scholarly journals Application to NWP Models Verification of an Atmospheric Circulation Patterns Classification

2021 ◽  
Author(s):  
Raffaele Salerno ◽  
Laura Bertolani
Keyword(s):  
Large Scale ◽  
Precipitation Forecast ◽  
Specific Humidity ◽  
Forecast Errors ◽  
Self Organizing Map ◽  
Model Ensemble ◽  
Climate Services ◽  
Global Models ◽  
Circulation Patterns ◽  
Synoptic Circulation

<p>At Meteo Expert, a Italian private organization providing weather and climate services and formerly known as Epson Meteo Centre, we are using the Self Organizing Map (SOM) algorithm to study synoptic circulation over Southern Europe, evaluating the capability of five NWP global models and one multi-model ensemble to predict its variability in order to relate synoptic circulation patterns to temperature and precipitation forecast’s quality over Italy. SOM is an iterative algorithm that ‘learns’ the patterns of the input data vectors and organizes them into nodes within the SOM space, arranging like patterns in neighboring nodes and the most unlike patterns in nodes farthest from each other. Daily observed and predicted weather types from the five NWP global models and the multi-model ensemble were recognized and classified by the SOM. The SOM-based classification built for our purposes produces a 12-weather-type set using daily 500 hPa and 700 hPa geopotential, sea level pressure, 850 hPa temperature and 700 hPa specific humidity. The five global models are GFS from National Centers for Environmental Prediction, IFS from European Centre for Medium-Range Weather (ECMWF), Arpege from Meteo France, GEM from Canadian Meteorological Centre, ICON from Deutscher Wetterdienst, together with MIX, our multi-model ensemble. Here we would like to present some examples of this operational activity in the one-year-period, also showing how much the source of forecast errors may depend on large-scale dynamics rather than model's physical parameterisations. A quality index has been used to quantify the overall ability of models in predicting the circulation patterns, showing that MIX and ECMWF reached the best performance within 96 hours of forecast.</p>

The impact of large-scale atmospheric patterns on Heatwaves in summer Northern China based on Self-Organizing Map

2020 ◽  
Author(s):  
Chen Shi ◽  
Wang Kaicun ◽  
Zhou Chunlüe
Keyword(s):  
Atmospheric Circulation ◽  
Large Scale ◽  
Stepwise Regression ◽  
Northern China ◽  
Subtropical High ◽  
Self Organizing Map ◽  
Okhotsk Sea ◽  
Circulation Patterns ◽  
The Impact ◽  
Self Organizing

<p>Heatwave is affected by large-scale atmospheric circulation on temperature-related climates in the context of global warming. Recently Northern China have experienced an increase in heatwaves which is partly due to the atmospheric circulation. This study aims to address the influence clearly. Northern China heatwaves are computed on excess hot factor (EHF) and the five EHF indexes are studied afterwards to get a picture of heatwaves in summer Northern China. China circulation patterns are classified into nine typical circulation patterns on self-organizing map (SOM) which then can be described quantitatively by pattern factors: frequency, persistence and maximum persistence. Pearson correlation analysis and stepwise regression analysis are applied for exploring the impact. Results show the spatial pattern of the times of individual heatwave event (HWN) and the days of the longest heatwave duration (HWD) are high value everywhere in Northern China. The overall EHF indexes all rising in time series (P<0.05) and the regional heatwave occurrence have trends of 0.79 day per year (P<0.05). However, the factors of the patterns show inconspicuous tendency. Two patterns with significant correlations (P<0.05) are proved to be suggestive of Okhotsk Sea high and West Pacific Subtropical High. It declares that the Okhotsk Sea high favors Northern China heatwave occurrence rather than subtropical high: the warm center over Okhotsk Sea transfer heat upper and west, generating the high temperature and persist high pressure system, causing heatwave happening in summer Northern China. The two related atmospheric circulation patterns explain 38% of the heatwave occurrence based on stepwise regression model, the Okhotsk Sea high gets the coefficient of 0.443 and the subtropical high is -0.347.  </p>

scholarly journals Three distinct atmospheric circulation patterns associated with high temperature extremes in South Korea

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Han-Kyoung Kim ◽  
Byung-Kwon Moon ◽  
Maeng-Ki Kim ◽  
Jong-Yeon Park ◽  
Yu-Kyung Hyun
Keyword(s):  
High Temperature ◽  
South Korea ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Negative Impact ◽  
Wave Train ◽  
Self Organizing Map ◽  
Atmospheric Circulation Patterns ◽  
Circulation Patterns ◽  
Extreme High Temperature

