scholarly journals Analysis of Missed Summer Severe Rainfall Forecasts

2016 ◽  
Vol 31 (2) ◽  
pp. 433-450 ◽  
Author(s):  
Zuohao Cao ◽  
Da-Lin Zhang
Keyword(s):  
Convective Instability ◽  
Weather Prediction ◽  
Convective Available Potential Energy ◽  
Vertical Motion ◽  
Cloud Water ◽  
Initial Condition ◽  
Latent Heating ◽  
Initial Model ◽  
Training Process ◽  
Nwp Model

Abstract Despite considerable progress in mesoscale numerical weather prediction (NWP), the ability to predict summer severe rainfall (SSR) in terms of amount, location, and timing remains very limited because of its association with convective or mesoscale phenomena. In this study, two representative missed SSR events that occurred in the highly populated Great Lakes regions are analyzed within the context of moisture availability, convective instability, and lifting mechanism in order to help identify the possible causes of these events and improve SSR forecasts/nowcasts. Results reveal the following limitations of the Canadian regional NWP model in predicting SSR events: 1) the model-predicted rainfall is phase shifted to an undesired location that is likely caused by the model initial condition errors, and 2) the model is unable to resolve the echo-training process because of the weakness of the parameterized convection and/or coarse resolutions. These limitations are related to the ensuing model-predicted features: 1) vertical motion in the areas of SSR occurrence is unfavorable for triggering parameterized convection and grid-scale condensation; 2) convective available potential energy is lacking for initial model spinup and later for elevating latent heating to higher levels through parameterized convection, giving rise to less precipitation; and 3) the conversion of water vapor into cloud water at the upper and middle levels is underpredicted. Recommendations for future improvements are discussed.

scholarly journals Application of Adjoint-Derived Forecast Sensitivities to the 24–25 January 2000 U.S. East Coast Snowstorm

2005 ◽  
Vol 133 (11) ◽  
pp. 3148-3175 ◽  
Author(s):  
Daryl T. Kleist ◽  
Michael C. Morgan
Keyword(s):  
Response Function ◽  
Initial Conditions ◽  
Forecast Error ◽  
Weather Prediction ◽  
Lower Troposphere ◽  
Vertical Motion ◽  
Initial Condition ◽  
Response Functions ◽  
Eastern United States ◽  
Surface Cyclone

Abstract The 24–25 January 2000 eastern United States snowstorm was noteworthy as operational numerical weather prediction (NWP) guidance was poor for lead times as short as 36 h. Despite improvements in the forecast of the surface cyclone position and intensity at 1200 UTC 25 January 2000 with decreasing lead time, NWP guidance placed the westward extent of the midtropospheric, frontogenetically forced precipitation shield too far to the east. To assess the influence of initial condition uncertainties on the forecast of this event, an adjoint model is used to evaluate forecast sensitivities for 36- and 48-h forecasts valid at 1200 UTC 25 January 2000 using as response functions the energy-weighted forecast error, lower-tropospheric circulation about a box surrounding the surface cyclone, 750-hPa frontogenesis, and vertical motion. The sensitivities with respect to the initial conditions for these response functions are in general very similar: geographically isolated, maximized in the middle and lower troposphere, and possessing an upshear vertical tilt. The sensitivities are maximized in a region of enhanced low-level baroclinicity in the vicinity of the surface cyclone’s precursor upper trough. However, differences in the phase and structure of the gradients for the four response functions are evident, which suggests that perturbations could be constructed to alter one response function but not necessarily the others. Gradients of the forecast error response function with respect to the initial conditions are used in an iterative procedure to construct initial condition perturbations that reduce the forecast error. These initial condition perturbations were small in terms of both spatial scale and magnitude. Those initial condition perturbations that were confined primarily to the midtroposphere grew rapidly into much larger amplitude upper-and-lower tropospheric perturbations. The perturbed forecasts were not only characterized by reduced final time forecast error, but also had a synoptic evolution that more closely followed analyses and observations.

