Improving Short-Term QPF Using Geostationary Satellite All-Sky Infrared Radiances: Real-Time Ensemble Data Assimilation and Forecast during the PRECIP 2020 and 2021 Experiments

The Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP) aims to improve our understanding of extreme rainfall processes in the East Asian summer monsoon. A convection-permitting ensemble-based data assimilation and forecast system (the PSU WRF-EnKF system) was run in real time in the summers of 2020–21 in advance of the 2022 field campaign, assimilating all-sky infrared (IR) radiances from the geostationary Himawari-8 and GOES-16 satellites, and providing 48-h ensemble forecasts every day for weather briefings and discussions. This is the first time that all-sky IR data assimilation has been performed in a real-time forecast system at a convection-permitting resolution for several seasons. Compared with retrospective forecasts that exclude all-sky IR radiances, rainfall predictions are statistically significantly improved out to at least 4–6 h for the real-time forecasts, which is comparable to the time scale of improvements gained from assimilating observations from the dense ground-based Doppler weather radars. The assimilation of all-sky IR radiances also reduced the forecast errors of large-scale environments and helped to maintain a more reasonable ensemble spread compared with the counterpart experiments that did not assimilate all-sky IR radiances. The results indicate strong potential for improving routine short-term quantitative precipitation forecasts using these high-spatiotemporal-resolution satellite observations in the future.Significance StatementDuring the summers of 2020/21, the PSU WRF-EnKF data assimilation and forecast system was run in real time in advance of the 2022 Prediction of Rainfall Extremes Campaign In the Pacific (PRECIP), assimilating all-sky (clear-sky and cloudy) infrared radiances from geostationary satellites into a numerical weather prediction model and providing ensemble forecasts. This study presents the first-of-its-kind systematic evaluation of the impacts of assimilating all-sky infrared radiances on short-term qualitative precipitation forecasts using multiyear, multiregion, real-time ensemble forecasts. Results suggest that rainfall forecasts are improved out to at least 4–6 h with the assimilation of all-sky infrared radiances, comparable to the influence of assimilating radar observations, with benefits in forecasting large-scale environments and representing atmospheric uncertainties as well.

The YOPP Final Summit: Assessing Past and Forecasting Future Polar Prediction Research

The successes of YOPP from the presentations and keynote presentations included * a better understanding of the impact of key polar measurements (radiosondes and space-based instruments such as microwave radiometers), and recent advancements in the current NWP observing system, achieved through coordinated OSEs in both polar regions (e.g., Sandu et al. 2021);* enhanced understanding of the linkages between Arctic and midlatitude weather (e.g., Day et al. 2019);* advancements in the atmosphere–ocean–sea ice and atmosphere–land–cryosphere coupling in NWP, and in assessing and recognizing the added value of coupling in Earth system models (e.g., Bauer et al. 2016);* deployment of tailored polar observation campaigns to address yet-unresolved polar processes (e.g., Renfrew et al. 2019);* progress in verification and forecasting techniques for sea ice, including a novel headline score (e.g., Goessling and Jung 2018);* advances in process understanding and process-based evaluation with the establishment of the YOPPsiteMIP framework and tools (Svensson 2020);* better understanding of emerging societal and stakeholder needs in the Arctic and Antarctic (e.g., Dawson et al. 2017);and * innovative transdisciplinary methodologies for coproducing salient information services for various user groups (Jeuring and Lamers 2021). The YOPP Final Summit identified a number of areas worthy of prioritized research in the area of environmental prediction and services for the polar regions: * coupled atmosphere, sea ice, and ocean models with an emphasis on advanced parameterizations and enhanced resolution at which critical phenomena start to be resolved (e.g., ocean eddies);* improved definition and representation of stable boundary layer processes, including mixed-phase clouds and aerosols;incorporation of wave–ice–ocean interactions;* radiance assimilation over sea ice, land ice, and ice sheets;understanding of linkages between polar regions and lower latitudes from a prediction perspective;* exploring the limits of predictability of the atmosphere–cryosphere–ocean system;* an examination of the observational representativeness over land, sea ice, and ocean;better representation of the hydrological cycle;and * transdisciplinary work with the social science community around the use of forecasting services and operational decision-making to name but a few. The presentations and discussions at the YOPP Final Summit identified the major legacy elements of YOPP: the YOPPsiteMIP approach to enable easy comparison of collocated multivariate model and observational outputs with the aim of enhancing process understanding, the development of an international and multi-institutional community across many disciplines investigating aspects of polar prediction and services, the YOPP Data Portal3 (https://yopp.met.no/), and the education and training delivered to early-career polar researchers. Next steps Logistical issues, the COVID-19 pandemic, but also new scientific questions (e.g., the value of targeted observations in the Southern Hemisphere), as well as technical issues emerging toward the end of the YOPP Consolidation Phase, resulted in the decision to continue the following three YOPP activities to the end of 2023: (i) YOPP Southern Hemisphere (YOPP-SH);(ii) Model Intercomparison and Improvement Project (MIIP);of which YOPPSiteMIP is a critical element;and (iii) the Societal, Economics and Research Applications (PPP-SERA) Task Team.

