Uncertainties of ENSO-related Regional Hadley Circulation Anomalies within Eight Reanalysis Datasets

El Nino-Southern Oscillation(ENSO),the leading mode of global interannual variability,usually intensifies the Hadley Circulation(HC),and meanwhile constrains its meridional extension,leading to an equatorward movement of the jet system.Previous studies have investigated the response of HC to ENSO events using different reanalysis datasets and evaluated their capability in capturing the main features of ENSO-associated HC anomalies.However,these studies mainly focused on the global HC,represented by a zonal-mean mass stream function(MSF).Comparatively fewer studies have evaluated HC responses from a regional perspective,partly due to the prerequisite of the Stokes MSF,which prevents us from integrating a regional HC.In this study,we adopt a recently developed technique to construct the three-dimensional structure of HC and evaluate the capability of eight state-of-the-art reanalyses in reproducing the regional HC response to ENSO events.Results show that all eight reanalyses reproduce the spatial structure of HC responses well,with an intensified HC around the central-eastern Pacific but weakened circulations around the Indo-Pacific warm pool and tropical Atlantic.The spatial correlation coefficient of the three-dimensional HC anomalies among the different datasets is always larger than 0.93.However,these datasets may not capture the amplitudes of the HC responses well.This uncertainty is especially large for ENSO-associated equatorially asymmetric HC anomalies,with the maximum amplitude in Climate Forecast System Reanalysis(CFSR)being about 2.7 times the minimum value in the Twentieth Century Reanalysis(20CR).One should be careful when using reanalysis data to evaluate the intensity of ENSO-associated HC anomalies.

Decadal trends in precipitable water vapor over the Indus River Basin using ERA5 reanalysis data

Precipitable Water Vapor(PWV)constitutes a pivotal parameter within the domains of atmospheric science,and remote sensing due to its profound influence on Earth’s climate dynamics and weather patterns.It exerts a significant impact on atmospheric stability absorption and emission of radiation,thus engendering alterations in the Earth’s radiative equilibrium.As such,precise quantification of PWV holds the potential to enhance weather prognostication and fortify preparedness against severe meteorological phenomena.This study aimed to elucidate the spatial and temporal changes in seasonal and annual PWV across the Indus River Basin and its sub-basins using ERA5 reanalysis datasets.The present study used ERA5 PWV(entire atmospheric column),air temperature at 2 m(t2m)and 500 hPa(T_500hPa),evapotranspiration,and total cloud cover data from 1960 to 2021.Theil Sen slope estimator and Mann-Kendall test were used for trend analysis.Correlation and multiple regression methods were used to understand the association of PWV with other factors.The findings have unveiled the highest increase in mean PWV during the monsoon(0.40 mm/decade),followed by premonsoon(0.37 mm/decade),post-monsoon(0.27 mm/decade),and winter(0.19 mm/decade)throughout the study period.Additionally,the mean PWV exhibited the most pronounced positive trend in the sub-basin Lower Indus(LI),followed by Panjnad(P),Kabul(K),and Upper Indus(UI)across all seasons,except winter.Annual PWV has also risen in the Indus basin and its sub-basins over the last six decades.PWV exhibits a consistent upward trend up to an elevation of 3500 m within the basin which is most pronounced during the monsoon season,followed by the pre-monsoon.The escalating PWV within the basin is reasonably ascribed to increasing air temperatures,augmented evapotranspiration,and heightened cloud cover.These findings hold potential utility for pertinent authorities engaged in water resource management and planning.

Applicability evaluation of ERA5 wind and wave reanalysis data in the South China Sea

Wind and wave data are essential in climatological and engineering design applications.In this study,data from 15 buoys located throughout the South China Sea(SCS)were used to evaluate the ERA5 wind and wave data.Applicability assessment are beneficial for gaining insight into the reliability of the ERA5 data in the SCS.The bias range between the ERA5 and observed wind-speed data was-0.78-0.99 m/s.The result indicates that,while the ERA5 wind-speed data underestimation was dominate,the overestimation of such data existed as well.Additionally,the ERA5 data underestimated annual maximum wind-speed by up to 38%,with a correlation coefficient>0.87.The bias between the ERA5 and observed significant wave height(SWH)data varied from-0.24 to 0.28 m.And the ERA5 data showed positive SWH bias,which implied a general underestimation at all locations,except those in the Beibu Gulf and centralwestern SCS,where overestimation was observed.Under extreme conditions,annual maximum SWH in the ERA5 data was underestimated by up to 30%.The correlation coefficients between the ERA5 and observed SWH data at all locations were greater than 0.92,except in the central-western SCS(0.84).The bias between the ERA5 and observed mean wave period(MWP)data varied from-0.74 to 0.57 s.The ERA5 data showed negative MWP biases implying a general overestimation at all locations,except for B1(the Beibu Gulf)and B7(the northeastern SCS),where underestimation was observed.The correlation coefficient between the ERA5 and observed MWP data in the Beibu Gulf was the smallest(0.56),and those of other locations fluctuated within a narrow range from 0.82 to 0.90.The intercomparison indicates that during the analyzed time-span,the ERA5 data generally underestimated wind-speed and SWH,but overestimated MWP.Under non-extreme conditions,the ERA5 wind-speed and SWH data can be used with confidence in most regions of the SCS,except in the central-western SCS.