First model evaluations of height-resolved diurnal water vapour cycles using lidar observations in an Arctic environment

2021 ◽  
Author(s):  
Shannon Hicks-Jalali ◽  
Zen Mariani ◽  
Barbara Casati ◽  
Sylvie Leroyer ◽  
Francois Lemay ◽  
...  
Keyword(s):  
Solar Cycle ◽  
Water Vapour ◽  
Diurnal Cycle ◽  
Weather Prediction ◽  
Vertical Motion ◽  
The Arctic ◽  
Diurnal Cycles ◽  
Surface Station ◽  
Nwp Model ◽  
Total Column

<p>Atmospheric water vapour is a critical component of both meteorological and climatological processes. It is the dominant gas in the greenhouse effect and its diurnal cycle is an essential component of the hydrological cycle. Diurnal water vapour cycles are complex and are a product of several mechanisms, including (but not necessarily limited to): evapotranspiration, advection, large-scale vertical motion, and precipitation. They are dependent on local geography, as well as latitude. Numerical Weather Prediction (NWP) models rely on high-quality water vapour input to provide accurate forecasts, which is particularly difficult in the Arctic due to its extreme weather and harsh environment. Diurnal water vapour cycle observations are also excellent tools for evaluating NWPs due to their complex nature and dependence on multiple processes. Integrated water vapour (IWV), or total column, diurnal water vapour cycles, usually calculated with Global Navigation Satellite Systems (GNSS) instruments, have been the focus of most previous diurnal WV studies; however, height-resolved diurnal cycles provide a more complete picture of the diurnal mechanisms and include vertical motion, which cannot be discerned via IWV measurements. Differential Absorption Lidars (DIALs) are well suited to providing height-resolved diurnal cycles in the boundary layer due to their high vertical and temporal resolution.</p><p>We use the novel Vaisala pre-production DIAL, installed in Iqaluit, Nunavut (63.75 N, 68.55 W), to calculate seasonal height-resolved diurnal WV cycles from 100 m to 1500 m altitude. We also calculate the surface and total column WV diurnal cycles using co-located surface station and GNSS measurements. We find that the first 250 m of the DIAL diurnal cycle magnitudes agree well with the surface station measurements. The phases of the cycle do shift with altitude, and the amplitudes generally increase with altitude. In the summer, all instruments observe a strong 24 hr cycle. As the amount of solar radiation decreases over the year, the 24 hr cycle weakens and the 12 hr cycle begins to dominate in all instruments. While we find a strong correlation between the 24 hr cycle and the solar cycle, we do not observe any correlation between the 12 hr cycle and the solar cycle. Finally, we also compare the DIAL observations to the Environment and Climate Change Canada (ECCC) NWP model. We evaluate both the assimilation of the humidity input and initial water vapour fields, as well as the diurnal cycle over the 24 hour forecast. Future work will include case study comparisons with the Canadian NWP model to assess the model’s ability to resolve rapid changes in diurnal water vapour.</p>

scholarly journals A Hybrid NWP–Analog Ensemble

2016 ◽  
Vol 144 (3) ◽  
pp. 897-911 ◽  
Author(s):  
F. Anthony Eckel ◽  
Luca Delle Monache
Keyword(s):  
Real Time ◽  
Weather Prediction ◽  
Ensemble Member ◽  
Initial Condition ◽  
Error Growth ◽  
High Quality ◽  
Time Model ◽  
Probabilistic Forecasts ◽  
Nwp Model ◽  
Dependent Error

Abstract An analog ensemble (AnEn) is constructed by first matching up the current forecast from a numerical weather prediction (NWP) model with similar past forecasts. The verifying observation from each match is then used as an ensemble member. For at least some applications, the advantages of AnEn over an NWP ensemble (multiple real-time model runs) may include higher efficiency, avoidance of initial condition and model perturbation challenges, and little or no need for postprocessing calibration. While AnEn can capture flow-dependent error growth, it may miss aspects of error growth that can be represented dynamically by the multiple real-time model runs of an NWP ensemble. To combine the strengths of the AnEn and NWP ensemble approaches, a hybrid ensemble (HyEn) is constructed by finding m analogs for each member of a small n-member NWP ensemble, to produce a total of m × n members. Forecast skill is compared between the AnEn, HyEn, and an NWP ensemble calibrated using logistic regression. The HyEn outperforms the other approaches for probabilistic 2-m temperature forecasts yet underperforms for 10-m wind speed. The mixed results reveal a dependence on the intrinsic skill of the NWP members employed. In this study, the NWP ensemble is underspread for both 2-m temperature and 10-m winds, yet displays some ability to represent flow-dependent error for the former and not the latter. Thus, the HyEn is a promising approach for efficient generation of high-quality probabilistic forecasts, but requires use of a small, and at least partially functional, NWP ensemble.