AbstractThe negative impact of extreme high-temperature days (EHDs) on people’s livelihood has increased over the past decades. Therefore, an improved understanding of the fundamental mechanisms of EHDs is imperative to mitigate this impact. Herein, we classify the large-scale atmospheric circulation patterns associated with EHDs that occurred in South Korea from 1982 to 2018 using a self-organizing map (SOM) and investigate the dynamic mechanism for each cluster pattern through composite analysis. A common feature of all SOM clusters is the positive geopotential height (GPH) anomaly over the Korean Peninsula, which provides favorable conditions for EHDs through adiabatic warming caused by anomalous downward motion. Results show that Cluster 1 (C1) is related to the eastward-propagating wave train in the mid-latitude Northern Hemisphere, while Cluster 2 (C2) and 3 (C3) are influenced by a northward-propagating wave train forced by enhanced convection in the subtropical western North Pacific (WNP). Compared to C2, C3 exhibits strong and eastward-extended enhanced convection over the subtropical WNP, which generates an anomalous high-pressure system over the southern part of the Kamchatka Peninsula, reinforcing EHDs via atmospheric blocking. Our results can contribute to the understanding of East Asia climate variability because wave trains influence the climate dynamics of this region.

scholarly journals Association between the Biophysical Environment in Coastal South China Sea and Large-Scale Synoptic Circulation Patterns: The Role of the Northwest Pacific Subtropical High and Typhoons

2021 ◽  
Vol 13 (16) ◽  
pp. 3250
Author(s):  
Shuhong Liu ◽  
Yuanjian Yang ◽  
Danling Tang ◽  
Hong Yan ◽  
Guicai Ning
Keyword(s):  
South China Sea ◽  
Large Scale ◽  
Northwest Pacific ◽  
Concentration Zone ◽  
Chl A ◽  
Southern Vietnam ◽  
Circulation Patterns ◽  
Biophysical Environment ◽  
Synoptic Circulation ◽  
Northwest Pacific Subtropical High

Synoptic weather conditions can modulate short-term variations in the marine biophysical environment. However, the impact of large-scale synoptic circulation patterns (LSCPs) on variations in chlorophyll-a (chl-a) and sea surface temperature (SST) in the South China Sea (SCS) remains unclear. Using a T-mode principal component analysis method, four types of LSCP related to the Northwest Pacific subtropical high are objectively identified over the SCS for the summers of 2015–2018. Type 1 exhibits a lower chl-a concentration of <0.3 mg m−3 offshore of southern Vietnam with respect to the other three types. For Type 2, the high chl-a concentration zone (>0.3 mg m−3) along the coast of Guangdong exhibits the widest areas of coverage. The offshore chl-a bloom jet (>0.3 mg m−3) formed in southern Vietnam is the most obvious under Type 3. Under Type 4, the high chl-a concentration zone along the coast of Guangdong is the narrowest, while the chl-a concentration in the middle of the SCS is the lowest (<0.1 mg m−3). These type differences are mostly caused by the various monsoon circulations, local ocean mesoscale processes and resultant differences in localized precipitation, wind vectors, photosynthetically active radiation and SST. In particular, precipitation over land helps to transport nutrients from the land to the shore, which is conducive to the increase of chl-a. However, precipitation over ocean will dilute the upper seawater and reduce chl-a. Typhoons pump the deeper seawater with nutrients to the surface, and therefore make a positive contribution to chl-a in most offshore areas; however, they also disturb shallower water and hinder the growth of phytoplankton, making a negative contribution near the coast of Guangdong. In general, our findings will provide a better understanding of wind pump impact: the responses of marine biophysical environments to LSCPs.

scholarly journals Effects of Synoptic-Scale Control on Long-Term Declining Trends of Summer Fog Frequency over the Pacific Side of Hokkaido Island

2013 ◽  
Vol 52 (10) ◽  
pp. 2226-2242 ◽  
Author(s):  
Shiori Sugimoto ◽  
Tomonori Sato ◽  
Kazuki Nakamura
Keyword(s):  
Large Scale ◽  
Interannual Variation ◽  
Inversion Layer ◽  
Large Scale Circulation ◽  
Sea Fog ◽  
The Pacific ◽  
Circulation Patterns ◽  
Synoptic Circulation ◽  
Hokkaido Island

AbstractIn this study, long-term visibility data for the Pacific Ocean side of Hokkaido Island, northeast Japan, are investigated to clarify the relationship between interannual variation in summer fog frequency (FF) and large-scale circulation patterns. At Kushiro, a significant FF decrease is found during 1931–2010 even without the influence of the observatory's relocation after 2000. In particular, since the late 1970s, a linear declining trend has accelerated, as evidenced by an increased number of years with very low FF in July and August. To clarify the climatological factor causing the summer FF declining trend at Kushiro, atmospheric vertical conditions in the planetary boundary layer and large-scale circulation are examined during 1989–2009 and 1958–2002, respectively, using available datasets. Composite analyses that are based on radiosonde observations reveal that the shallow fog layer is covered with a strong inversion layer during fog days whereas the inversion layer is absent during nonfog days. Composite circulation anomalies for the low-FF years at Kushiro show an intensified Okhotsk high (OH) pressure feature and southward shrinking of the North Pacific high (NPH) in July, in addition to the eastward displacement or shrinking of the NPH in August. These anomalous synoptic circulation patterns cause weakening in the southerly–southeasterly wind, which reduces sea-fog advection toward Kushiro and prevents the formation of stable stratification over the sea-fog layer. The authors suggest that the interannual variation in summer FF with the recent accelerated decline at Kushiro is primarily controlled by changes in the synoptic circulation associated with the OH and NPH development.