Exploitable wave energy assessment based on ERA-Interim reanalysis data—A case study in the East China Sea and the South China Sea

Wave energy resources assessment is a very important process before the exploitation and utilization of the wave energy. At present, the existing wave energy assessment is focused on theoretical wave energy conditions for interesting areas. While the evaluation for exploitable wave energy conditions is scarcely ever performed. Generally speaking, the wave energy are non-exploitable under a high sea state and a lower sea state which must be ignored when assessing wave energy. Aiming at this situation, a case study of the East China Sea and the South China Sea is performed. First, a division basis between the theoretical wave energy and the exploitable wave energy is studied. Next, based on recent 20 a ERA-Interim wave field data, some indexes including the spatial and temporal distribution of wave power density, a wave energy exploitable ratio, a wave energy level, a wave energy stability, a total wave energy density, the seasonal variation of the total wave energy and a high sea condition frequency are calculated. And then the theoretical wave energy and the exploitable wave energy are compared each other; the distributions of the exploitable wave energy are assessed and a regional division for exploitable wave energy resources is carried out; the influence of the high sea state is evaluated. The results show that considering collapsing force of the high sea state and the utilization efficiency for wave energy, it is determined that the energy by wave with a significant wave height being not less 1 m or not greater than 4 m is the exploitable wave energy. Compared with the theoretical wave energy, the average wave power density, energy level, total wave energy density and total wave energy of the exploitable wave energy decrease obviously and the stability enhances somewhat. Pronounced differences between the theoretical wave energy and the exploitable wave energy are present. In the East China Sea and the South China Sea, the areas of an abundant and stable exploitable wave energy are primarily located in the north-central part of the South China Sea, the Luzon Strait, east of Taiwan, China and north of Ryukyu Islands; annual average exploitable wave power density values in these areas are approximately 10-15 kW/m; the exploitable coefficient of variation （COV） and seasonal variation （SV） values in these areas are less than 1.2 and 1, respectively. Some coastal areas of the Beibu Gulf, the Changjiang Estuary, the Hangzhou Bay and the Zhujiang Estuary are the poor areas of the wave energy. The areas of the high wave energy exploitable ratio is primarily in nearshore waters. The influence of the high sea state for the wave energy in nearshore waters is less than that in offshore waters. In the areas of the abundant wave energy, the influence of the high sea state for the wave energy is prominent and the utilization of wave energy is relatively difficult. The developed evaluation method may give some references for an exploitable wave energy assessment and is valuable for practical applications.

Evaluation on monthly sea surface wind speed of four reanalysis data sets over the China seas after 1988

This study investigates the long-term changes of monthly sea surface wind speeds over the China seas from 1988 to 2015. The 10-meter wind speeds products from four major global reanalysis datasets with high resolution are used: Cross-Calibrated Multi-Platform data set(CCMP), NCEP climate forecast system reanalysis data set(CFSR),ERA-interim reanalysis data set(ERA-int) and Japanese 55-year reanalysis data set(JRA55). The monthly sea surface wind speeds of four major reanalysis data sets have been investigated through comparisons with the longterm and homogeneous observation wind speeds data recorded at ten stations. The results reveal that(1) the wind speeds bias of CCMP, CFSR, ERA-int and JRA55 are 0.91 m/s, 1.22 m/s, 0.62 m/s and 0.22 m/s, respectively.The wind speeds RMSE of CCMP, CFSR, ERA-int and JRA55 are 1.38 m/s, 1.59 m/s, 1.01 m/s and 0.96 m/s,respectively;(2) JRA55 and ERA-int provides a realistic representation of monthly wind speeds, while CCMP and CFSR tend to overestimate observed wind speeds. And all the four data sets tend to underestimate observed wind speeds in Bohai Sea and Yellow Sea;(3) Comparing the annual wind speeds trends between observation and the four data sets at ten stations for 1988-1997, 1988–2007 and 1988–2015, the result show that ERA-int is superior to represent homogeneity monthly wind speeds over the China seaes.