scholarly journals Banded Convection Caused by Frontogenesis in a Conditionally, Symmetrically, and Inertially Unstable Environment

2007 ◽  
Vol 135 (6) ◽  
pp. 2095-2110 ◽  
Author(s):  
David M. Schultz ◽  
John A. Knox
Keyword(s):  
Weather Prediction ◽  
Convective Available Potential Energy ◽  
Vertical Motion ◽  
Numerical Weather Prediction Model ◽  
Intense Band ◽  
Light Rain ◽  
Inertial Instability ◽  
Unstable Environment ◽  
Lifting Condensation Level ◽  
East West

Abstract Several east–west-oriented bands of clouds and light rain formed on 20 July 2005 over eastern Montana and the Dakotas. The cloud bands were spaced about 150 km apart, and the most intense band was about 20 km wide and 300 km long, featuring areas of maximum radar reflectivity factor of about 50 dBZ. The cloud bands formed poleward of an area of lower-tropospheric frontogenesis, where air of modest convective available potential energy was being lifted. During initiation and maintenance of the bands, mesoscale regions of dry symmetric and inertial instability were present in the region of the bands, suggesting a possible mechanism for the banding. Interpretation of the extant instabilities in the region of the bands was sensitive to the methodology to assess the instability. The release of these instabilities produced circulations with enough vertical motion to lift parcels to their lifting condensation level, resulting in the observed cloud bands. A high-resolution, numerical weather prediction model demonstrated that forecasting these types of events in such real-time models is possible, although the timing, evolution, and spacing of the bands were not faithfully reproduced. This case is compared to two previous cases in the literature where banded convection was associated with a combination of conditional, symmetric, and inertial instability.

scholarly journals Evaluation of WRF-DART (ARW v3.9.1.1 and DART Manhattan release) multiphase cloud water path assimilation for short-term solar irradiance forecasting in a tropical environment

2019 ◽  
Vol 12 (9) ◽  
pp. 3939-3954
Author(s):  
Frederik Kurzrock ◽  
Hannah Nguyen ◽  
Jerome Sauer ◽  
Fabrice Chane Ming ◽  
Sylvain Cros ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Weather Prediction ◽  
Cloud Water ◽  
Specific Humidity ◽  
Reunion Island ◽  
Short Term ◽  
Water Path ◽  
Réunion Island ◽  
Cloud Water Path ◽  
The Impact

Abstract. Numerical weather prediction models tend to underestimate cloud presence and therefore often overestimate global horizontal irradiance (GHI). The assimilation of cloud water path (CWP) retrievals from geostationary satellites using an ensemble Kalman filter (EnKF) led to improved short-term GHI forecasts of the Weather Research and Forecasting (WRF) model in midlatitudes in case studies. An evaluation of the method under tropical conditions and a quantification of this improvement for study periods of more than a few days are still missing. This paper focuses on the assimilation of CWP retrievals in three phases (ice, supercooled, and liquid) in a 6-hourly cycling procedure and on the impact of this method on short-term forecasts of GHI for Réunion Island, a tropical island in the southwest Indian Ocean. The multilayer gridded cloud properties of NASA Langley's Satellite ClOud and Radiation Property retrieval System (SatCORPS) are assimilated using the EnKF of the Data Assimilation Research Testbed (DART) Manhattan release (revision 12002) and the advanced research WRF (ARW) v3.9.1.1. The ability of the method to improve cloud analyses and GHI forecasts is demonstrated, and a comparison using independent radiosoundings shows a reduction of specific humidity bias in the WRF analyses, especially in the low and middle troposphere. Ground-based GHI observations at 12 sites on Réunion Island are used to quantify the impact of CWP DA. Over a total of 44 d during austral summertime, when averaged over all sites, CWP data assimilation has a positive impact on GHI forecasts for all lead times between 5 and 14 h. Root mean square error and mean absolute error are reduced by 4 % and 3 %, respectively.

