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The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) held seven Targeted Observing Periods (TOPs) during the 2022 austral winter to enhance atmospheric predictability over the Southern Ocean and Antarctica. The TOPs of 5-10 days duration each featured the release of additional radiosonde balloons, more than doubling the routine sounding program at the 24 participating stations run by 14 nations, together with process-oriented observations at selected sites. These extra sounding data are evaluated for their impact on forecast skill via data denial experiments with the goal of refining the observing system to improve numerical weather prediction for winter conditions. Extensive observations focusing on clouds and precipitation primarily during atmospheric river (AR) events are being applied to refine model microphysical parameterizations for the ubiquitous mixed phase clouds that frequently impact coastal Antarctica. Process studies are being facilitated by high time resolution series of observations and forecast model output via the YOPP Model Intercomparison and Improvement Project (YOPPsiteMIIP). Parallel investigations are broadening the scope and impact of the YOPP-SH winter TOPs. Studies of the Antarctic tourist industry’s use of weather services show the scope for much greater awareness of the availability of forecast products and the skill they exhibit. The SIPN South analysis of predictions of the sea ice growth period reveals that the forecast skill is superior to the sea ice retreat phase.

The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) had a Special Observing Period (SOP) that ran from November 16, 2018 to February 15, 2019, a period chosen to span the austral warm season months of greatest operational activity in the Antarctic. Some 2200 additional radiosondes were launched during the 3-month SOP, roughly doubling the routine program, and the network of drifting buoys in the Southern Ocean was enhanced. An evaluation of global model forecasts during the SOP and using its data has confirmed that extratropical Southern Hemisphere forecast skill lags behind that in the Northern Hemisphere with the contrast being greatest between the southern and northern polar regions. Reflecting the application of the SOP data, early results from observing system experiments show that the additional radiosondes yield the greatest forecast improvement for deep cyclones near the Antarctic coast. The SOP data have been applied to provide insights on an atmospheric river event during the YOPP-SH SOP that presented a challenging forecast and that impacted southern South America and the Antarctic Peninsula. YOPP-SH data have also been applied in that seasonal predictions by coupled atmosphere-ocean-sea ice models struggle to capture the spatial and temporal characteristics of the Antarctic sea ice minimum. Education, outreach, and communication activities have supported the YOPP-SH SOP efforts. Based on the success of this Antarctic summer YOPP-SH SOP, a winter YOPP-SH SOP is being organized to support explorations of Antarctic atmospheric predictability in the austral cold season when the southern sea-ice cover is rapidly expanding.

A unique set of 1-year precipitation and stable water isotope measurements from the Japanese Antarctic station, Dome Fuji, has been used to study the impact of the synoptic situation and the precipitation origin on the isotopic composition of precipitation on the Antarctic Plateau. The Antarctic Mesoscale Prediction System (AMPS) archive data are used to analyse the synoptic situations that cause precipitation. These situations are investigated and divided into five categories. The most common weather situation during a precipitation event is an upper-level ridge that extends onto the Antarctic Plateau and causes strong northerly advection from the ocean. Most precipitation events are associated with an increase in temperature and wind speed, and a local maximum of δ18O. During the measurement period, 21 synoptically caused precipitation events caused 60 % of the total annual precipitation, whereas the remaining 40 % were predominantly attributed to diamond dust. By combining the synoptic analyses with 5-day back-trajectories, the moisture source regions for precipitation events were estimated. An average source region around a latitude of 55◦ S was found. The atmospheric conditions in the source region were used as initial conditions for running a Rayleigh-type isotopic model in order to reproduce the measured isotopic composition of fresh snow and to investigate the influence of the precipitation source region on the isotope ratios. The model represents the measured annual cycle of δ18O and the second-order isotopic parameter deuterium excess reasonably well, but yields on average too little fractionation along the transport/cooling path. While simulations with an isotopic general circulation model (GCM) (ECHAM5-wiso) for Dome Fuji are on average closer to the observations, this model cannot reproduce the annual cycle of deuterium excess. In the event-based analysis, no evidence of a correlation of the measured deuterium excess with the latitude of the moisture so

