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Inger-Lise Frogner, Ulf Andrae, Pirkka Ollinaho, Alan Hally, Karoliina Hämäläinen, Janne Kauhanen, Karl-Ivar Ivarsson, and Daniel Yazgi

Abstract

The Stochastically Perturbed Parameterizations scheme (SPP) is here implemented and tested in HarmonEPS - the convection-permitting limited area ensemble prediction system by the international research program High Resolution Limited Area Model (HIRLAM) group. SPP introduces stochastic perturbations to values of chosen closure parameters representing efficiencies or rates of change in parameterized atmospheric (sub)processes. The impact of SPP is compared to that of the Stochastically Perturbed Parameterization Tendencies scheme (SPPT). SPP in this first version in HarmonEPS perturbs 11 parameters, active in different atmospheric processes and under various weather conditions. The main motivation for this study is the lack of variability seen in cloud products in HarmonEPS, as reported by duty forecasters. SPP in this first version is able to increase variability in a range of weather variables, including the cloud products. However, for some weather variables the root mean squared error of the ensemble mean is increased and the mean bias is impacted, especially in winter. This indicates that (some) parameter perturbation distributions are not optimal in the current configuration, and a further sensitivity analysis is required. SPPT resulted in a smaller increase in variability in the ensemble, but the impact was almost completely masked out when combined with perturbations of the initial state, lateral boundaries and surface properties. An in-depth investigation into this lack of impact from SPPT is here presented through examining, among other things, accumulated tendencies from the model physics.

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Manuel Tanguy, Gaёlle de Coёtlogon, and Laurence Eymard

Abstract

ERA5 reanalyses and observations of convective clouds and precipitation are used over the northern Gulf of Guinea between 7W and 3E to study the influence of ocean surface temperature and land-sea temperature gradient on Guinea Coast Rainfall (GCR) in boreal spring and summer. Seasonal composites are calculated around two dates indexing the onset (Tref) and demise (Tend) of the GCR: Tref corresponds to the emergence of the equatorial upwelling in boreal spring, which “pushes” the zonal precipitation belt northward against the Guinea coast. Tend characterizes the emergence of the coastal upwelling in July, which is known to coincide with the beginning of the “little dry season” that lasts until September. Along the Guinea Coast, the diurnal cycle of the air-sea temperature gradient controls precipitation through the land-sea breeze, which explains why precipitation reaches its maximum around noon over the ocean, and in the late afternoon over the continent. The emergence of the Guinea Coast upwelling in July induces a weakening of southerlies on a seasonal scale, and a weaker land breeze on a diurnal scale: it induces a decrease in the convergence of humidity transport across the coast and in coastal oceanic precipitation. Therefore, the GCR is seasonally controlled by the latitude of the maximum tropospheric water vapor content and the annual cycle of the West African Monsoon, but the ocean surface temperature is responsible for the abruptness of its onset via the intensification of the equatorial upwelling around the end of May, and possibly of its demise as well via the emergence of the coastal upwelling by early July.

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Altug Aksoy, Joseph J. Cione, Brittany A. Dahl, and Paul D. Reasor

Abstract

A unique dataset obtained from the Coyote small uncrewed aircraft system (sUAS) in the inner-core boundary layer of Hurricane Maria (2017) is assimilated using NOAA’s Hurricane Ensemble Data Assimilation System (HEDAS) for data assimilation and Hurricane Weather Research and Forecast (HWRF) for model advances. The case of study is 1800 UTC 23 September 2017 when Maria was a Category-3 hurricane. In addition to the Coyote observations, measurements collected by the NOAA Lockheed WP-3D Orion and U.S. Air Force C-130 aircraft were also included. To support the assimilation of this unique dataset, a new online quality control (QC) technique in HEDAS scales the observation-background difference by the total uncertainty during data assimilation and uses the inter-quartile range outlier method to identify outlier observations. Experimental setup includes various very-frequent cycling scenarios for a Control that does not assimilate Coyote observations, assimilation of Coyote observations in addition to the Control observations, and the application of online QC.

Findings suggest progressively improved analyses with more-frequent cycling, Coyote assimilation, and application of online QC. This applies to verification statistics computed at the locations of both Coyote and non-Coyote observations. In terms of the storm structure, only experiments that assimilated the Coyote observations were able to reproduce the double-eyewall structure that was observed at the time of the analysis, which is more consistent with the intensity of the storm according to the observations that were collected. Limitations of the study and future plans are also discussed.