Accumulation over the Greenland Ice Sheet as Represented in Reanalysis Data

Annual precipitation,evaporation,and calculated accumulation from reanalysis model outputs have been investigated for the Greenland Ice Sheet （GrIS）,based on the common period of 1989-2001.The ERA-40 and ERA-interim reanalysis data showed better agreement with observations than do NCEP-1 and NCEP-2 reanalyses.Further,ERA-interim showed the closest spatial distribution of accumulation to the observation.Concerning temporal variations,ERA-interim showed the best correlation with precipitation observations at five synoptic stations,and the best correlation with in situ measurements of accumulation at nine ice core sites.The mean annual precipitation averaged over the whole GrIS from ERA-interim （363 mm yr 1） and mean annual accumulation （319 mm yr 1） are very close to the observations.The validation of accumulation calculated from reanalysis data against ice-core measurements suggests that further improvements to reanalysis models are needed.

Validation of ECMWF and NCEP–NCAR Reanalysis Data in Antarctica

The European Center for Medium-Range Weather Forecast （ECMWF） Re-Analysis （ERA-40） and the National Centers for Environmental Prediction-National Center for Atmospheric Research （NCEP-NCAR） ECMWF （ERA-40） and NCEP–NCAR reanalysis data were compared with Antarctic station observations, including surface-layer and upper-layer atmospheric observations, on intraseasonal and interannual timescales. At the interannual timescale, atmospheric pressure at different height levels in the ERA-40 data are in better agreement with observed pressure than that in the NCEP–NCAR reanalysis data. ERA-40 reanalysis also outperforms NCEP–NCAR reanalysis in atmospheric temperature, except in the surface layer where the biases are somewhat larger. The wind velocity fields in both datasets do not agree well with surface-and upper-layer atmospheric observations. At intraseasonal timescales, both datasets capture the observed intraseasonal variability in pressure and temperature during austral winter.

Study on the Applicability of ERA5 Reanalysis Data at Lake Taihu

Lakes are an important component of the earth climate system. They play an important role in the study of basin weather forecasting, air quality forecasting, and regional climate research. The accuracy of driving variables is the basic premise to ensure the rationality of lake mode simulation. Based on the in-situ observations at Bifenggang site of the Lake Taihu Eddy flux Network from 2012 to 2017, this paper investigated temporal variations in temperature, relative humidity, wind speed, radiation components at different time scales (hourly, seasonal and interannual). ERA5 reanalysis data were compared with in-situ observation to quantify the error and evaluate the performance of reanalysis data. The results show that: 1) On the hourly scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. 2) On the seasonal variation scale, the ERA5 reanalysis data described air temperature, and downward long-wave radiation more accurately. However, the descriptions of wind speed, relative humidity and downward short-wave have large deviations. 3) On the interannual scale, the ERA5 reanalysis data show a good performance for temperature, followed by downward longwave radiation, downward shortwave radiation and relative humidity.

Characteristics of Atmospheric Heat Sources over Asia in Summer:Comparison of Results Calculated Using Multiple Reanalysis Datasets

Using 1979-2000 daily NCEP/NCAR （National Centers for Environmental Prediction/National Center for Atmospheric Research） reanalysis data （version 1, hereafter referred to as NCEP1; version 2, hereafter referred to as NCEP2）, ECMWF （European Center for Medium-range Weather Forecasts） reanalysis data （ERA）, and the Global Asian Monsoon Experiment （GAME） reanalysis data in summer 1998, the vertically integrated heat source （Q1） in summer is calculated, and results obtained using different datasets are compared. The distributions of （Q1） calculated by using NCEP1 are in good agreement with rainfall observations over the Arabian Sea/Indian Peninsula, the Bay of Bengal （BOB）, and East China. The distributions of （Q1） revealed by using NCEP2 are unrealistic in the southern Indian Peninsula, the BOB, and the South China Sea. Using ERA, the heat sources over the tropical Asia are in accordance with the summer precipitation, however, the distributions of （Q1） in East China are unreasonable. In the tropical region, the distributions of the summer heat source given by NCEP1 and ERA seem to be more accurate than those revealed by NCEP2. The NCEP1 and NCEP2 data are better for calculating heat sources over the subtropical and eastern regions of China's Mainland.

