Improved nowcasting of precipitation based on convective analysis fields

Abstract. The high-resolution analysis and nowcasting system INCA (Integrated Nowcasting through Comprehensive Analysis) developed at the Austrian national weather service provides three-dimensional fields of temperature, humidity, and wind on an hourly basis, and two-dimensional fields of precipitation rate in 15 min intervals. The system operates on a horizontal resolution of 1 km and a vertical resolution of 100–200 m. It combines surface station data, remote sensing data (radar, satellite), forecast fields of the numerical weather prediction model ALADIN, and high-resolution topographic data. An important application of the INCA system is nowcasting of convective precipitation. Based on fine-scale temperature, humidity, and wind analyses a number of convective analysis fields are routinely generated. These fields include convective boundary layer (CBL) flow convergence and specific humidity, lifted condensation level (LCL), convective available potential energy (CAPE), convective inhibition (CIN), and various convective stability indices. Based on the verification of areal precipitation nowcasts it is shown that the pure translational forecast of convective cells can be improved by using a decision algorithm which is based on a subset of the above fields, combined with satellite products.

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Intense sea-effect snowfall case on the western coast of Finland

Advances in Science and Research ◽

10.5194/asr-14-231-2017 ◽

2017 ◽

Vol 14 ◽

pp. 231-239 ◽

Cited By ~ 3

Author(s):

Taru Olsson ◽

Tuuli Perttula ◽

Kirsti Jylhä ◽

Anna Luomaranta

Keyword(s):

Preliminary Analysis ◽

Temporal Evolution ◽

Model Simulation ◽

Weather Prediction ◽

Convective Available Potential Energy ◽

Horizontal Resolution ◽

Convective Precipitation ◽

Western Coast ◽

Radar Images ◽

A Value

Abstract. A new national daily snowfall record was measured in Finland on 8 January 2016 when it snowed 73 cm (31 mm as liquid water) in less than a day in Merikarvia on the western coast of Finland. The area of the most intense snowfall was very small, which is common in convective precipitation. In this work we used hourly weather radar images to identify the sea-effect snowfall case and to qualitatively estimate the performance of HARMONIE, a non-hydrostatic convection-permitting weather prediction model, in simulating the spatial and temporal evolution of the snowbands. The model simulation, including data assimilation, was run at 2.5 km horizontal resolution and 65 levels in vertical. HARMONIE was found to capture the overall sea-effect snowfall situation quite well, as both the timing and the location of the most intense snowstorm were properly simulated. Based on our preliminary analysis, the snowband case was triggered by atmospheric instability above the mostly ice-free sea and a low-level convergence zone almost perpendicular to the coastline. The simulated convective available potential energy (CAPE) reached a value of 87 J kg−1 near the site of the observed snowfall record.

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A Unified Convection Scheme (UNICON). Part I: Formulation

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-13-0233.1 ◽

2014 ◽

Vol 71 (11) ◽

pp. 3902-3930 ◽

Cited By ~ 77

Author(s):

Sungsu Park

Keyword(s):

Deep Convection ◽

Convective Available Potential Energy ◽

Horizontal Resolution ◽

Vertical Transport ◽

Convective Precipitation ◽

Cold Pool ◽

Quasi Equilibrium ◽

Convection Scheme ◽

Time Step ◽

Turbulent Eddies

Abstract The author develops a unified convection scheme (UNICON) that parameterizes relative (i.e., with respect to the grid-mean vertical flow) subgrid vertical transport by nonlocal asymmetric turbulent eddies. UNICON is a process-based model of subgrid convective plumes and mesoscale organized flow without relying on any quasi-equilibrium assumptions such as convective available potential energy (CAPE) or convective inhibition (CIN) closures. In combination with a relative subgrid vertical transport scheme by local symmetric turbulent eddies and a grid-scale advection scheme, UNICON simulates vertical transport of water species and conservative scalars without double counting at any horizontal resolution. UNICON simulates all dry–moist, forced–free, and shallow–deep convection within a single framework in a seamless, consistent, and unified way. It diagnoses the vertical profiles of the macrophysics (fractional area, plume radius, and number density) as well as the microphysics (production and evaporation rates of convective precipitation) and the dynamics (mass flux and vertical velocity) of multiple convective updraft and downdraft plumes. UNICON also prognoses subgrid cold pool and mesoscale organized flow within the planetary boundary layer (PBL) that is forced by evaporation of convective precipitation and accompanying convective downdrafts but damped by surface flux and entrainment at the PBL top. The combined subgrid parameterization of diagnostic convective updraft and downdraft plumes, prognostic subgrid mesoscale organized flow, and the feedback among them remedies the weakness of conventional quasi-steady diagnostic plume models—the lack of plume memory across the time step—allowing UNICON to successfully simulate various transitional phenomena associated with convection (e.g., the diurnal cycle of precipitation and the Madden–Julian oscillation).