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Sue Chen, Carolyn A. Reynolds, Jerome M. Schmidt, Philippe P. Papin, Matthew A. Janiga, Richard Bankert, and Andrew Huang

Abstract

A high-impact Atmospheric River (AR) event that made landfall on the US West Coast on Valentine’s Day, 2019 and produced widespread flooding in California is examined. The US Naval Research Laboratory cloud resolving and high-resolution Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) captures the main features impacting the life cycle and structure of the Valentine’s Day AR. Analysis of the model simulated AR reveals the complex processes leading up to the initial northeastward surge of the water vapor and enhanced near-surface flow associated with this AR. These include the pre-existence of a mesoscale cold-core Kona Low, a mesoscale anticyclone, and a strong low-level convergence in the corridor between the Kona Low and mesoscale anticyclone where the environment becomes supersaturated in a region of weak vertical wind shear. Model sensitivity experiments show that the eastward progression and magnitude of the AR water vapor surge is strongly sensitive to the magnitude of Kona Low circulation. Experiments with the Kona Low circulation amplitude reduced to less than 25% showed that the AR is not able to reach the US West Coast. These results help identify key new aspects of an important player – the Kona Low— and its significant contributions to the overall AR characteristics of this particular observed event.

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Bruna Barbosa Silveira, Nadia Fourrié, Vincent Guidard, Philippe Chambon, Jean-François Mahfouf, Pierre Brousseau, Patrick Moll, Thomas August, and Tim Hultberg

Abstract

The main objective of the study is to evaluate the feasibility and benefits of assimilating satellite temperature and humidity soundings (aka Level 2 or L2 profiles), instead of radiances, from the EUMETSAT Advanced Retransmission Service (EARS) into the AROME-France data assimilation system. The satellite soundings are operational forecast-independent retrievals that used the infrared sounder IASI in synergy with its companion microwave instruments AMSU-A and MHS onboard the Metop platforms. In this assimilation study, L2 profiles are used as pseudo-radiosondes, discarding vertical error correlations and the instrument vertical sensitivity in the observation operator due to the the lack of available averaging kernels. Three assimilation experiments were performed, the baseline (including all satellite radiances except those from IASI, AMSU-A and MHS sounders), the control (with observations from the baseline plus IASI, AMSU-A and MHS radiances) and the L2 experiment (with observations from the baseline and L2 temperature and humidity profiles). The assimilation runs cover the periods of the winter 2017 and summer 2018. The forecast skills of the three experiments are gauged against independent analyses and observations. Despite that the vertical observation operator is not accounted for in this study, it is found that L2 profile assimilation does not have a negative impact on 1-hour temperature and humidity forecasts, especially in the mid-troposphere. Their impacts are comparable in magnitude to the radiance ones in the operational AROME framework, except in terms of temperature and wind fields during winter where the impact is more negative than positive. These findings encourage further investigations.

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Ning Zhao, Peiming Wu, Satoru Yokoi, and Miki Hattori

Abstract

This study investigated the diurnal cycle of convection over Sumatra Island in an active phase of the Madden-Julian Oscillation (MJO) during the Pre-Years of the Maritime Continent (YMC) observation campaign in December 2015 based on in-situ and satellite observations and a convection-permitting numerical model. Observations suggest that before the active phase of the MJO in early December, convection occurred frequently over the island during the afternoon and at midnight. By contrast, during the active phase of the MJO in mid-December, afternoon convection over the island was delayed and suppressed, and midnight convection was suppressed. Numerical experiments also successfully replicated the main features of the observed modulations. In general, during the active phase of the MJO, the troposphere became drier in the Sumatra region. While the clouds reduced the solar radiation over the land, the sea breeze was also found to be delayed and weakened. As a result, the afternoon convection initiation was delayed and weakened. Further analyses suggested that the sea breeze was weakened mainly due to the orographic stagnation effect rather than the slightly reduced land-sea temperature contrast. On the other hand, the increased stratiform-anvil clouds induced the anomalous evaporative cooling in the mid-troposphere and generated island-scale subsidence during the nighttime, which finally led to the suppression of inland convection. Overall, our study reveals the modulation of diurnal convection over Sumatra Island by an active phase of the MJO and also shows the potential role of land-sea interaction in convection initiation and maintenance.

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Jagdeep Singh Sodhi and Frédéric Fabry

Abstract

In the ensemble Kalman filter (EnKF), the covariance localization radius is usually small when assimilating radar observations because of high density of the radar observations. This makes the region away from precipitation difficult to correct if no other observations are available, as there is no reason to correct the background. To correct errors away from the innovating radar observations, a multiscale localization (MLoc) method adapted to dense observations like those from radar is proposed. In this method, different scales are corrected successively by using the same reflectivity observations, but with different degree of smoothing and localization radius at each step. In the context of observing system simulation experiments, single and multiple assimilation experiments are conducted with the MLoc method. Results show that the MLoc assimilation updates areas that are away from the innovative observations and improves on average the analysis and forecast quality in single cycle and cycling assimilation experiments. The forecast gains are maintained until the end of the forecast period, illustrating the benefits of correcting different scales.

