Large-Sample Application of Radar Reflectivity Object-Based Verification to Evaluate HRRR Warm-Season Forecasts

2021 ◽  
Author(s):  
Jeffrey D. Duda ◽  
David D. Turner
Keyword(s):  
Warm Season ◽  
Skill Score ◽  
Central Plains ◽  
Attribute Weights ◽  
Object Based ◽  
Convective Scale ◽  
Heidke Skill Score ◽  
Sample Application ◽  
Storm Cells ◽  
The Impact

AbstractThe Method of Object-based Diagnostic Evaluation (MODE) is used to perform an object-based verification of approximately 1400 forecasts of composite reflectivity from the operational HRRR from April – September 2019. In this study, MODE is configured to prioritize deep, moist convective storm cells typical of those that produce severe weather across the central and eastern US during the warm season. In particular, attributes related to distance and size are given the greatest attribute weights for computing interest in MODE.HRRR tends to over-forecast all objects, but substantially over-forecasts both small objects at low reflectivity thresholds and large objects at high reflectivity thresholds. HRRR tends to either under-forecast objects in the southern and central Plains or has a correct frequency bias there, whereas it over-forecasts objects across the southern and eastern US. Attribute comparisons reveal the inability of the HRRR to fully resolve convective scale features and the impact of data assimilation and loss of skill during the initial hours of the forecasts.Scalar metrics are defined and computed based on MODE output, chiefly relying on the interest value. The object-based threat score (OTS), in particular, reveals similar performance of HRRR forecasts as does the Heidke Skill Score, but with differing magnitudes, suggesting value in adopting an object-based approach to forecast verification. The typical distance between centroids of objects is also analyzed and shows gradual degradation with increasing forecast length.

scholarly journals Impacts of the mountain–plains solenoid and cold pool dynamics on the diurnal variation of warm-season precipitation over northern China

2013 ◽  
Vol 13 (14) ◽  
pp. 6965-6982 ◽  
Author(s):  
◽  
Keyword(s):  
Diurnal Variation ◽  
Initial Conditions ◽  
Wrf Model ◽  
Warm Season ◽  
Northern China ◽  
Early Morning ◽  
Cold Pool ◽  
Mean Flow ◽  
Central Plains ◽  
The Impact

Abstract. Convection-permitting numerical experiments using the Weather Research and Forecasting (WRF) model are performed to examine the impact of a thermally driven mountain–plains solenoid (MPS) on the diurnal variation of warm-season precipitation over northern China. The focus of the analyses is a 15-day simulation that uses the 8-day average of the NCEP GFS gridded analyses at 00:00 UT between 17 and 24 June 2004 for the initial conditions and the 8-day averages at 00:00, 06:00, 12:00, and 18:00 UT for the lateral boundary conditions. Despite differences in rainfall intensity and location, the control experiment captures the essence of the observed diurnal variation of warm-season precipitation in northern China. Consistent with observations, the simulated local precipitation peak initiates in the afternoon on the eastern edge and the immediate lee of the mountain ranges due to the upward branch of the MPS. The peak subsequently propagates downslope and southeastward along the steering-level mean flow, reaching the central North China Plain around midnight and early morning hours, resulting in a broad area of nocturnal precipitation maxima over the central plains. Sensitivity experiments show that, besides the impact of the MPS, cold pool dynamics play an essential role in the propagation and maintenance of the precipitation peak over the plains.

The Impact of Large-Scale Forcing on Skill of Simulated Convective Initiation and Upscale Evolution with Convection-Allowing Grid Spacings in the WRF*

2013 ◽  
Vol 28 (4) ◽  
pp. 994-1018 ◽  
Author(s):  
Jeffrey D. Duda ◽  
William A. Gallus
Keyword(s):  
Large Scale ◽  
Skill Score ◽  
Precipitation Forecast ◽  
Small Scale ◽  
Illustrative Case ◽  
Convective Initiation ◽  
Convective Systems ◽  
Object Based ◽  
Mesoscale Convective ◽  
The Impact

Abstract A set of mesoscale convective systems (MCSs) was simulated using the Weather Research and Forecasting model with 3-km grid spacing to investigate the skill at predicting convective initiation and upscale evolution into an MCS. Precipitation was verified using equitable threat scores (ETSs), the neighborhood-based fractions skill score (FSS), and the Method of Object-Based Diagnostic Evaluation. An illustrative case study more closely examines the strong influence that smaller-scale forcing features had on convective initiation. Initiation errors for the 36 cases were in the south-southwest direction on average, with a mean absolute displacement error of 105 km. No systematic temporal error existed, as the errors were approximately normally distributed. Despite earlier findings that quantitative precipitation forecast skill in convection-parameterizing simulations is a function of the strength of large-scale forcing, this relationship was not present in the present study for convective initiation. However, upscale evolution was better predicted for more strongly forced events according to ETSs and FSSs. For the upscale evolution, the relationship between ETSs and object-based ratings was poor. There was also little correspondence between object-based ratings and the skill at convective initiation. The lack of a relationship between the strength of large-scale forcing and model skill at forecasting initiation is likely due to a combination of factors, including the strong role of small-scale features that exert an influence on initiation, and potential errors in the analyses used to represent observations. The limit of predictability of individual convective storms on a 3-km grid must also be considered.