scholarly journals Scale-Dependent Uncertainties in Global QPFs and QPEs from NWP Model and Satellite Fields

2010 ◽  
Vol 11 (1) ◽  
pp. 139-155 ◽  
Author(s):  
C. Lu ◽  
H. Yuan ◽  
E. I. Tollerud ◽  
N. Wang
Keyword(s):  
Large Scale ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Global Model ◽  
Precipitation Forecast ◽  
Forecast Errors ◽  
Satellite Precipitation ◽  
Model Based ◽  
Nwp Model ◽  
Global Precipitation

Abstract Global precipitation forecasts from numerical weather prediction (NWP) models can be verified using the near-global coverage of satellite precipitation retrievals. However, inaccuracies in satellite precipitation analyses complicate the interpretation of forecast errors that result from verification of an NWP model against satellite observations. In this study, assessments of both a global quantitative precipitation estimate (QPE) from a satellite precipitation product and corresponding global quantitative precipitation forecast (QPF) from a global NWP model are conducted using available global land-based gauge data. A scale decomposition technique is devised, coupled with seasonal and spatial classifications, to evaluate these inaccuracies. The results are then analyzed in context with various physical precipitation systems, including heavy monsoonal rains, light Mediterranean winter rains, and North American convective-related and midlatitude cyclone–related precipitation. In general, global model results tend to consistently overforecast rainfall, whereas satellite measurements present a mixed pattern, underestimating many large-scale precipitation systems while overestimating many convective-scale precipitation systems. Both global model QPF and satellite-retrieved QPE showed better correlation scores in large-scale precipitation systems when verified with gauge measurements. In this case, model-based QPF tends to outperform satellite-retrieved QPE. At convective scales, there are significant drops in both model QPF and satellite QPE correlation scores, but satellite QPE performs slightly better than model QPF. These general results also showed regional and seasonal variation. For example, in tropical monsoon systems, satellite QPE tended to outperform model-based QPF at both scales. Overall, the results suggest potential improvements for both satellite estimates and weather forecast systems, in particular as applied to global precipitation forecasts.

scholarly journals Extreme Precipitation in the Great Lakes Region: Trend Estimation and Relation With Large-Scale Circulation and Humidity

2021 ◽  
Vol 3 ◽  
Author(s):  
Andrew Paxton ◽  
Justin T. Schoof ◽  
Trent W. Ford ◽  
Jonathan W. F. Remo
Keyword(s):  
Great Lakes ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Ordinary Least Squares ◽  
Specific Humidity ◽  
Great Lakes Region ◽  
Self Organizing Map ◽  
Precipitation Frequency ◽  
Urban Floods ◽  
The U.S

Extreme precipitation contributes to widespread impacts in the U.S. Great Lakes region, ranging from agricultural losses to urban floods and associated infrastructure costs. Previous studies have reported historical increases in the frequency of extreme precipitation in the region and downscaled model projections indicate further changes as the climate system continues to warm. Here, we conduct trend analysis on the 5 km NOAA NClimDiv data for the U.S. Great Lakes region using both parametric (Ordinary Least Squares) and non-parametric methods (Theil-Sen/Mann-Kendall) and accounting for temporal autocorrelation and field significance to produce robust estimates of extreme precipitation frequency trends in the region. The approaches provide similar overall results and reflect an increase in extreme precipitation frequency in parts of the U.S. Great Lakes region. To relate the identified trends to large scale drivers, a bivariate self-organizing map (SOM) is constructed using standardized values of 500 hPa geo-potential height and 850 hPa specific humidity obtained from the ECMWF ERA-5 reanalysis. Using a Monte Carlo approach, we identify six SOM nodes that account for only 25.4% of all days, but 50.5% of extreme precipitation days. Composites of days with and without extreme precipitation for each node indicate that extreme events are associated with stronger features (height gradient and background humidity) than their non-extreme counterparts. The analysis also identifies a significant increase in the frequency of one SOM node often associated with extreme precipitation (accounting for 8.5% of all extreme precipitation days) and a significant increase in the frequency of extreme precipitation days relative to all days across the six extreme precipitation nodes collectively. Our results suggest that changes in atmospheric circulation and related moisture transport and convergence are major contributors to changes in extreme precipitation in the U.S. Great Lakes region.

