cubed-sphere to a rectilinear grid. Decreasing the GEOS-Chem resolution from 0.250.3125 to 22.5 induces further weakening of vertical transport as transient vertical motions are averaged out spatially and temporally. The resulting (exp 222)Rn concentrations simulated by the coarse-resolution GEOS-Chem are overestimated by up to 40% in surface air relative to the online c360 simulations and underestimated by up to 40% in the upper troposphere, while the tropospheric lifetimes of (exp 210)Pb and (exp 7)Be against aerosol deposition are affected by 510%. The lost vertical transport in the coarse-resolution GEOS-Chem simulation can be partly restored by recomputing the convective mass fluxes at the appropriate resolution to replace the archived convective mass fluxes and by correcting for bias in the spatial averaging of boundary layer mixing depths.

Description: An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Nio-Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation. Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Nio-namely, eastern Pacific (EP) and central Pacific (CP) El Nio-and weaker activity during La Nia. However, none of the models capture the differences in TC activity between EP and CP El Nio as are shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Nio events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Nio.

Description: The radiative flux data and other meteorological data in the BSRN archive start from 1992, but the RadFlux data, the clearsky radiative fluxes at the BSRN sites derived through regression analyses of actually observed clearsky fluxes, did not come into existence until the early 2000s, and at first, they were limited to the 7 NOAA SURFRAD and 4 DOE ARM sites, a subset of the BSRN sites. Recently, the RadFlux algorithm was applied more extensively to the BSRN sites for the production of clearsky groundbased fluxes. At the time of this writing, there are 7119 site-months of clearsky fluxes at 42 BSRN sites spanning the time from 1992 to late 2017. These data provide an unprecedented opportunity to validate the satellite based clearsky fluxes. In this paper, the GEWEX SRB GSW(V3.0) shortwave downward fluxes spanning 24.5 years from 198307 to 200712, the CERES SYN1deg(Ed4A) and EBAF(Ed4.0) shortwave fluxes spanning 200003 to mid2017 are compared with their RadFlux counterparts on the hourly, 3hourly, daily and monthly time scales. All the three datasets show reasonable agreement with their groundbased counterparts. Comparison of the satellitebased surface shortwave clearsky radiative fluxes to the BSRN RadFlux analysis shows negative biases. Further analysis shows that the satellitebased atmosphere contains greater aerosol optical paths as well as more precipitable water than RadFlux analysis estimates.

Description: This paper presents details of the University of Colorado (CU) "Pilatus" unmanned research aircraft, assembled to provide measurements of aerosols, radiation and thermodynamics in the lower troposphere. This aircraft has a wingspan of 3.2 m and a maximum take-off weight of 25 kg, and it is powered by an electric motor to reduce engine exhaust and concerns about carburetor icing. It carries instrumentation to make measurements of broadband up- and downwelling shortwave and longwave radiation, aerosol particle size distribution, atmospheric temperature, relative humidity and pressure and to collect video of flights for subsequent analysis of atmospheric conditions during flight. In order to make the shortwave radiation measurements, care was taken to carefully position a high-quality compact inertial measurement unit (IMU) and characterize the attitude of the aircraft and its orientation to the upward-looking radiation sensor. Using measurements from both of these sensors, a correction is applied to the raw radiometer measurements to correct for aircraft attitude and sensor tilt relative to the sun. The data acquisition system was designed from scratch based on a set of key driving requirements to accommodate the variety of sensors deployed. Initial test flights completed in Colorado provide promising results with measurements from the radiation sensors agreeing with those from a nearby surface site. Additionally, estimates of surface albedo from onboard sensors were consistent with local surface conditions, including melting snow and bright runway surface. Aerosol size distributions collected are internally consistent and have previously been shown to agree well with larger, surface-based instrumentation. Finally the atmospheric state measurements evolve as expected, with the near-surface atmosphere warming over time as the day goes on, and the atmospheric relative humidity decreasing with increased temperature. No directional bias on measured temperature, as might be expected due to uneven heating of the sensor housing over the course of a racetrack pattern, was detected. The results from these flights indicate that the CU Pilatus platform is capable of performing research-grade lower tropospheric measurement missions.