scholarly journals The Impact of Different WRF Model Physical Parameterizations and Their Interactions on Warm Season MCS Rainfall

2005 ◽  
Vol 20 (6) ◽  
pp. 1048-1060 ◽  
Author(s):  
Isidora Jankov ◽  
William A. Gallus ◽  
Moti Segal ◽  
Brent Shaw ◽  
Steven E. Koch
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Wrf Model ◽  
Warm Season ◽  
Mesoscale Convective System ◽  
Skill Score ◽  
Convective System ◽  
Mesoscale Convective ◽  
Physics Ensemble ◽  
The Impact

Abstract In recent years, a mixed-physics ensemble approach has been investigated as a method to better predict mesoscale convective system (MCS) rainfall. For both mixed-physics ensemble design and interpretation, knowledge of the general impact of various physical schemes and their interactions on warm season MCS rainfall forecasts would be useful. Adopting the newly emerging Weather Research and Forecasting (WRF) model for this purpose would further emphasize such benefits. To pursue this goal, a matrix of 18 WRF model configurations, created using different physical scheme combinations, was run with 12-km grid spacing for eight International H2O Project (IHOP) MCS cases. For each case, three different treatments of convection, three different microphysical schemes, and two different planetary boundary layer schemes were used. Sensitivity to physics changes was determined using the correspondence ratio and the squared correlation coefficient. The factor separation method was also used to quantify in detail the impacts of the variation of two different physical schemes and their interaction on the simulated rainfall. Skill score measures averaged over all eight cases for all 18 configurations indicated that no one configuration was obviously best at all times and thresholds. The greatest variability in forecasts was found to come from changes in the choice of convective scheme, although notable impacts also occurred from changes in the microphysics and planetary boundary layer (PBL) schemes. Specifically, changes in convective treatment notably impacted the forecast of system average rain rate, while forecasts of total domain rain volume were influenced by choices of microphysics and convective treatment. The impact of interactions (synergy) of different physical schemes, although occasionally of comparable magnitude to the impacts from changing one scheme alone (compared to a control run), varied greatly among cases and over time, and was typically not statistically significant.

A Predictive Model of the Impact of the Skidding System on Forest Soil in Severe Climatic Conditions

2020 ◽  
pp. 131-144
Author(s):  
S.E. Rudov ◽  
◽  
V.Ya. Shapiro ◽  
O.I. Grigoreva ◽  
I.V. Grigorev ◽  
...  
Keyword(s):  
Forest Soil ◽  
Warm Season ◽  
Climatic Conditions ◽  
Soil Freezing ◽  
Class Iii ◽  
Freezing And Thawing ◽  
Metal Structures ◽  
Rapid Adjustment ◽  
Soil Freezing And Thawing ◽  
The Impact

In the Russian Federation logging operations are traditionally carried out in winter. This is due to the predominance of areas with swamped and water-logged (class III and IV) soils in the forest fund, where work of forestry equipment is difficult, and sometimes impossible in the warm season. The work of logging companies in the forests of the cryolithozone, characterized by a sharply continental climate, with severe frosts in winter, is hampered by the fact that forest machines are not recommended to operate at temperatures below –40 °C due to the high probability of breaking of metal structures and hydraulic system. At the same time, in the warm season, most of the cutting areas on cryosolic soils become difficult to pass for heavy forest machines. It turns out that the convenient period for logging in the forests of the cryolithozone is quite small. This results in the need of work in the so-called off-season period, when the air temperature becomes positive, and the thawing processes of the soil top layer begin. The same applies to the logging companies not operating in the conditions of cryosolic soils, for instance, in the Leningrad, Novgorod, Pskov, Vologda regions, etc. The observed climate warming has led to a significant reduction in the sustained period of winter logging. Frequent temperature transitions around 0 °C in winter, autumn and spring necessitate to work during the off-season too, while cutting areas thaw. In bad seasonal and climatic conditions, which primarily include off-season periods in general and permafrost in particular, it is very difficult to take into account in mathematical models features of soil freezing and thawing and their effect on the destruction nature. The article shows that the development of long-term predictive models of indicators of cyclic interaction between the skidding system and forest soil in adverse climatic conditions of off-season logging operations in order to improve their reliability requires rapid adjustment of the calculated parameters based on the actual experimental data at a given step of the cycles.