scholarly journals Characteristics of Large-Scale Circulation Affecting the Inter-Annual Precipitation Variability in Northern Sumatra Island during Boreal Summer

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 136
Author(s):  
Yahya Darmawan ◽  
Huang-Hsiung Hsu ◽  
Jia-Yuh Yu
Keyword(s):  
Large Scale ◽  
Precipitation Variability ◽  
Specific Humidity ◽  
Boreal Summer ◽  
Moisture Budget ◽  
Large Scale Circulation ◽  
Budget Analysis ◽  
Sumatra Island ◽  
Precipitation Anomalies ◽  
The Impact

This study aims to explore the contrasting characteristics of large-scale circulation that led to the precipitation anomalies over the northern parts of Sumatra Island. Further, the impact of varying the Asian–Australian Monsoon (AAM) was investigated for triggering the precipitation variability over the study area. The moisture budget analysis was applied to quantify the most dominant component that induces precipitation variability during the JJA (June, July, and August) period. Then, the composite analysis and statistical approach were applied to confirm the result of the moisture budget. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Anaysis Interim (ERA-Interim) from 1981 to 2016, we identified 9 (nine) dry and 6 (six) wet years based on precipitation anomalies, respectively. The dry years (wet years) anomalies over the study area were mostly supported by downward (upward) vertical velocity anomaly instead of other variables such as specific humidity, horizontal velocity, and evaporation. In the dry years (wet years), there is a strengthening (weakening) of the descent motion, which triggers a reduction (increase) of convection over the study area. The overall downward (upward) motion of westerly (easterly) winds appears to suppress (support) the convection and lead to negative (positive) precipitation anomaly in the whole region but with the largest anomaly over northern parts of Sumatra. The AAM variability proven has a significant role in the precipitation variability over the study area. A teleconnection between the AAM and other global circulations implies the precipitation variability over the northern part of Sumatra Island as a regional phenomenon. The large-scale tropical circulation is possibly related to the PWC modulation (Pacific Walker Circulation).

scholarly journals Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Adeoluwa Akande ◽  
Ana Cristina Costa ◽  
Jorge Mateu ◽  
Roberto Henriques
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Northern Region ◽  
Extreme Weather Events ◽  
Self Organizing Map ◽  
Spatial And Temporal Patterns ◽  
Self Organizing Maps ◽  
The North ◽  
Precipitation Regimes ◽  
Self Organizing

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

A stochastic approach for assessing the effect of changes in synoptic circulation patterns on gauge precipitation

1993 ◽  
Vol 29 (10) ◽  
pp. 3303-3315 ◽  
Author(s):  
James P. Hughes ◽  
Dennis P. Lettenmaier ◽  
Peter Guttorp
Keyword(s):  
Stochastic Approach ◽  
Circulation Patterns ◽  
Synoptic Circulation

scholarly journals Forecasting Tropical Cyclones in the Western North Pacific Basin Using the NCEP Operational HWRF: Real-Time Implementation in 2012

2015 ◽  
Vol 30 (5) ◽  
pp. 1355-1373 ◽  
Author(s):  
Vijay Tallapragada ◽  
Chanh Kieu ◽  
Samuel Trahan ◽  
Zhan Zhang ◽  
Qingfu Liu ◽  
...  
Keyword(s):  
Real Time ◽  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
Environmental Modeling ◽  
Pacific Basin ◽  
Forecast Errors ◽  
Storm Intensity ◽  
Intensity Forecast ◽  
North Pacific Basin

Abstract This study documents the recent efforts of the hurricane modeling team at the National Centers for Environmental Prediction’s (NCEP) Environmental Modeling Center (EMC) in implementing the operational Hurricane Weather Research and Forecasting Model (HWRF) for real-time tropical cyclone (TC) forecast guidance in the western North Pacific basin (WPAC) from May to December 2012 in support of the operational forecasters at the Joint Typhoon Warning Center (JTWC). Evaluation of model performance for the WPAC in 2012 reveals that the model has promising skill with the 3-, 4-, and 5-day track errors being 125, 220, and 290 nautical miles (n mi; 1 n mi = 1.852 km), respectively. Intensity forecasts also show good performance, with the most significant intensity error reduction achieved during the first 24 h. Stratification of the track and intensity forecast errors based on storm initial intensity reveals that HWRF tends to underestimate storm intensity for weak storms and overestimate storm intensity for strong storms. Further analysis of the horizontal distribution of track and intensity forecast errors over the WPAC suggests that HWRF possesses a systematic negative intensity bias, slower movement, and a rightward bias in the lower latitudes. At higher latitudes near the East China Sea, HWRF shows a positive intensity bias and faster storm movement. This appears to be related to underestimation of the dominant large-scale system associated with the western Pacific subtropical high, which renders weaker steering flows in this basin.

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