UTCI as the NWP model ALADIN (CHMI) output – first experiences

2021 ◽  
Vol 94 (2) ◽  
pp. 237-249
Author(s):  
Martin Novák
Keyword(s):  
Numerical Weather Prediction ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Climate Index ◽  
Basic Information ◽  
Universal Thermal Climate Index ◽  
Numerical Weather ◽  
Weather Forecasters ◽  
Thermal Climate ◽  
Nwp Model

The article includes a summary of basic information about the Universal Thermal Climate Index (UTCI) calculation by the numerical weather prediction (NWP) model ALADIN of the Czech Hydrometeorological Institute (CHMI). Examples of operational outputs for weather forecasters in the CHMI are shown in the first part of this work. The second part includes results of a comparison of computed UTCI values by ALADIN for selected place with UTCI values computed from real measured meteorological data from the same place.

scholarly journals Detection and thermal description of medicanes from numerical simulation

2014 ◽  
Vol 14 (5) ◽  
pp. 1059-1070 ◽  
Author(s):  
M. A. Picornell ◽  
J. Campins ◽  
A. Jansà
Keyword(s):  
Numerical Simulation ◽  
Thermal Structure ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Small Scale ◽  
Medium Range Weather Forecast ◽  
Warm Core ◽  
Strong Winds ◽  
Nwp Model ◽  
Ecmwf Model

Abstract. Tropical-like cyclones rarely affect the Mediterranean region but they can produce strong winds and heavy precipitations. These warm-core cyclones, called MEDICANES (MEDIterranean hurriCANES), are small in size, develop over the sea and are infrequent. For these reasons, the detection and forecast of medicanes are a difficult task and many efforts have been devoted to identify them. The goals of this work are to contribute to a proper description of these structures and to develop some criteria to identify medicanes from numerical weather prediction (NWP) model outputs. To do that, existing methodologies for detecting, characterizating and tracking cyclones have been adapted to small-scale intense cyclonic perturbations. First, a mesocyclone detection and tracking algorithm has been modified to select intense cyclones. Next, the parameters that define the Hart's cyclone phase diagram are tuned and calculated to examine their thermal structure. Four well-known medicane events have been described from numerical simulation outputs of the European Centre for Medium-Range Weather Forecast (ECMWF) model. The predicted cyclones and their evolution have been validated against available observational data and numerical analyses from the literature.

scholarly journals Toward a Weather-Based Forecasting System for Fire Blight and Downy Mildew

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 484 ◽  
Author(s):  
Ana Firanj Sremac ◽  
Branislava Lalić ◽  
Milena Marčić ◽  
Ljiljana Dekić
Keyword(s):  
Downy Mildew ◽  
Fire Blight ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Atmospheric Model ◽  
Plasmopara Viticola ◽  
Forecasting System ◽  
Nwp Model ◽  
The Impact

The aim of this research is to present a weather-based forecasting system for apple fire blight (Erwinia amylovora) and downy mildew of grapevine (Plasmopara viticola) under Serbian agroecological conditions and test its efficacy. The weather-based forecasting system contains Numerical Weather Prediction (NWP) model outputs and a disease occurrence model. The weather forecast used is a product of the high-resolution forecast (HRES) atmospheric model by the European Centre for Medium-Range Weather Forecasts (ECMWF). For disease modelling, we selected a biometeorological system for messages on the occurrence of diseases in fruits and vines (BAHUS) because it contains both diseases with well-known and tested algorithms. Several comparisons were made: (1) forecasted variables for the fifth day are compared against measurements from the agrometeorological network at seven locations for three months (March, April, and May) in the period 2012–2018 to determine forecast efficacy; (2) BAHUS runs driven with observed and forecast meteorology were compared to test the impact of forecasted meteorological data; and (3) BAHUS runs were compared with field disease observations to estimate system efficacy in plant disease forecasts. The BAHUS runs with forecasted and observed meteorology were in good agreement. The results obtained encourage further development, with the goal of fully utilizing this weather-based forecasting system.