scholarly journals The Midlatitude Continental Convective Clouds Experiment (MC3E) sounding network: operations, processing and analysis

2015 ◽  
Vol 8 (1) ◽  
pp. 421-434 ◽  
Author(s):  
M. P. Jensen ◽  
T. Toto ◽  
D. Troyan ◽  
P. E. Ciesielski ◽  
D. Holdridge ◽  
...  
Keyword(s):  
Large Scale ◽  
Scale Model ◽  
Data Sets ◽  
Central Plains ◽  
Data Set ◽  
Convective Systems ◽  
Convective Clouds ◽  
Quality Checks ◽  
Network Operations ◽  
The Impact

Abstract. The Midlatitude Continental Convective Clouds Experiment (MC3E) took place during the spring of 2011 centered in north-central Oklahoma, USA. The main goal of this field campaign was to capture the dynamical and microphysical characteristics of precipitating convective systems in the US Central Plains. A major component of the campaign was a six-site radiosonde array designed to capture the large-scale variability of the atmospheric state with the intent of deriving model forcing data sets. Over the course of the 46-day MC3E campaign, a total of 1362 radiosondes were launched from the enhanced sonde network. This manuscript provides details on the instrumentation used as part of the sounding array, the data processing activities including quality checks and humidity bias corrections and an analysis of the impacts of bias correction and algorithm assumptions on the determination of convective levels and indices. It is found that corrections for known radiosonde humidity biases and assumptions regarding the characteristics of the surface convective parcel result in significant differences in the derived values of convective levels and indices in many soundings. In addition, the impact of including the humidity corrections and quality controls on the thermodynamic profiles that are used in the derivation of a large-scale model forcing data set are investigated. The results show a significant impact on the derived large-scale vertical velocity field illustrating the importance of addressing these humidity biases.

Future changes in heatwaves over Africa at the convection-permitting scale

2021 ◽  
Author(s):  
Cathryn Birch ◽  
Lawrence Jackson ◽  
Declan Finney ◽  
John Marsham ◽  
Rachel Stratton ◽  
...  
Keyword(s):  
Climate Model ◽  
Daily Rainfall ◽  
Shortwave Radiation ◽  
Daily Maximum ◽  
Future Change ◽  
Driving Mechanisms ◽  
The Future ◽  
Convective Scale ◽  
Climate Model Simulations ◽  
The Impact

<p>Mean temperatures and their extremes have increased over Africa since the latter half of the 20th century and this trend is projected to continue, with very frequent, intense and often deadly heatwaves likely to occur very regularly over much of Africa by 2100. It is crucial that we understand the scale of the future increases in extremes and the driving mechanisms. We diagnose daily maximum wet bulb temperature heatwaves, which allows for both the impact of temperature and humidity, both critical for human health and survivability. During wet bulb heatwaves, humidity and cloud cover increase, which limits the surface shortwave radiation flux but increases longwave warming. It is found from observations and ERA5 reanalysis that approximately 30% of wet bulb heatwaves over Africa are associated with daily rainfall accumulations of more than 1 mm/day on the first day of the heatwave. The first ever pan-African convection-permitting climate model simulations of present-day and RCP8.5 future climate are utilised to illustrate the projected future change in heatwaves, their drivers and their sensitivity to the representation of convection. Compared to ERA5, the convection-permitting model better represents the frequency and magnitude of present-day wet bulb heatwaves than a version of the model with more traditional parameterised convection. The future change in heatwave frequency, duration and magnitude is also larger in the convective-scale simulation, suggesting CMIP-style models may underestimate the future change in wet bulb heat extremes over Africa. The main reason for the larger future change appears to be the ability of the model to produce larger anomalies relative to its climatology in precipitation, cloud and the surface energy balance.</p>

scholarly journals Investigation of post-depositional processing of nitrate in East Antarctic snow: isotopic constraints on photolytic loss, re-oxidation, and source inputs

2015 ◽  
Vol 15 (16) ◽  
pp. 9435-9453 ◽  
Author(s):  
G. Shi ◽  
A. M. Buffen ◽  
M. G. Hastings ◽  
C. Li ◽  
H. Ma ◽  
...  
Keyword(s):  
Isotopic Composition ◽  
Mass Fraction ◽  
Stratospheric Ozone ◽  
Warm Season ◽  
Cold Season ◽  
Depth Interval ◽  
Depositional Processes ◽  
Antarctic Snow ◽  
Exponential Change ◽  
The Impact