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Improving Numerical Weather Predictions of Summertime Precipitation over the Southeastern United States through a High-Resolution Initialization of the Surface State

Weather and Forecasting ◽

10.1175/2011waf2222455.1 ◽

2011 ◽

Vol 26 (6) ◽

pp. 785-807 ◽

Cited By ~ 35

Author(s):

Jonathan L. Case ◽

Sujay V. Kumar ◽

Jayanthi Srikishen ◽

Gary J. Jedlovec

Keyword(s):

United States ◽

Soil Moisture ◽

High Resolution ◽

Land Surface ◽

Weather Prediction ◽

Southeastern United States ◽

Model Verification ◽

Sea Surface ◽

Convective Precipitation ◽

Numerical Weather

Abstract It is hypothesized that high-resolution, accurate representations of surface properties such as soil moisture and sea surface temperature are necessary to improve simulations of summertime pulse-type convective precipitation in high-resolution models. This paper presents model verification results of a case study period from June to August 2008 over the southeastern United States using the Weather Research and Forecasting numerical weather prediction model. Experimental simulations initialized with high-resolution land surface fields from the National Aeronautics and Space Administration’s (NASA) Land Information System (LIS) and sea surface temperatures (SSTs) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) are compared to a set of control simulations initialized with interpolated fields from the National Centers for Environmental Prediction’s (NCEP) 12-km North American Mesoscale model. The LIS land surface and MODIS SSTs provide a more detailed surface initialization at a resolution comparable to the 4-km model grid spacing. Soil moisture from the LIS spinup run is shown to respond better to the extreme rainfall of Tropical Storm Fay in August 2008 over the Florida peninsula. The LIS has slightly lower errors and higher anomaly correlations in the top soil layer but exhibits a stronger dry bias in the root zone. The model sensitivity to the alternative surface initial conditions is examined for a sample case, showing that the LIS–MODIS data substantially impact surface and boundary layer properties. The Developmental Testbed Center’s Meteorological Evaluation Tools package is employed to produce verification statistics, including traditional gridded precipitation verification and output statistics from the Method for Object-Based Diagnostic Evaluation (MODE) tool. The LIS–MODIS initialization is found to produce small improvements in the skill scores of 1-h accumulated precipitation during the forecast hours of the peak diurnal convective cycle. Because there is very little union in time and space between the forecast and observed precipitation systems, results from the MODE object verification are examined to relax the stringency of traditional gridpoint precipitation verification. The MODE results indicate that the LIS–MODIS-initialized model runs increase the 10 mm h−1 matched object areas (“hits”) while simultaneously decreasing the unmatched object areas (“misses” plus “false alarms”) during most of the peak convective forecast hours, with statistically significant improvements of up to 5%. Simulated 1-h precipitation objects in the LIS–MODIS runs more closely resemble the observed objects, particularly at higher accumulation thresholds. Despite the small improvements, however, the overall low verification scores indicate that much uncertainty still exists in simulating the processes responsible for airmass-type convective precipitation systems in convection-allowing models.

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Objective 3D atmospheric front detection in high-resolution numerical weather prediction data

10.5194/egusphere-egu21-10055 ◽

2021 ◽

Author(s):

Andreas Beckert ◽

Lea Eisenstein ◽

Tim Hewson ◽

George C. Craig ◽

Marc Rautenhaus

Keyword(s):

