scholarly journals A Method for Probability Matching Based on the Ensemble Maximum for Quantitative Precipitation Forecasts

2020 ◽  
Vol 148 (8) ◽  
pp. 3379-3396
Author(s):  
Xiaoshi Qiao ◽  
Shizhang Wang ◽  
Craig S. Schwartz ◽  
Zhiquan Liu ◽  
Jinzhong Min
Keyword(s):  
Rare Events ◽  
Heavy Precipitation ◽  
Skill Score ◽  
Grid Spacing ◽  
Probability Matching ◽  
Ensemble Mean ◽  
Quantitative Precipitation Forecasts ◽  
Horizontal Grid ◽  
Light Precipitation

Abstract A probability matching (PM) product using the ensemble maximum (EnMax) as the basis for spatial reassignment was developed. This PM product was called the PM max and its localized version was called the local PM (LPM) max. Both products were generated from a 10-member ensemble with 3-km horizontal grid spacing and evaluated over 364 36-h forecasts in terms of the fractions skill score. Performances of the PM max and LPM max were compared to those of the traditional PM mean and LPM mean, which both used the ensemble mean (EnMean) as the basis for spatial reassignment. Compared to observations, the PM max typically outperformed the PM mean for precipitation rates ≥5 mm h−1; this improvement was related to the EnMax, which had better spatial placement than the EnMean for heavy precipitation. However, the PM mean produced better forecasts than the PM max for lighter precipitation. It appears that the global reassignment used to produce the PM max was responsible for its poorer performance relative to the PM mean at light precipitation rates, as the LPM max was more skillful than the LPM mean at all thresholds. These results suggest promise for PM products based on the EnMax, especially for rare events and ensembles with insufficient spread.

Initial Conditions for Convection-Allowing Ensembles over the Conterminous United States

2020 ◽  
Vol 148 (7) ◽  
pp. 2645-2669
Author(s):  
Craig S. Schwartz ◽  
May Wong ◽  
Glen S. Romine ◽  
Ryan A. Sobash ◽  
Kathryn R. Fossell
Keyword(s):  
United States ◽  
Ensemble Kalman Filter ◽  
Initial Conditions ◽  
Limited Area ◽  
Grid Spacing ◽  
Forecast System ◽  
Skill Scores ◽  
Ensemble Mean ◽  
Horizontal Grid ◽  
Better Than

Abstract Five sets of 48-h, 10-member, convection-allowing ensemble (CAE) forecasts with 3-km horizontal grid spacing were systematically evaluated over the conterminous United States with a focus on precipitation across 31 cases. The various CAEs solely differed by their initial condition perturbations (ICPs) and central initial states. CAEs initially centered about deterministic Global Forecast System (GFS) analyses were unequivocally better than those initially centered about ensemble mean analyses produced by a limited-area single-physics, single-dynamics 15-km continuously cycling ensemble Kalman filter (EnKF), strongly suggesting relative superiority of the GFS analyses. Additionally, CAEs with flow-dependent ICPs derived from either the EnKF or multimodel 3-h forecasts from the Short-Range Ensemble Forecast (SREF) system had higher fractions skill scores than CAEs with randomly generated mesoscale ICPs. Conversely, due to insufficient spread, CAEs with EnKF ICPs had worse reliability, discrimination, and dispersion than those with random and SREF ICPs. However, members in the CAE with SREF ICPs undesirably clustered by dynamic core represented in the ICPs, and CAEs with random ICPs had poor spinup characteristics. Collectively, these results indicate that continuously cycled EnKF mean analyses were suboptimal for CAE initialization purposes and suggest that further work to improve limited-area continuously cycling EnKFs over large regional domains is warranted. Additionally, the deleterious aspects of using both multimodel and random ICPs suggest efforts toward improving spread in CAEs with single-physics, single-dynamics, flow-dependent ICPs should continue.

scholarly journals Evaluation of Mei-yu Heavy-Rainfall Quantitative Precipitation Forecasts in Taiwan by A Cloud-Resolving Model for Three Seasons of 2012–2014

2021 ◽  
Author(s):  
Chung-Chieh Wang ◽  
Pi-Yu Chuang ◽  
Chih-Sheng Chang ◽  
Kazuhisa Tsuboki ◽  
Shin-Yi Huang ◽  
...  
Keyword(s):  
False Alarm ◽  
Heavy Rainfall ◽  
Domain Size ◽  
Probability Of Detection ◽  
Crucial Importance ◽  
Grid Spacing ◽  
Fine Mesh ◽  
Quantitative Precipitation Forecasts ◽  
Cloud Resolving Model ◽  
Horizontal Grid