A Comparison of Atmospheric Temperature over China between Radiosonde Observations and Multiple Reanalysis Datasets

The quality controlled（RAW） and homogenized（ADJ） radiosonde temperatures within 850-30 hPa collected at 118 stations in China are compared,on a monthly mean basis,with the temperatures extracted from 8 reanalysis datasets（REA） including NCEP-1,NCEP-2,ERA-40（ECMWF 45-yr Reanalysis）,ERAInterim,JRA-55（Japanese 55-yr Reanalysis）,20CR（20th Century Reanalysis）,MERRA（Modern Era Retrospective-Analysis）,and CFSR（Climate Forecast System Reanalysis）.Average differences,correlations,standard deviations,and linear trends among RAW,ADJ,and REA for the period 1981-2010 are analyzed.The results reveal significant inhomogeneity in the time series of RAW radiosonde temperature in China;an overall negative adjustment was thus employed to obtain the ADJ temperatures,and the effect of the negative adjustment is the most significant within 200-100 hPa.Such a homogenization process has removed the system errors in RAW,possibly caused by radiosonde instrument changes and observation system upgrades.Hence,the correlation is higher between ADJ and REA than that between RAW and REA.The mean difference between ADJ and REA is about 1℃ during 1981-2010,while REA are mostly cooler in the troposphere and warmer in the stratosphere than ADJ;nonetheless,they have a significant high and positive correlation and their annual variability is notably consistent.Furthermore,the linear trends in REA and ADJ both demonstrate warming in the lower-mid troposphere and cooling in the mid stratosphere,with large uncertainties found in the upper troposphere and lower stratosphere.In general,ERA-Interim,JRA-55,and MERRA are more consistent with ADJ than other reanalysis datasets.

An evaluation of new satellite-derived latent and sensible heat fluxes with moored buoy data, OAFlux and NCEP2 reanalysis products

New satellite-derived latent and sensible heat fluxes are performed by using Wind Sat wind speed, Wind Sat sea surface temperature, the European Centre for Medium-range Weather Forecasting（ECMWF） air humidity, and ECMWF air temperature from 2004 to 2014. The 55 moored buoys are used to validate them by using the 30 min and 25 km collocation window. Furthermore, the objectively analyzed air-sea heat fluxes（OAFlux） products and the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis 2（NCEP2） products are also used for global comparisons. The mean biases of sensible and latent heat fluxes between Wind Sat flux results and buoy flux data are –0.39 and –8.09 W/m^2, respectively. In addition, the rootmean-square（RMS） errors of the sensible and latent heat fluxes between them are 5.53 and 24.69 W/m^2,respectively. The RMS errors of sensible and latent heat fluxes are observed to gradually increase with an increasing buoy wind speed. The difference shows different characteristics with an increasing sea surface temperature, air humidity, and air temperature. The zonal average latent fluxes have some high regions which are mainly located in the trade wind zones where strong winds carry dry air in January, and the maximum value centers are found in the eastern waters of Japan and on the US east coast. Overall, the seasonal variability is pronounced in the Indian Ocean, the Pacific Ocean, and the Atlantic Ocean. The three sensible and latent heat fluxes have similar latitudinal dependencies; however, some differences are found in some local regions.

Reanalysis on Hail Suppression Weather Prewarning of the "8.21" Rare Hail in Shenyang

[Objective]The research aimed to analyze hail weather during 18：30-19：30 on August 21,2011.[Method]Based on NCEP 6 h reanalysis data,Micaps data and FY-2 satellite cloud image,weather situation field,meteorological element field and satellite cloud image of the hail during 18：30-19：30 on August 21,2011 were reanalyzed.Weather causes of the hail and characteristics of the satellite cloud image were discussed.We summed up how to conduct prewarning analysis of the hail suppression weather from live weather data and numerical forecast products.[Result]In occurrence and development process of the hail weather,cold vortex at 500 hPa was background weather system.850 hPa warm tongue and ground wind shear were essential conditions for forming strong convective hail cloud.Early weather chart was analyzed.It could analyze occurrence reason of the weather from mechanism aspect of the weather system,and issue weather prewarning as early as possible.Numerical forecast products were used to analyze meteorological element field.It could further analyze and accurately predict probability,time and range of the hail occurrence.Infrared satellite cloud image was more accurate for monitoring strong convective hail cloud,which could intuitively predict occurrence of the hail weather.[Conclusion]The research offered some hail suppression prewarning experiences for the future similar hail weather.