The Met Office winter testbed 2020/2021: Experimenting with an on-demand 300-m ensemble in a real-time environment

The Met Office held a testbed over winter 2020/2021 where a new numerical weather prediction (NWP) sub-km ensemble was set up on-demand in response to interesting weather phenomena in the United Kingdom. The domain for the model was chosen in real time by a community of Met Office Research Scientists and Operational Meteorologists and over a 4-month period the ensemble was triggered for nine events. The purpose of the testbed was to investigate whether a real-time weather regime-based enhancement in NWP capability was feasible, to understand what benefits a testbed environment might give, and to explore the practicalities of running such an event. Case studies from the testbed demonstrated that forecast ensembles at 2.2 km and 300 m grid spacing were able to capture observed winter weather, with greater spatial detail apparent, especially over complex orography, in the 300-m model. Ensemble spread appeared less influenced by resolution, potentially due to the size of the domains tested or the weather regimes of the case studies. The testbed also showcased underutilized observations and additional radiosonde ascents were conducted. All the testbed meetings were conducted virtually due to COVID-19 restrictions, and decisions were made about when to trigger the event using an online message board. The winter 2020/2021 testbed provides ideas for how on-demand weather-dependent testbeds might be conducted in the future. However, several recommendations are made that would enhance testbed benefits further, including more dedicated resource, stronger technology and data visualization and greater participation from both academia and weather information users.

Covid 19 and its impact on AMDAR data

The COVID-19 pandemic has caused problems in many human activities. It was a sign of a sharp reduction in air traffic, and this reduction in traffic also led to a major outage of specific data used in numerical weather forecasts (NWP). This paper seeks to provide this data to the general public, based on information from the World Meteorological Organization (WMO) and other professional sources, and to show its importance in aviation, as well as how meteorologists have coped with this unusual situation. © 2021 IEEE.

The Impact of COVID-19 on Weather Forecasts: A Balanced View.

Aircraft reports are an important source of information for numerical weather prediction (NWP). From March 2020, the COVID-19 pandemic resulted in a large loss of aircraft data but despite this it is difficult to see any evidence of significant degradation in the forecast skill of global NWP systems. This apparent discrepancy is partly because forecast skill is very variable, showing both day-to-day noise and lower frequency dependence on the mean state of the atmosphere. The definitive way to cleanly assess aircraft impact is using a data denial experiment, which shows that the largest impact is in the upper troposphere. The method used by Chen (2020, https://doi.org/10.1029/2020gl088613) to estimate the impact of COVID-19 is oversimplistic. Chen understates the huge importance of satellite data for modern weather forecasts and raises more alarm than necessary about a drop in forecast accuracy.