High Resolution ◽

Numerical Weather Prediction ◽

Feature Detection ◽

3D Visualization ◽

Weather Prediction ◽

Three Dimensional ◽

Detection Methods ◽

Numerical Weather ◽

Atmospheric Fronts ◽

Front Detection

Atmospheric fronts, a widely used conceptual model in meteorology, describe sharp boundaries between two air masses of different thermal properties. In the mid-latitudes, these sharp boundaries are commonly associated with extratropical cyclones. The passage of a frontal system is accompanied by significant weather changes, and therefore fronts are of particular interest in weather forecasting. Over the past decades, several two-dimensional, horizontal feature detection methods to objectively identify atmospheric fronts in numerical weather prediction (NWP) data were proposed in the literature (e.g. Hewson, Met.Apps. 1998). In addition, recent research (Kern et al., IEEE Trans. Visual. Comput. Graphics, 2019) has shown the feasibility of detecting atmospheric fronts as three-dimensional surfaces representing the full 3D frontal structure. In our work, we build on the studies by Hewson (1998) and Kern et al. (2019) to make front detection usable for forecasting purposes in an interactive 3D visualization environment. We consider the following aspects: (a) As NWP models evolved in recent years to resolve atmospheric processes on scales far smaller than the scale of midlatitude-cyclone- fronts, we evaluate whether previously developed detection methods are still capable to detect fronts in current high-resolution NWP data. (b) We present integration of our implementation into the open-source &#8220;Met.3D&#8221; software (http://met3d.wavestoweather.de) and analyze two- and three-dimensional frontal structures in selected cases of European winter storms, comparing different models and model resolution. (c) The considered front detection methods rely on threshold parameters, which mostly refer to the magnitude of the thermal gradient within the adjacent frontal zone - the frontal strength. If the frontal strength exceeds the threshold, a so-called feature candidate is classified as a front, while others are discarded. If a single, fixed, threshold is used, unwanted &#8220;holes&#8221; can be observed in the detected fronts. Hence, we use transparency mapping with fuzzy thresholds to generate continuous frontal features. We pay particular attention to the adjustment of filter thresholds and evaluate the dependence of thresholds and resolution of the underlying data.

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Effects of Increasing Horizontal Resolution in a Convection-Permitting Model on Flood Forecasting: The 2011 Dramatic Events in Liguria, Italy

Journal of Hydrometeorology ◽

10.1175/jhm-d-14-0094.1 ◽

2015 ◽

Vol 16 (4) ◽

pp. 1843-1856 ◽

Cited By ~ 26

Author(s):

Silvio Davolio ◽

Francesco Silvestro ◽

Piero Malguzzi

Keyword(s):

High Resolution ◽

Weather Prediction ◽

Flood Forecasting ◽

Horizontal Resolution ◽

Precipitation Forecast ◽

Limited Area ◽

Flood Prediction ◽

Meteorological Model ◽

The Impact ◽

Atmospheric Simulations

Abstract Coupling meteorological and hydrological models is a common and standard practice in the field of flood forecasting. In this study, a numerical weather prediction (NWP) chain based on the BOLogna Limited Area Model (BOLAM) and the MOdello LOCale in Hybrid coordinates (MOLOCH) was coupled with the operational hydrological forecasting chain of the Ligurian Hydro-Meteorological Functional Centre to simulate two major floods that occurred during autumn 2011 in northern Italy. Different atmospheric simulations were performed by varying the grid spacing (between 1.0 and 3.0 km) of the high-resolution meteorological model and the set of initial/boundary conditions driving the NWP chain. The aim was to investigate the impact of these parameters not only from a meteorological perspective, but also in terms of discharge predictions for the two flood events. The operational flood forecasting system was thus used as a tool to validate in a more pragmatic sense the quantitative precipitation forecast obtained from different configurations of the NWP system. The results showed an improvement in flood prediction when a high-resolution grid was employed for atmospheric simulations. In turn, a better description of the evolution of the precipitating convective systems was beneficial for the hydrological prediction. Although the simulations underestimated the severity of both floods, the higher-resolution model chain would have provided useful information to the decision-makers in charge of protecting citizens.

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Global climate simulations at 2.8 km on GPU with the ICON model

10.5194/egusphere-egu2020-10306 ◽

2020 ◽

Author(s):