An ERA5 tropospheric parameters-augmented approach for improving GNSS precise point positioning

Precise Point Positioning(PPP) technology has developed into a potent instrument for geodetic positioning, ionospheric modeling, tropospheric atmospheric parameter detection, and seismic monitoring.As atmospheric reanalysis data products’ accuracy and spatiotemporal resolution have improved recently, it has become important to apply these products to obtain high-accuracy tropospheric delay parameters, like zenith tropospheric delay(ZTD) and tropospheric horizontal gradient. These tropospheric delay parameters can be applied to PPP to reduce the convergence time and to increase the accuracy in the vertical direction of the position. The European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5) atmospheric reanalysis data is the latest product with a high spatiotemporal resolution released by the European Center for Medium-Range Weather Forecasts(ECMWF). Only a few researches have evaluated the application of ERA5 data to Global Navigation Satellite System(GNSS)PPP. Therefore, this study compared and validated the ZTD products derived from ERA5 data using ZTD values provided by 290 global International GNSS Service(IGS) stations for 2016-2017. The results indicated a stable performance for ZTD, with annual average bias and RMS values of 0.23 cm and 1.09 cm,respectively. Further, GNSS observations for one week in each of the four seasons(spring: DOY 92-98;summer: DOY 199-205;autumn: DOY 275-281;and winter: DOY 22-28) from 34 multi-GNSS experiments(MGEX) stations distributed globally in 2016 were considered to evaluate the performance of ERA5-derived tropospheric delay products in GNSS PPP. The performance of ERA5-enhanced PPP was compared with that of the two standard GNSS PPP schemes(without estimated tropospheric horizontal gradient and with estimated tropospheric horizontal gradient). The results demonstrated that ERA5-enhanced GNSS PPP showed no significant improvement in the convergence times in both the Eastern(E) and Northern(N) directions, while the average convergence time over four weeks in the vertical(U)direction improved by 53.3% and 52.7%, respectively(in the case of pngm station). The average convergence times for each week in the U direction of the northern and southern hemisphere stations indicated a decrease of 16.3%, 12.6%, 9.6%, and 9.1%, and 16.9%, 9.6%, 8.9%, and 14.5%, respectively.Regarding positioning accuracy, ERA5-enhanced PPP showed an improvement of 13.3% and 16.2% over the two standard PPP schemes in the U direction, respectively. No significant improvement in the positioning performance was observed in both the E and N directions. Thus, this study demonstrated the potential application of the ERA5 tropospheric parameters-augmented approach to Beidou navigation and positioning.

A Review on Clustering Methods for Climatology Analysis and Its Application over South America

South America’s climatic diversity is a product of its vast geographical expanse, encompassing tropical to subtropical latitudes. The variations in precipitation and temperature across the region stem from the influence of distinct atmospheric systems. While some studies have characterized the prevailing systems over South America, they often lacked the utilization of statistical techniques for homogenization. On the other hand, other research has employed multivariate statistical methods to identify homogeneous regions regarding temperature and precipitation, but their focus has been limited to specific areas, such as the south, southeast, and northeast. Surprisingly, there is a lack of work that compares various multivariate statistical techniques to determine homogeneous regions across the entirety of South America concerning temperature and precipitation. This paper aims to address this gap by comparing three such techniques: Cluster Analysis (K-means and Ward) and Self Organizing Maps, using data from different sources for temperature (ERA5, ERA5-Land, and CRU) and precipitation (ERA5, ERA5-Land, and CPC). Spatial patterns and time series were generated for each region over the period 1981-2010. The results from this analysis of spatially homogeneous regions concerning temperature and precipitation have the potential to significantly benefit climate analysis and forecasts. Moreover, they can offer valuable insights for various climatological studies, guiding decision-making processes in diverse fields that rely on climate information, such as agriculture, disaster management, and water resources planning.

On analyzing space-time distribution of evaporation duct height over the global ocean

The statistical features of the evaporation duct over the global ocean were comprehensively investigated with reanalysis data sets from the National Centers for Environmental Prediction. These data sets have time and spatial resolutions of 1 h and 0.313°x0.312°, respectively. The efficiency of the analysis was evaluated by processing weather buoy data from the Pacific Ocean and measuring propagation loss in the Yellow Sea of China. The distribution features of evaporation duct height （EDH） and the related meteorological factors for different seas were analyzed. The global EDH is generally high and demonstrates a latitudinal distribution for oceans at low latitudes. The average EDH is approximately 11 m over oceans beside the equator with a latitude of less than 20°. The reasons for the formation of the global EDH features were also analyzed for different sea areas.