To bridge the gaps between traditional mesoscale modelling and microscale modelling, the National Center for Atmospheric Research, in collaboration with other agencies and research groups, has developed an integrated urban modelling system coupled to the weather research and forecasting (WRF) model as a community tool to address urban environmental issues. The core of this WRF/urban modelling system consists of the following: (1) three methods with different degrees of freedom to parameterize urban surface processes, ranging from a simple bulk parameterization to a sophisticated multi-layer urban canopy model with an indoor-outdoor exchange sub-model that directly interacts with the atmospheric boundary layer, (2) coupling to fine-scale computational fluid dynamic Reynolds-averaged Navier-Stokes and Large-Eddy simulation models for transport and dispersion (T&D) applications, (3) procedures to incorporate high-resolution urban land use, building morphology, and anthropogenic heating data using the National Urban Database and Access Portal Tool (NUDAPT), and (4) an urbanized high-resolution land data assimilation system. This paper provides an overview of this modelling system; addresses the daunting challenges of initializing the coupled WRF/urban model and of specifying the potentially vast number of parameters required to execute the WRF/urban model; explores the model sensitivity to these urban parameters; and evaluates the ability of WRF/urban to capture urban heat islands, complex boundary-layer structures aloft, and urban plume T&D for several major metropolitan regions. Recent applications of this modelling system illustrate its promising utility, as a regional climate-modelling tool, to investigate impacts of future urbanization on regional meteorological conditions and on air quality under future climate change scenarios. © 2010 Royal Meteorological Society.

The coupled Weather Research and Forecasting (WRF) model with the Noah land surface model (Noah LSM) is an attempt of the modeling community to embody the complex interrelationship between land surface and atmosphere into numerical weather or climate prediction. This study describes coupled WRF/Noah model tests to evaluate the model sensitivity and improvement through vegetation fraction (Fg) parameterizations and soil moisture initialization. We utilized the 500 m 8-day Moderate Resolution Imaging Spectroradiometer reflectance data to derive the model Fg parameter using two different methods: the linear and quadric methods. In addition, combining the Fg quadric method, we initialized soil moisture simulated by High-Resolution Land Data Assimilation System, which has been developed for providing better soil moisture data in high spatial resolution by National Center for Atmospheric Research. We performed temporal comparisons of the simulated land surface variables: surface temperature (TS), sensible heat flux (SH), ground heat flux (GH), and latent heat flux (LH) to observed data during 2002 International H2O Project. Then these results were statistically validated with correlation coefficients and root mean square errors. The results indicate high sensitivity of the coupled model to vegetation fluctuations, showing overestimation of vegetation transpiration and very low variability of GH in highly vegetated area. Copyright 2009 by the American Geophysical Union.

A coupled convection-resolving mesoscale atmosphere-land surface model (LSM) is used to investigate land surface-planetary boundary layer (PBL) interactions responsible for the initiation of deep, moist convection over the southern Great Plains of the United States on 19 June 1998. A high-resolution land data assimilation system provides initial conditions to the LSM, facilitating examination of soil moisture effects on forecasts of deep convection. During the late morning and early afternoon, the southwestern portion of a simulated southwest-northeast (SW-NE)-oriented surface water vapor gradient zone evolves into an intense dryline, unlike the northeastern portion, which remains relatively weak. Despite these regional differences, mid afternoon convection initiation occurs within a ∼100-km-wide region of enhanced PBL depth along much of the SW-NE extent of the water vapor gradient zone. The afternoon PBL depth maximum results from a midmorning-to-early afternoon surface sensible heat flux maximum of similar horizontal scale, and is reinforced by an ensuing mesoscale (L ∼ 100 km) vertical circulation. Finescale (L ∼ 10 km) PBL circulations that directly trigger deep convection are confined within this mesoscale region that contains the deeper and more unstable PBL. Comparisons among different simulations reveal that thermodynamic stability and simulated convection initiation are affected by details in the initial soil moisture distribution, through differences in the partitioning of the surface heat and moisture fluxes. These differences in convection initiation among simulations occur despite only minor differences in the overall structure of the afternoon surface moisture gradient zone, which has potentially important implications for operational forecasts of deep convection. © 2004 American Meteorological Society.

A high-resolution land data assimilation system (HRLDAS) was developed and was applied to a coupled modeling system, the weather research and forecast (WRF). The aim of the system was to reduce the errors introduced by interpolating land conditions from one LDAS source to a coupled model grids because of the mismatch of terrain, landuse, and soil specifications. As an example, HRLDAS was set up to run in the continental US due to the readily available forcing data required by HRLDAS in this region. The results show that the HRLDAS compares well with Mesonet and IHOP soil moisture in terms of seasonal tendency, and the correct specification of soil texture in HRLDAS is critical for comparing HRLDAS results with observations.