Xavier Lapillonne ◽

William Sawyer ◽

Philippe Marti ◽

Valentin Clement ◽

Remo Dietlicher ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

Climate Model ◽

Global Climate ◽

Weather Prediction ◽

Time Integration ◽

Horizontal Resolution ◽

Performance Comparison ◽

Quasi Biennial Oscillation ◽

Numerical Weather

The ICON modelling framework is a unified numerical weather and climate model used for applications ranging from operational numerical weather prediction to low and high resolution climate projection. In view of further pushing the frontier of possible applications and to make use of the latest evolution in hardware technologies, parts of the model were recently adapted to run on heterogeneous GPU system. This initial GPU port focus on components required for high-resolution climate application, and allow considering multi-years simulations at 2.8 km on the Piz Daint heterogeneous supercomputer. These simulations are planned as part of the QUIBICC project &#8220;The Quasi-Biennial Oscillation (QBO) in a changing climate&#8221;, which propose to investigate effects of climate change on the dynamics of the QBO.Because of the low compute intensity of atmospheric model the cost of data transfer between CPU and GPU at every step of the time integration would be prohibitive if only some components would be ported to the accelerator. We therefore present a full port strategy where all components required for the simulations are running on the GPU. For the dynamics, most of the physical parameterizations and infrastructure code the OpenACC compiler directives are used. For the soil parameterization, a Fortran based domain specific language (DSL) the CLAW-DSL has been considered. We discuss the challenges associated to port a large community code, about 1 million lines of code, as well as to run simulations on large-scale system at 2.8 km horizontal resolution in terms of run time and I/O constraints. We show performance comparison of the full model on CPU and GPU, achieving a speed up factor of approximately 5x, as well as scaling results on up to 2000 GPU nodes. Finally we discuss challenges and planned development regarding performance portability and high level DSL which will be used with the ICON model in the near future.

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Experimental Tropical Cyclone Forecasts Using a Variable-Resolution Global Model

Monthly Weather Review ◽

10.1175/mwr-d-15-0159.1 ◽

2015 ◽

Vol 143 (10) ◽

pp. 4012-4037 ◽

Cited By ~ 21

Author(s):

Colin M. Zarzycki ◽

Christiane Jablonowski

Keyword(s):

High Resolution ◽

Tropical Cyclone ◽

Initial Conditions ◽

Weather Prediction ◽

Horizontal Resolution ◽

Hurricane Sandy ◽

Track Forecast ◽

Time Step ◽

Variable Resolution ◽

The Impact

Abstract Tropical cyclone (TC) forecasts at 14-km horizontal resolution (0.125°) are completed using variable-resolution (V-R) grids within the Community Atmosphere Model (CAM). Forecasts are integrated twice daily from 1 August to 31 October for both 2012 and 2013, with a high-resolution nest centered over the North Atlantic and eastern Pacific Ocean basins. Using the CAM version 5 (CAM5) physical parameterization package, regional refinement is shown to significantly increase TC track forecast skill relative to unrefined grids (55 km, 0.5°). For typical TC forecast integration periods (approximately 1 week), V-R forecasts are able to nearly identically reproduce the flow field of a globally uniform high-resolution forecast. Simulated intensity is generally too strong for forecasts beyond 72 h. This intensity bias is robust regardless of whether the forecast is forced with observed or climatological sea surface temperatures and is not significantly mitigated in a suite of sensitivity simulations aimed at investigating the impact of model time step and CAM’s deep convection parameterization. Replacing components of the default physics with Cloud Layers Unified by Binormals (CLUBB) produces a statistically significant improvement in forecast intensity at longer lead times, although significant structural differences in forecasted TCs exist. CAM forecasts the recurvature of Hurricane Sandy into the northeastern United States 60 h earlier than the Global Forecast System (GFS) model using identical initial conditions, demonstrating the sensitivity of TC forecasts to model configuration. Computational costs associated with V-R simulations are dramatically decreased relative to globally uniform high-resolution simulations, demonstrating that variable-resolution techniques are a promising tool for future numerical weather prediction applications.

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The impact of GPS and high-resolution radiosonde nudging on the simulation of heavy precipitation during HyMeX IOP6

10.5194/wcd-2021-2 ◽

2021 ◽

Author(s):

Alberto Caldas-Alvarez ◽

Samiro Khodayar ◽

Peter Knippertz

Keyword(s):