Abstract. Snowpits along a traverse from coastal East Antarctica to the summit of the ice sheet (Dome Argus) are used to investigate the post-depositional processing of nitrate (NO3−) in snow. Seven snowpits from sites with accumulation rates between 24 and 172 kg m−2 a−1 were sampled to depths of 150 to 300 cm. At sites from the continental interior (low accumulation, < 55 kg m−2 a−1), nitrate mass fraction is generally > 200 ng g−1 in surface snow and decreases quickly with depth to < 50 ng g−1. Considerably increasing values of δ15N of nitrate are also observed (16–461 ‰ vs. air N2), particularly in the top 20 cm, which is consistent with predicted fractionation constants for the photolysis of nitrate. The δ18O of nitrate (17–84 ‰ vs. VSMOW (Vienna Standard Mean Ocean Water)), on the other hand, decreases with increasing δ15N, suggestive of secondary formation of nitrate in situ (following photolysis) with a low δ18O source. Previous studies have suggested that δ15N and δ18O of nitrate at deeper snow depths should be predictable based upon an exponential change derived near the surface. At deeper depths sampled in this study, however, the relationship between nitrate mass fraction and δ18O changes, with increasing δ18O of nitrate observed between 100 and 200 cm. Predicting the impact of post-depositional loss, and therefore changes in the isotopes with depth, is highly sensitive to the depth interval over which an exponential change is assumed. In the snowpits collected closer to the coast (accumulation > 91 kg m−2 a−1), there are no obvious trends detected with depth and instead seasonality in nitrate mass fraction and isotopic composition is found. In comparison to the interior sites, the coastal pits are lower in δ15N (−15–71 ‰ vs. air N2) and higher in δ18O of nitrate (53–111 ‰ vs. VSMOW). The relationships found amongst mass fraction, δ15N, δ18O and Δ17O (Δ17O = δ17O–0.52 × δ18O) of nitrate cannot be explained by local post-depositional processes alone, and are instead interpreted in the context of a primary atmospheric signal. Consistent with other Antarctic observational and modeling studies, the isotopic results are suggestive of an important influence of stratospheric ozone chemistry on nitrate formation during the cold season and a mix of tropospheric sources and chemistry during the warm season. Overall, the findings in this study speak to the sensitivity of nitrate isotopic composition to post-depositional processing and highlight the strength of combined use of the nitrogen and oxygen isotopes for a mechanistic understanding of this processing.

scholarly journals Nitrogen and harvest impact on warm-season grass biomass yield and feedstock quality

2017 ◽  
Author(s):  
◽  
Chamara Sandaruwan Weerasekara Imbulana Acharige
Keyword(s):  
Biomass Yield ◽  
Warm Season ◽  
Early Spring ◽  
Harvest Date ◽  
Feedstock Quality ◽  
Harvest Timing ◽  
Bioenergy Feedstocks ◽  
Partial Factor ◽  
The Impact ◽  
Warm Season Grasses

Perennial warm-season grasses including switchgrass (Panicum virgatum L.), big bluestem (Andropogon geradii Vitman), and Indiangrass (Sorghastrum nutans L.) have drawn interest as bioenergy feedstocks due to their high yielding capacity with minimal amounts of inputs under a wide range of environments, and their capability to produce multiple environmental benefits. Nitrogen (N) fertility and harvest timing are considered as critical management practices when optimizing biomass yield and the feedstock quality of these grasses. The objective of this investigation was to quantify the impact of N fertilizer rate, N timing and harvest date on warm season biomass dry matter yield. Research was conducted in 2014 and 2015 on a total of four field-plot locations situated in central and west-central Missouri. Nitrogen fertilizer was applied using dry ammonium nitrate at the rates of 0, 34, 67, and 101 kg ha-1 at two application times, all N early spring and split N (early spring and following 1st harvest). Harvest treatments were as follows: 1) one cut in September; 2) one cut in November; 3) one cut in June and a second in September; and 4) one cut in June and a second in November. Treatments were arranged in a split-plot design with N rate as the main plot and harvest as the sub-plot in arandomized complete block design. Both N and harvest date and their interactions impacted biomass yield at all four locations. Delaying harvesting until late fall or killing frost increased yield. November harvest in combination with N rates grater than or equal to 67 kg ha-1 year-1 produced higher yields compared to the control and 34 kg ha-1N treatments and other harvest timing strategies. Although N was needed to optimize yield, partial factor 24 productivity (PFP) of applied N was flat when N applied was greater than 34 kg ha-1. Nitrogen fertilization at 67 kg ha-1 per growing season provided an opportunity to maintain a balance between both yield and efficiency of N inputs. Results of this research highlight the interactions of N fertilization and harvest management have when optimizing yield of warm-season grasses grown as bioenergy feedstocks. List of acronyms: N, Nitrogen; PFP, partial factor productivity.

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