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R. James Purser, Miodrag Rancic, and Manuel S. F. V. De Pondeca

Abstract

We describe a method for the efficient generation of the covariance operators of a variational data assimilation scheme which is suited to implementation on a massively parallel computer. The elementary components of this scheme are what we call ‘beta filters’, since they are based on the same spatial profiles possessed by the symmetric beta distributions of probability theory. These approximately Gaussian (bell-shaped) polynomials blend smoothly to zero at the ends of finite intervals, which makes them better suited to parallelization than the present quasi-Gaussian ‘recursive filters’ used in operations at NCEP. These basic elements are further combined at a hierarchy of different spatial scales into an overall multigrid structure formulated to preserve the necessary self-adjoint attribute possessed by any valid covariance operator. This paper describes the underlying idea of the beta filter and discusses how generalized Helmholtz operators can be enlisted to weight the elementary contributions additively in such a way that the covariance operators may exhibit realistic negative sidelobes, which are not easily obtained through the recursive filter paradigm. The main focus of the paper is on the basic logistics of the multigrid structure by which more general covariance forms are synthesized from the basic quasi-Gaussian elements. We describe several ideas on how best to organize computation, which led us to a generalization of this structure which made it practical so that it can efficiently perform with any rectangular arrangement of processing elements. Some simple idealized examples of the applications of these ideas are given.

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Nicholas A. Gasperoni, Xuguang Wang, and Yongming Wang

Abstract

A Valid Time Shifting (VTS) method is explored for the GSI-based ensemble variational (EnVar) system modified to directly assimilate radar reflectivity at convective scales. VTS is a cost-efficient method to increase ensemble size by including subensembles before and after the central analysis time. Additionally, VTS addresses common time and phase model error uncertainties within the ensemble. VTS is examined here for assimilating radar reflectivity in a continuous hourly analysis system for a case study of 1-2 May 2019. The VTS implementation is compared against a 36-member control experiment (ENS-36), to increase ensemble size (3×36 VTS), and as a cost-savings method (3×12 VTS), with time-shifting intervals τ between 15 and 120 min. The 3×36 VTS experiments increased the ensemble spread, with largest subjective benefits in early cycle analyses during convective development. The 3×12 VTS experiments captured analysis with similar accuracy as ENS-36 by the third hourly analysis. Control forecasts launched from hourly EnVar analyses show significant skill increases in 1-h precipitation over ENS-36 out to hour 12 for 3×36 VTS experiments, subjectively attributable to more accurate placement of the convective line. For 3×12 VTS, experiments with τ ≥ 60 min met and exceeded the skill of ENS-36 out to forecast hour 15, with VTS-3×12τ90 maximizing skill. Sensitivity results demonstrate preference to τ = 30–60 min for 3x36 VTS and 60 – 120 min for 3×12 VTS. The best 3×36 VTS experiments add a computational cost of 45-67%, compared to the near tripling of costs when directly increasing ensemble size, while best 3×12 VTS experiments save about 24-41% costs over ENS-36.

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Derek J. Posselt, Longtao Wu, Mathias Schreier, Jacola Roman, Masashi Minamide, and Bjorn Lambrigtsen

Abstract

Forecast observing system simulation experiments (OSSEs) are conducted to assess the potential impact of geostationary microwave (GeoMW) sounder observations on numerical weather prediction forecasts. A regional OSSE is conducted using a tropical cyclone (TC) case that is very similar to hurricane Harvey (2017), as hurricanes are among the most devastating of weather-related natural disasters, and hurricane intensity continues to pose a significant challenge for numerical weather prediction. A global OSSE is conducted to assess the potential impact of a single GeoMW sounder centered over the continental United States versus two sounders positioned at the current locations of the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellites (GOES) East and West. It is found that assimilation of GeoMW soundings result in better characterization of the TC environment, especially before and during intensification, which leads to significant improvements in forecasts of TC track and intensity. TC vertical structure (warm core thermal perturbation and horizontal wind distribution) is also substantially improved, as are the surface wind and precipitation extremes. In the global OSSE, assimilation of GeoMW soundings leads to slight improvement globally and significant improvement regionally, with regional impact equal to or greater than nearly all other observation types.

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