The Tibetan Plateau (TP) is often referred to as the "water tower of Asia" or the "Third Pole". It remains a challenge for most global and regional models to realistically simulate precipitation, especially its diurnal cycles, over the TP. This study focuses on evaluating the summer (June-August) precipitation diurnal cycles over the TP simulated by the Weather Research and Forecasting (WRF) model. The horizontal resolution used in this study is 9 km, which is within the gray-zone grid spacing that a cumulus parameterization scheme (CU) may or may not be used. We conducted WRF simulations with different cumulus schemes (CU experiments) and a simulation without CU (No_CU experiment). The selected CUs include the Grell-3D Ensemble (Grell), New Simplified Arakawa-Schubert (NSAS), and Multiscale Kain-Fritsch (MSKF). These simulations are compared with both the in-situ observations and satellite products. Results show that the scale-aware MSKF outperforms the other CUs in simulating precipitation in terms of both the mean intensity and diurnal cycles. In addition, the peak time of precipitation intensity is better captured by all the CU experiments than by the No_CU experiment. However, all the CU experiments tend to overestimate the mean precipitation and simulate an earlier peak of precipitation frequency when compared to observations. The frequencies and initiation timings for short-duration (1-3 h) and long-duration (> 6 h) precipitation events are well captured by the No_CU experiment, while these features are poorly reproduced by the CU experiments. The results demonstrate simulation without a CU outperforms those with a CU at the gray-zone spatial resolution in regard to the precipitation diurnal cycles.

Precipitation over the Tibetan Plateau (TP) has major societal impacts in South and East Asia, but its spatiotemporal variations are not well understood mainly because of the sparsely distributed in-situ observation sites. With help of the Global Precipitation Measurement satellite product IMERG and ERA5 reanalysis, distinct precipitation seasonality features over the TP were objectively classified using a self-organizing map algorithm fed with ten-day averaged precipitation from 2000 to 2019. The classification reveals three main precipitation regimes with distinct seasonality of precipitation: winter peak, centered at the western plateau; early summer peak, found on the eastern plateau; and late summer peak, mainly located on the southwestern plateau. On a year-to-year basis, the winter peak regime is relatively robust, while the early summer and late summer peak regimes tend to shift mainly between the central and northern TP, but are robust in the eastern and southwestern TP. A composite analysis shows that the winter peak regime experiences larger amounts of precipitation in winter and early spring when the westerly jet is anomalously strong to the north of the TP. Precipitation variations in the late summer peak regime are associated with intensity changes in the South Asian High and Indian summer monsoon. The precipitation in the early summer peak regime is correlated with the Indian summer monsoon together with anticyclonic circulation over the western North Pacific. The results provide a basic understanding of precipitation seasonality variations over the TP and associated large-scale conditions.

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The Tibetan Plateau is regarded as the Earth's Third Pole, which is the source region of several major rivers that impact more 20% the world population. This high‐altitude region is reported to have been undergoing much greater rate of weather changes under global warming, but the existing reanalysis products are inadequate for depicting the state of the atmosphere, particularly with regard to the amount of precipitation and its diurnal cycle. An ensemble Kalman filter (EnKF) data assimilation system based on the limited‐area Weather Research and Forecasting (WRF) model was evaluated for use in developing a regional reanalysis over the Tibetan Plateau and the surrounding regions. A 3‐month prototype reanalysis over the summer months (June−August) of 2015 using WRF‐EnKF at a 30‐km grid spacing to assimilate nonradiance observations from the Global Telecommunications System was developed and evaluated against independent sounding and satellite observations in comparison to the ERA‐Interim and fifth European Centre for Medium‐Range Weather Forecasts Reanalysis (ERA5) global reanalysis. Results showed that both the posterior analysis and the subsequent 6‐ to 12‐hr WRF forecasts of the prototype regional reanalysis compared favorably with independent sounding observations, satellite‐based precipitation versus those from ERA‐Interim and ERA5 during the same period. In particular, the prototype regional reanalysis had clear advantages over the global reanalyses of ERA‐Interim and ERA5 in the analysis accuracy of atmospheric humidity, as well as in the subsequent downscale‐simulated precipitation intensity, spatial distribution, diurnal evolution, and extreme occurrence.

The Tibetan Plateau and its surrounding mountains have an average elevation of 4,400 m and a glaciated area of ∼100,000 km 2 giving it the name "Third Pole (TP) region". The TP is the headwater of many major rivers in Asia that provide fresh water to hundreds of millions of people. Climate change is altering the energy and water cycle of the TP at a record pace but the future of this region is highly uncertain due to major challenges in simulating weather and climate processes in this complex area. The Convection-Permitting Third Pole (CPTP) project is a Coordinated Regional Downscaling Experiment (CORDEX) Flagship Pilot Study (FPS) that aims to revolutionize our understanding of climate change impacts on the TP through ensemble-based, kilometerscale climate modeling. Here we present the experimental design and first results from multi-model, multi-physics ensemble simulations of three case studies. The five participating modeling systems show high performance across a range of meteorological situations and are close to having "observational quality" in simulating precipitation and nearsurface temperature. This is partly due to the large differences between observational datasets in this region, which are the leading source of uncertainty in model evaluations. However, a systematic cold bias above 2,000 m exists in most modeling systems. Model physics sensitivity tests performed with the Weather Research and Forecasting (WRF) model show that planetary boundary layer (PBL) physics and microphysics contribute equally to model uncertainties. Additionally, larger domains result in better model performance. We conclude by describing high-priority research needs and the next steps in the CPTP project.