High Resolution ◽

Temporal Resolution ◽

Hydrological Cycle ◽

Weather Prediction ◽

Heavy Precipitation ◽

Convective Precipitation ◽

Small Scale ◽

High Temporal Resolution ◽

The Impact

Abstract. Heavy precipitation is one of the most devastating weather extremes in the western Mediterranean region. Our capacity to prevent negative impacts from such extreme events requires advancements in numerical weather prediction, data assimilation and new observation techniques. In this paper we investigate the impact of two state-of-the-art data sets with very high resolution, Global Positioning System-Zenith Total Delays (GPS-ZTD) with a 10 min temporal resolution and radiosondes with ~700 levels, on the representation of convective precipitation in nudging experiments. Specifically, we investigate whether the high temporal resolution, quality, and coverage of GPS-ZTDs can outweigh their lack of vertical information or if radiosonde profiles are more valuable despite their scarce coverage and low temporal resolution (24 h to 6 h). The study focuses on the Intensive Observation Period 6 (IOP6) of the Hydrological Cycle in the Mediterranean eXperiment (HyMeX; 24 September 2012). This event is selected due to its severity (100 mm/12 h), the availability of observations for nudging and validation, and the large observation impact found in preliminary sensitivity experiments. We systematically compare simulations performed with the COnsortium for Small scale MOdelling (COSMO) model assimilating GPS, high- and low vertical resolution radiosoundings in model resolutions of 7 km, 2.8 km and 500 m. The results show that the additional GPS and radiosonde observations cannot compensate errors in the model dynamics and physics. In this regard the reference COSMO runs have an atmospheric moisture wet bias prior to precipitation onset but a negative bias in rainfall, indicative of deficiencies in the numerics and physics, unable to convert the moisture excess into sufficient precipitation. Nudging GPS and high-resolution soundings corrects atmospheric humidity, but even further reduces total precipitation. This case study also demonstrates the potential impact of individual observations in highly unstable environments. We show that assimilating a low-resolution sounding from Nimes (southern France) while precipitation is taking place induces a 40 % increase in precipitation during the subsequent three hours. This precipitation increase is brought about by the moistening of the 700 hPa level (7.5 g kg−1) upstream of the main precipitating systems, reducing the entrainment of dry air above the boundary layer. The moist layer was missed by GPS observations and high-resolution soundings alike, pointing to the importance of profile information and timing. However, assimilating GPS was beneficial for simulating the temporal evolution of precipitation. Finally, regarding the scale dependency, no resolution is particularly sensitive to a specific observation type, however the 2.8 km run has overall better scores, possibly as this is the optimally tuned operational version of COSMO. In follow-up experiments the Icosahedral Nonhydrostatic Model (ICON) will be investigated for this case study to assert whether its numerical and physics updates, compared to its predecessor COSMO, are able to improve the quality of the simulations.

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Satellite-derived Indian methane emission sources with TROPOMI retrievals and a high-resolution modelling framework: Initial comparison with WRF-GHG model results

10.5194/egusphere-egu2020-12559 ◽

2020 ◽

Author(s):

Dhanyalekshmi Pillai ◽

Monish Deshpande ◽

Julia Marshall ◽

Christoph Gerbig ◽

Oliver Schneising ◽

...

Keyword(s):

High Resolution ◽

Greenhouse Gas ◽

Methane Emission ◽

Weather Prediction ◽

Horizontal Resolution ◽

International Standards ◽

Inverse Modelling ◽

Optical Absorption Spectroscopy ◽

Retrieval Algorithm ◽

Modelling Framework

In accordance with the Global stocktake under Article 14 of Paris Agreement, each county estimates its own greenhouse gas (GHG) emissions based on standardised bottom-up management methods. However, the accuracy of these methods along with the standards differs from country to country, resulting in large uncertainties that make it difficult to implement effective climate change mitigation strategies. India plays an important role in global methane emission scenario, necessitating the accurate quantification of its sources at the regional and the local levels. However, the country lacks sufficient long term, continuous and accurate observations of the atmospheric methane which are required to quantify its source, to understand changes in the carbon cycle and the climate system. Recent technological advancements in the use of satellite remote-sensing dedicated to the greenhouse gases enforce international standards for the observation methods; hence enabling those high-resolution-high-density observations to be utilised for this quantification purpose. This study focuses on exploring the use of such dedicated observations of the column-averaged dry-air mixing ratio of methane (XCH4) retrieved from TROPOMI onboard Sentinel-5 Precursor to quantify the major CH4 anthropogenic and natural emission fluxes over India.Our inverse modelling approach at the mesoscale includes a high-resolution atmospheric modelling framework consisting of the Weather Research and Forecasting model with greenhouse gas module (WRF-GHG) and a set of prior emission inventory model data. We use TROPOMI retrievals derived using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS) retrieval algorithm. WRF-GHG simulations are performed in hourly time intervals at a horizontal resolution of&#160;10 km &#215;10 km for a month. In order to compare our CH4 simulations with the satellite column data, we have also taken into account the different vertical sensitivities of the instrument by applying the averaging kernel to the model simulations. To demonstrate the model performance, our simulations are also compared with the CAMS reanalysis product based on ECMWF (European Centre for Medium-Range Weather Forecasts) numerical weather prediction reanalysis data available at a horizontal resolution of&#160;0.25o &#215; 0.25o. Our comparison of these modelling results against unique satellite dataset indicates high potential of using TROPOMI retrievals in distinguishing the major CH4 anthropogenic and natural sources over India via inverse modelling. The results will help to objectively investigate the claims of emission reductions and the efficiency of reduction countermeasures, as well as the establishment of standards and advancement of technology. The details about our approach and preliminary results based on our analysis using above satellite measurements and WRF-GHG simulations over India will be presented.&#160;&#160;&#160;

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