Improvement of wind field hindcasts for tropical cyclones

This paper presents a study on the improvement of wind field hindcasts for two typical tropical cyclones, i.e., Fanapi and Meranti, which occurred in 2010. The performance of the three existing models for the hindcasting of cyclone wind fields is first examined, and then two modification methods are proposed to improve the hindcasted results. The first one is the superposition method, which superposes the wind field calculated from the parametric cyclone model on that obtained from the cross-calibrated multi-platform （CCMP） reanalysis data. The radius used for the superposition is based on an analysis of the minimum difference between the two wind fields. The other one is the direct modification method, which directly modifies the CCMP reanalysis data according to the ratio of the measured maximum wind speed to the reanalyzed value as well as the distance from the cyclone center. Using these two methods, the problem of underestimation of strong winds in reanalysis data can be overcome. Both methods show considerable improvements in the hindcasting of tropical cyclone wind fields, compared with the cyclone wind model and the reanalysis data.

A Study of Structure and Mechanism of a Meso-beta-scale Convective Vortex and Associated Heavy Rainfall in the Dabie Mountain Area Part I: Diagnostic Analysis of the Structure

An analysis was conducted on the evolutional process of a mesoscale convective vortex （MCV） and associated heavy rainfall in the Dabie Mountain area on 21-22 June 2008,as well as their structural characteristics in different stages,by using the mesoscale reanalysis data with 3 km and 1 h resolution generated by the Local Analysis and Prediction System （LAPS） in the Southern China Heavy Rainfall Experiment.The results showed that the latent heat released by convection in the midtroposphere was the main energy source for the development of a low-level vortex.There was a positive feedback interaction between the convection and the vortex,and the evolution of the MCV was closely related to the strength of the positive interaction.The most typical characteristics of the thermal structure in different stages were that,there was a relatively thin diabatic heating layer in the midtroposphere in the formative stage;the thickness of diabatic heating layer significantly increased in the mature stage;and it almost disappeared in the decay stage.The characteristics of the dynamic structure were that,in the formative stage,there was no anticyclonic circulation at the high level;in the mature stage,an anticyclonic circulation with strong divergence was formed at the high level;in the decay stage,the anticyclonic circulation was damaged and the high-level atmosphere was in a disordered state of turbulence.Finally,the structural schematics of the MCV in the formative and mature stage were established respectively.

Mapping Near-surface Air Temperature, Pressure, Relative Humidity and Wind Speed over China's Mainland with High Spatiotemporal Resolution

As part of a joint effort to construct an atmospheric forcing dataset for China's Mainland with high spatiotemporal reso- lution, a new approach is proposed to construct gridded near-surface temperature, relative humidity, wind speed and surface pressure with a resolution of 1 km× 1 km. The approach comprises two steps： （1） fit a partial thin-plate smoothing spline with orography and reanalysis data as explanatory variables to ground-based observations for estimating a trend surface; （2） apply a simple kriging procedure to the residual for trend surface correction. The proposed approach is applied to observations collected at approximately 700 stations over China's Mainland. The generated forcing fields are compared with the corresponding components of the National Centers for Environmental Predic- tion （NCEP） Climate Forecast System Reanalysis dataset and the Princeton meteorological forcing dataset. The comparison shows that, both within the station network and within the resolutions of the two gridded datasets, the interpolation errors of the proposed approach are markedly smaller than the two gridded datasets.

Statistical Guidance on Seasonal Forecast of Korean Dust Days over South Korea in the Springtime

This study aimed to develop the seasonal forecast models of Korean dust days over South Korea in the springtime. Forecast mode was a ternary forecast （below normal, normal, above normal） which was classified based on the mean and the standard deviation of Korean dust days for a period of 30 years （1981-2010）. In this study, we used three kinds of monthly data： the Korean dust days observed in South Korea, the National Center for Environmental Prediction in National Center for Atmospheric Research （NCEP/NCAR） reanalysis data for meteorological factors over source regions of Asian dust, and the large-scale climate indices offered from the Climate Diagnostic Center and Climate Prediction Center in NOAA. Forecast guidance consisted of two components; ordinal logistic regression model to generate trinomial distributions, and conversion algorithm to generate ternary forecast by two thresholds. Forecast guidance was proposed for each month separately and its predictability was evaluated based on skill scores.