Abstract. In this study, the performance of quantitative precipitation forecasts (QPFs) by the Cloud-Resolving Storm Simulator (CReSS) in real-time in Taiwan, at a horizontal grid spacing of 2.5 km and a domain size of 1500 x 1200 km2, within a range of 72 h during three mei-yu seasons of 2012–2014 is evaluated using categorical statistics, with an emphasis on heavy events (≥ 100 mm per 24 h). The overall threat scores (TSs) of QPFs for all events on day 1 (0–24 h) are 0.18, 0.15, and 0.09 at the threshold of 100, 250, and 500 mm, respectively, and indicate considerable improvements compared to past results and 5-km models. Moreover, the TSs are shown to be higher and the model more skillful in predicting larger events, in agreement with earlier findings for typhoons. After classification based on observed rainfall, the TSs of day-1 QPFs for the largest 4 % of events by CReSS at 100, 250, and 500 mm (per 24 h) are 0.34, 0.24, and 0.16, respectively, and can reach 0.15 at 250 mm on day 2 (24–48 h) and 130 mm on day 3 (48–72 h). The larger events also exhibit higher probability of detection and lower false alarm ratio than weaker events almost without exception across all thresholds. The strength of the model lies mainly in the topographic rainfall in Taiwan rather than migratory events that are less predictable. Our results highlight the crucial importance of cloud-resolving capability and the size of fine mesh for heavy-rainfall QPFs in Taiwan.

Sensitivity of Convective Cell Dynamics and Microphysics to Model Resolution for the OWLeS IOP2b Lake-Effect Snowband

2020 ◽  
Vol 148 (8) ◽  
pp. 3305-3328 ◽  
Author(s):  
Anders A. Jensen ◽  
Philip T. Bergmaier ◽  
Bart Geerts ◽  
Hugh Morrison ◽  
Leah S. Campbell
Keyword(s):  
High Resolution ◽  
Wrf Model ◽  
Heavy Precipitation ◽  
Convective Cell ◽  
Maximum Diameter ◽  
Grid Spacing ◽  
Particle Properties ◽  
Lake Effect ◽  
Aircraft Observations ◽  
Horizontal Grid

Abstract The OWLeS IOP2b lake-effect case is simulated using the Weather Research and Forecasting (WRF) Model with a horizontal grid spacing of 148 m (WRF-LES mode). The dynamics and microphysics of the simulated high-resolution snowband and a coarser-resolution band from the parent nest (1.33-km horizontal grid spacing) are compared to radar and aircraft observations. The Ice Spheroids Habit Model with Aspect-ratio Evolution (ISHMAEL) microphysics is used, which predicts the evolution of ice particle properties including shape, maximum diameter, density, and fall speed. The microphysical changes within the band that occur when going from 1.33-km to 148-m grid spacing are explored. Improved representation of the dynamics at higher resolution leads to a better representation of the microphysics of the snowband compared to radar and aircraft observations. Stronger updrafts in the high-resolution grid produce higher ice number concentrations and produce ice particles that are more heavily rimed and thus more spherical, smaller (in terms of mean maximum diameter), and faster falling. These changes to the ice particle properties in the high-resolution grid limit the production of aggregates and improve reflectivity compared to observations. Graupel, observed in the band at the surface, is simulated in the strongest convective updrafts, but only at the higher resolution. Ultimately, the duration of heavy precipitation just onshore from the collapse of convection is better predicted in the high-resolution domain compared to surface and radar observations.

scholarly journals The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation

2021 ◽  
Author(s):  
Nikolina Ban ◽  
Cécile Caillaud ◽  
Erika Coppola ◽  
Emanuela Pichelli ◽  
Stefan Sobolowski ◽  
...  
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Model Ensemble ◽  
Grid Spacing ◽  
Model Simulations ◽  
Coarse Resolution ◽  
Climate Simulations ◽  
Scale Models ◽  
Horizontal Grid

AbstractHere we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of $$\sim $$ ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution ($$\sim $$ ∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from $$\sim \,$$ ∼  −40% at 12 km to $$\sim \,$$ ∼  −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.