Practical and Intrinsic Predictability of Severe and Convective Weather at the Mesoscales

2012 ◽  
Vol 69 (11) ◽  
pp. 3350-3371 ◽  
Author(s):  
Christopher Melhauser ◽  
Fuqing Zhang
Keyword(s):  
Weather Prediction ◽  
Squall Line ◽  
Cold Pool ◽  
Initial Condition ◽  
Large Variability ◽  
Forecast Performance ◽  
Sensitivity Experiments ◽  
Bow Echo ◽  
Upper Level ◽  
Convective Weather

Abstract This study explores both the practical and intrinsic predictability of severe convective weather at the mesoscales using convection-permitting ensemble simulations of a squall line and bow echo event during the Bow Echo and Mesoscale Convective Vortex (MCV) Experiment (BAMEX) on 9–10 June 2003. Although most ensemble members—initialized with realistic initial condition uncertainties smaller than the NCEP Global Forecast System Final Analysis (GFS FNL) using an ensemble Kalman filter—forecast broad areas of severe convection, there is a large variability of forecast performance among different members, highlighting the limit of practical predictability. In general, the best-performing members tend to have a stronger upper-level trough and associated surface low, producing a more conducive environment for strong long-lived squall lines and bow echoes, once triggered. The divergence in development is a combination of a dislocation of the upper-level trough, surface low with corresponding marginal environmental differences between developing and nondeveloping members, and cold pool evolution by deep convection prior to squall line formation. To further explore the intrinsic predictability of the storm, a sequence of sensitivity experiments was performed with the initial condition differences decreased to nearly an order of magnitude smaller than typical analysis and observation errors. The ensemble forecast and additional sensitivity experiments demonstrate that this storm has a limited practical predictability, which may be further improved with more accurate initial conditions. However, it is possible that the true storm could be near the point of bifurcation, where predictability is intrinsically limited. The limits of both practical and intrinsic predictability highlight the need for probabilistic and ensemble forecasts for severe weather prediction.

scholarly journals Analysis of Severe Elevated Thunderstorms over Frontal Surfaces Using DCIN and DCAPE

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 449
Author(s):  
Patrick Market ◽  
Kevin Grempler ◽  
Paula Sumrall ◽  
Chasity Henson
Keyword(s):  
Weather Prediction ◽  
Convective Available Potential Energy ◽  
Numerical Weather Prediction Model ◽  
Surface Boundary ◽  
Storm Events ◽  
Cold Side ◽  
Severe Thunderstorms ◽  
Stable Surface Layer ◽  
Different Populations ◽  
Convective Inhibition

A 10-year study of elevated severe thunderstorms was performed using The National Centers for Environmental Information Storm Events Database. A total of 80 elevated thunderstorm cases were identified, verified, and divided into “Prolific” and “Marginal” classes. These severe cases occurred at least 80 km away from, and on the cold side of, a surface boundary. The downdraft convective available potential energy (DCAPE), downdraft convective inhibition (DCIN), and their ratio are tools to help estimate the potential for a downdraft to penetrate through the depth of a stable surface layer. The hypothesis is that as the DCIN/DCAPE ratio decreases, there exists enhanced possibility of severe surface winds. Using the initial fields from the Rapid Refresh numerical weather prediction model, datasets of DCIN, DCAPE, and their ratio were created. Mann-Whitney U tests on the Prolific versus Marginal case sets were undertaken to determine if the DCAPE and DCIN values come from different populations for the two different case sets. Results show that the Prolific cases have values of DCIN closer to zero, suggesting the downdraft is able to penetrate to the surface causing severe winds. Thus, comparing DCIN and DCAPE is a viable tool in determining if downdrafts will reach the surface from elevated thunderstorms.

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