The latest MODIS GPP (gross primary productivity) product, MOD17A2H, has great advantages over the previous version, MOD17A2, because the resolution increased from 1000 m to 500 m. In this study, MOD17A2H GPP was assessed using the latest eddy covariance (EC) flux data (FLUXNET2015 Dataset) at eighteen sites in six ecosystems across the globe. The sensitivity of MOD17A2H GPP to the meteorology dataset and the fractional photosynthetically- active radiation (FPAR) product was explored by introducing site meteorology observations and improved Global Land Surface Satellite (GLASS) Leaf Area Index (LAI) products. The results showed that MOD17A2H GPP underestimated flux-derived GPP at most sites. Its performance in estimating annual GPP was poor (R² = 0.62) and even worse over eight days (R² = 0.52). For the MOD17A2H algorithm, replacing the reanalysis meteorological datasets with the site meteorological measurements failed to improve the estimation accuracies. However, great improvements in estimating the site-based GPP were gained by replacing MODIS FPAR with GLASS FPAR. This indicated that in the existing MOD17A2H product, the errors were originated more from FPAR than the meteorological data. We further examined the potential error contributions from land cover classification and maximum light use efficiency (ε_max). It was found that the current land cover classification scheme exhibited frequent misclassification errors. Moreover, the ε_max value assigned in MOD17A2H was much smaller than the inferred ε_max value. Therefore, the qualities of FPAR and land cover classification datasets should be upgraded, and the ε_max value needs to be adjusted to provide more accurate GPP estimates using MOD17A2H for global ecosystems.

Lagrangian models are fundamental tools to study atmospheric transport processes and for practical applications such as dispersion modeling for anthropogenic and natural emission sources. However, conducting large-scale Lagrangian transport simulations with millions of air parcels or more can become rather numerically costly. In this study, we assessed the potential of exploiting graphics processing units (GPUs) to accelerate Lagrangian transport simulations. We ported the Massive-Parallel Trajectory Calculations (MPTRAC) model to GPUs using the open accelerator (OpenACC) programming model. The trajectory calculations conducted within the MPTRAC model were fully ported to GPUs, i.e., except for feeding in the meteorological input data and for extracting the particle output data, the code operates entirely on the GPU devices without frequent data transfers between CPU and GPU memory. Model verification, performance analyses, and scaling tests of the Message Passing Interface (MPI) – Open Multi-Processing (OpenMP) – OpenACC hybrid parallelization of MPTRAC were conducted on the Jülich Wizard for European Leadership Science (JUWELS) Booster supercomputer operated by the Jülich Supercomputing Centre, Germany. The JUWELS Booster comprises 3744 NVIDIA A100 Tensor Core GPUs, providing a peak performance of 71.0 PFlop s⁻¹. As of June 2021, it is the most powerful supercomputer in Europe and listed among the most energy-efficient systems internationally. For large-scale simulations comprising 10⁸ particles driven by the European Centre for Medium-Range Weather Forecasts' fifth-generation reanalysis (ERA5), the performance evaluation showed a maximum speed-up of a factor of 16 due to the utilization of GPUs compared to CPU-only runs on the JUWELS Booster. In the large-scale GPU run, about 67 % of the runtime is spent on the physics calculations, conducted on the GPUs. Another 15 % of the runtime is required for file I/O, mostly to read the large ERA5 data set from disk. Meteorological data preprocessing on the CPUs also requires about 15 % of the runtime. Although this study identified potential for further improvements of the GPU code, we consider the MPTRAC model ready for production runs on the JUWELS Booster in its present form. The GPU code provides a much faster time to solution than the CPU code, which is particularly relevant for near-real-time applications of a Lagrangian transport model.

As the tropopause plays a key role in regulating the entry of air from the troposphere into the stratosphere and in controlling stratosphere-troposphere exchange, variation of the tropopause impacts the atmospheric dynamics, circulation patterns, and the distribution of greenhouse gases in the upper troposphere and lower stratosphere (UTLS). Therefore, it is of particular interest to investigate the climatological characteristics and trends of the tropopause. Previous studies have investigated the tropopause characteristics using reanalyses and multi-source observations. This study extends the analysis of long-term variability and trends of tropical tropopause characteristics in earlier studies from 1980 up to 2021 using the modern ERA5 reanalysis and compares the results with those of other reanalyses, including ERA-Interim, MERRA-2, and NCEP1/2. Our analysis reveals a general rise and cooling of the tropical tropopause between 1980 and 2021. The geopotential height has increased by approximately 0.06 ± 0.01 km/decade (at a 95% confidence level), while the temperature has decreased by −0.09 ± 0.03 K/decade (at a 95% confidence level) for both the lapse rate tropopause and the cold point tropopause in ERA5. However, from 2006 to 2021, ERA5 shows a warming tropical tropopause (0.10 ± 0.11 K/decade) along with a slower rise in tropopause height (0.05 ± 0.02 km/decade) (at a 95% confidence level). Furthermore, our analysis demonstrates a decline in the rise and cooling of the tropical tropopause since the late 1990s, based on moving 20-year window trends in ERA5. Similar trends are observed in other investigated reanalyses. In addition, this study evaluated the variability of the width of the tropical belt based on tropopause height data from the reanalyses. The ERA5 data show a narrowing tropical belt (−0.16 ± 0.11°/decade) for the time period 1980–2021 according to the relative threshold method. It reveals a tropical widening (0.05 ± 0.22°/decade) for the period between 1980 and 2005, followed by a tropical narrowing (−0.17 ± 0.42°/decade) after 2006. However, the large uncertainties pose a challenge in drawing definitive conclusions on the change of tropical belt width. Despite the many challenges involved in deriving the characteristics and trends of the tropopause from reanalysis data, this study and the open reanalysistropopause data sets provided to the community will help to better inform future assessments of stratosphere-troposphere exchange and studies of chemistry and dynamics of the upper troposphere and lower stratosphere region.