Importance of Regional Climate Model Grid Spacing for the Simulation of Heavy Precipitation in the Colorado Headwaters

2013 ◽  
Vol 26 (13) ◽  
pp. 4848-4857 ◽  
Author(s):  
Andreas F. Prein ◽  
Gregory J. Holland ◽  
Roy M. Rasmussen ◽  
James Done ◽  
Kyoko Ikeda ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Colorado River ◽  
Climate Model ◽  
Regional Climate ◽  
Heavy Precipitation ◽  
Grid Spacing ◽  
Climate Simulations ◽  
Horizontal Grid ◽  
Precipitation Events

Abstract Summer and winter daily heavy precipitation events (events above the 97.5th percentile) are analyzed in regional climate simulations with 36-, 12-, and 4-km horizontal grid spacing over the headwaters of the Colorado River. Multiscale evaluations are useful to understand differences across horizontal scales and to evaluate the effects of upscaling finescale processes to coarser-scale features associated with precipitating systems. Only the 4-km model is able to correctly simulate precipitation totals of heavy summertime events. For winter events, results from the 4- and 12-km grid models are similar and outperform the 36-km simulation. The main advantages of the 4-km simulation are the improved spatial mesoscale patterns of heavy precipitation (below ~100 km). However, the 4-km simulation also slightly improves larger-scale patterns of heavy precipitation.

Next-Day Convection-Allowing WRF Model Guidance: A Second Look at 2-km versus 4-km Grid Spacing

2009 ◽  
Vol 137 (10) ◽  
pp. 3351-3372 ◽  
Author(s):  
Craig S. Schwartz ◽  
John S. Kain ◽  
Steven J. Weiss ◽  
Ming Xue ◽  
David R. Bright ◽  
...  
Keyword(s):  
Wrf Model ◽  
Heavy Rain ◽  
The United States ◽  
Skill Score ◽  
Horizontal Resolution ◽  
Substantial Improvement ◽  
Added Value ◽  
Grid Spacing ◽  
Similar Work ◽  
Horizontal Grid

Abstract During the 2007 NOAA Hazardous Weather Testbed (HWT) Spring Experiment, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma produced convection-allowing forecasts from a single deterministic 2-km model and a 10-member 4-km-resolution ensemble. In this study, the 2-km deterministic output was compared with forecasts from the 4-km ensemble control member. Other than the difference in horizontal resolution, the two sets of forecasts featured identical Advanced Research Weather Research and Forecasting model (ARW-WRF) configurations, including vertical resolution, forecast domain, initial and lateral boundary conditions, and physical parameterizations. Therefore, forecast disparities were attributed solely to differences in horizontal grid spacing. This study is a follow-up to similar work that was based on results from the 2005 Spring Experiment. Unlike the 2005 experiment, however, model configurations were more rigorously controlled in the present study, providing a more robust dataset and a cleaner isolation of the dependence on horizontal resolution. Additionally, in this study, the 2- and 4-km outputs were compared with 12-km forecasts from the North American Mesoscale (NAM) model. Model forecasts were analyzed using objective verification of mean hourly precipitation and visual comparison of individual events, primarily during the 21- to 33-h forecast period to examine the utility of the models as next-day guidance. On average, both the 2- and 4-km model forecasts showed substantial improvement over the 12-km NAM. However, although the 2-km forecasts produced more-detailed structures on the smallest resolvable scales, the patterns of convective initiation, evolution, and organization were remarkably similar to the 4-km output. Moreover, on average, metrics such as equitable threat score, frequency bias, and fractions skill score revealed no statistical improvement of the 2-km forecasts compared to the 4-km forecasts. These results, based on the 2007 dataset, corroborate previous findings, suggesting that decreasing horizontal grid spacing from 4 to 2 km provides little added value as next-day guidance for severe convective storm and heavy rain forecasters in the United States.

scholarly journals Using Fractal Downscaling of Satellite Precipitation Products for Hydrometeorological Applications

2010 ◽  
Vol 27 (3) ◽  
pp. 409-427 ◽  
Author(s):  
Kun Tao ◽  
Ana P. Barros
Keyword(s):  
Spatial Resolution ◽  
Stage Iv ◽  
Tropical Rainfall Measuring Mission ◽  
Skill Score ◽  
Probability Of Detection ◽  
Grid Spacing ◽  
Satellite Precipitation ◽  
Target Field ◽  
Skill Scores ◽  
Central United States

Abstract The objective of spatial downscaling strategies is to increase the information content of coarse datasets at smaller scales. In the case of quantitative precipitation estimation (QPE) for hydrological applications, the goal is to close the scale gap between the spatial resolution of coarse datasets (e.g., gridded satellite precipitation products at resolution L × L) and the high resolution (l × l; L ≫ l) necessary to capture the spatial features that determine spatial variability of water flows and water stores in the landscape. In essence, the downscaling process consists of weaving subgrid-scale heterogeneity over a desired range of wavelengths in the original field. The defining question is, which properties, statistical and otherwise, of the target field (the known observable at the desired spatial resolution) should be matched, with the caveat that downscaling methods be as a general as possible and therefore ideally without case-specific constraints and/or calibration requirements? Here, the attention is focused on two simple fractal downscaling methods using iterated functions systems (IFS) and fractal Brownian surfaces (FBS) that meet this requirement. The two methods were applied to disaggregate spatially 27 summertime convective storms in the central United States during 2007 at three consecutive times (1800, 2100, and 0000 UTC, thus 81 fields overall) from the Tropical Rainfall Measuring Mission (TRMM) version 6 (V6) 3B42 precipitation product (∼25-km grid spacing) to the same resolution as the NCEP stage IV products (∼4-km grid spacing). Results from bilinear interpolation are used as the control. A fundamental distinction between IFS and FBS is that the latter implies a distribution of downscaled fields and thus an ensemble solution, whereas the former provides a single solution. The downscaling effectiveness is assessed using fractal measures (the spectral exponent β, fractal dimension D, Hurst coefficient H, and roughness amplitude R) and traditional operational scores statistics scores [false alarm rate (FR), probability of detection (PD), threat score (TS), and Heidke skill score (HSS)], as well as bias and the root-mean-square error (RMSE). The results show that both IFS and FBS fractal interpolation perform well with regard to operational skill scores, and they meet the additional requirement of generating structurally consistent fields. Furthermore, confidence intervals can be directly generated from the FBS ensemble. The results were used to diagnose errors relevant for hydrometeorological applications, in particular a spatial displacement with characteristic length of at least 50 km (2500 km2) in the location of peak rainfall intensities for the cases studied.

Warm Cores, Eyewall Slopes, and Intensities of Tropical Cyclones Simulated by a 7-km-Mesh Global Nonhydrostatic Model

2016 ◽  
Vol 73 (11) ◽  
pp. 4289-4309 ◽  
Author(s):  
Tomoki Ohno ◽  
Masaki Satoh ◽  
Yohei Yamada
Keyword(s):  
Tropical Cyclones ◽  
Inner Core ◽  
Grid Spacing ◽  
Satellite Measurements ◽  
Warm Core ◽  
Nonhydrostatic Model ◽  
Proposed Model ◽  
Tangential Wind ◽  
Balanced Model ◽  
Horizontal Grid

Abstract Based on the data of a 1-yr simulation by a global nonhydrostatic model with 7-km horizontal grid spacing, the relationships among warm-core structures, eyewall slopes, and the intensities of tropical cyclones (TCs) were investigated. The results showed that stronger TCs generally have warm-core maxima at higher levels as their intensities increase. It was also found that the height of a warm-core maximum ascends (descends) as the TC intensifies (decays). To clarify how the height and amplitude of warm-core maxima are related to TC intensity, the vortex structures of TCs were investigated. By gradually introducing simplifications of the thermal wind balance, it was established that warm-core structures can be reconstructed using only the tangential wind field within the inner-core region and the ambient temperature profile. A relationship between TC intensity and eyewall slope was investigated by introducing a parameter that characterizes the shape of eyewalls and can be evaluated from satellite measurements. The authors found that the eyewall slope becomes steeper (shallower) as the TC intensity increases (decreases). Based on a balanced model, the authors proposed a relationship between TC intensity and eyewall slope. The result of the proposed model is consistent with that of the analysis using the simulation data. Furthermore, for sufficiently strong TCs, the authors found that the height of the warm-core maximum increases as the slope becomes steeper, which is consistent with previous observational studies. These results suggest that eyewall slopes can be used to diagnose the intensities and structures of TCs.

scholarly journals Detectable Anthropogenic Influence on Changes in Summer Precipitation in China

2020 ◽  
Vol 33 (13) ◽  
pp. 5357-5369
Author(s):  
Chunhui Lu ◽  
Fraser C. Lott ◽  
Ying Sun ◽  
Peter A. Stott ◽  
Nikolaos Christidis
Keyword(s):  
Human Life ◽  
Eastern China ◽  
Precipitation Amount ◽  
Summer Precipitation ◽  
Heavy Precipitation ◽  
Observation Data ◽  
Anthropogenic Influence ◽  
Anthropogenic Forcing ◽  
The Future ◽  
Light Precipitation

AbstractIn China, summer precipitation contributes a major part of the total precipitation amount in a year and has major impacts on society and human life. Whether any changes in summer precipitation are affected by external forcing on the climate system is an important issue. In this study, an optimal fingerprinting method was used to compare the observed changes of total, heavy, moderate, and light precipitation in summer derived from newly homogenized observation data with the simulations from multiple climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). The results demonstrate that the anthropogenic forcing signal can be detected and separated from the natural forcing signal in the observed increase of seasonal accumulated precipitation amount for heavy precipitation in summer in China and eastern China (EC). The simulated changes in heavy precipitation are generally consistent with observed change in China but are underestimated in EC. When the changes in precipitation of different intensities are considered simultaneously, the human influence on simultaneous changes in moderate and light precipitation can be detected in China and EC in summer. Changes attributable to anthropogenic forcing explain most of the observed regional changes for all categories of summer precipitation, and natural forcing contributes little. In the future, with increasing anthropogenic influence, the attribution-constrained projection suggests that heavy precipitation in summer will increase more than that from the model raw outputs. Society may therefore face a higher risk of heavy precipitation in the future.

Analysis of Idealized Tropical Cyclone Simulations Using the Weather Research and Forecasting Model: Sensitivity to Turbulence Parameterization and Grid Spacing

2009 ◽  
Vol 137 (2) ◽  
pp. 745-765 ◽  
Author(s):  
Kevin A. Hill ◽  
Gary M. Lackmann
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Maximum Intensity ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Exchange Coefficient ◽  
Model Sensitivity ◽  
Wind Speeds ◽  
Horizontal Grid ◽  
Weather Research

Abstract The Weather Research and Forecasting Advanced Research Model (WRF-ARW) was used to perform idealized tropical cyclone (TC) simulations, with domains of 36-, 12-, and 4-km horizontal grid spacing. Tests were conducted to determine the sensitivity of TC intensity to the available surface layer (SL) and planetary boundary layer (PBL) parameterizations, including the Yonsei University (YSU) and Mellor–Yamada–Janjic (MYJ) schemes, and to horizontal grid spacing. Simulations were run until a quasi-steady TC intensity was attained. Differences in minimum central pressure (Pmin) of up to 35 hPa and maximum 10-m wind (V10max) differences of up to 30 m s−1 were present between a convection-resolving nested domain with 4-km grid spacing and a parent domain with cumulus parameterization and 36-km grid spacing. Simulations using 4-km grid spacing are the most intense, with the maximum intensity falling close to empirical estimates of maximum TC intensity. Sensitivity to SL and PBL parameterization also exists, most notably in simulations with 4-km grid spacing, where the maximum intensity varied by up to ∼10 m s−1 (V10max) or ∼13 hPa (Pmin). Values of surface latent heat flux (LHFLX) are larger in MYJ than in YSU at the same wind speeds, and the differences increase with wind speed, approaching 1000 W m−2 at wind speeds in excess of 55 m s−1. This difference was traced to a larger exchange coefficient for moisture, CQ, in the MYJ scheme. The exchange coefficients for sensible heat (Cθ) and momentum (CD) varied by <7% between the SL schemes at the same wind speeds. The ratio Cθ/CD varied by <5% between the schemes, whereas CQ/CD was up to 100% larger in MYJ, and the latter is theorized to contribute to the differences in simulated maximum intensity. Differences in PBL scheme mixing also likely played a role in the model sensitivity. Observations of the exchange coefficients, published elsewhere and limited to wind speeds <30 m s−1, suggest that CQ is too large in the MYJ SL scheme, whereas YSU incorporates values more consistent with observations. The exchange coefficient for momentum increases linearly with wind speed in both schemes, whereas observations suggest that the value of CD becomes quasi-steady beyond some critical wind speed (∼30 m s−1).

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