ERA-Interim Reanalysis Data Research Articles

Spatio-temporal change and variability of Barents-Kara sea ice, in the Arctic: Ocean and atmospheric implications

The reduction in Arctic sea-ice in recent decades has been a significant indicator of climate change and is related to weather pattern changes across the Arctic regions. In this study, for the period 1979–2018, we addressed the processes controlling the sea-ice cover in the Barents-Kara Sea (BKS). The inter-annual variability of the sea-ice extent (SIE) in BKS was analyzed using passive microwave satellite observations. The ocean-atmospheric forcing variables which including air temperature (AT), sea surface temperature (SST) and outgoing long-wave radiation (OLR) were derived from ERA-Interim reanalysis data. The spatial correlation analysis was performed for the year 2016 and 1998, where sea ice concentration (SIC) in BKS is recorded as a minimum and maximum respectively. The long-term analysis (1979–2018) shows negative trends of the Arctic SIE (−4.7 ± 0.3% decade−1) with the largest decrease in the Barents Sea (−23 ± 2.5% decade−1) and Kara Sea (−7.3 ± 0.9% decade−1). However, the sea-ice decline in the Barents Sea was recorded very high during the winter (−17.6 ± 2.2% decade−1) compared to the Kara Sea (−0.8 ± 0.2% decade−1). Sea-ice cover in the Barents Sea is more likely to recede during the summers −4.1 ± 0.7 x 103 km2yr−1 due to warm inflow of Atlantic waters. Correlation analysis using statistically significant trend values with p-values ≤ 0.01 was performed from 1982 to 2018, the SIC of BKS showing significant negative correlation analyses with SST (−0.75; p-value = 0.01), SAT (−0.84; p-value = 0.00) and OLR (−0.76; p-value = 0.00). In recent years, Atlantic Multi-decadal Oscillation (AMO) index has become positive due to an increase in SST anomalies, while, AMO does not reflect the cooling events in the BKS. During recent Arctic climate change, caused by atmospheric heat transport, the loss of sea-ice at BKS is becoming a major factor. In this study, new perspectives of the complex processes associated with Arctic warming and the declining sea-ice in the BKS region are demonstrated.

An Assessment of Tourism Climate Comfort in the China–Pakistan Economic Corridor

Pleasant climates can be divided into two types: the comfortable summer climate and the comfortable winter climate, but existing studies rarely pay attention to the distribution characteristics and differences between the two types of climate. This study investigates the spatial distribution of comfortable summer and winter climates in the China–Pakistan Economic Corridor (CPEC) and their differences based on the European Centre for Medium-Range Weather Forecasts Re-Analysis-Interim (ERA-interim) reanalysis data from 1979 to 2018. The Universal Thermal Climate Index was used to analyze climatic suitability. The findings are as follows. First, the comfortable summer climate regions of the CPEC were mainly distributed in Khyber Pakhtunkhwa in Pakistan and some regions of Xinjiang in China and also sporadically distributed in high altitude mountains, such as the western plateau area. The comfortable winter climate regions were mainly distributed in vast areas except for Karakoram and nearby areas. Second, there are a few regions with dual attributes of comfortable summer and winter climates in CPEC. Third, according to the calculation and comparison of the regional area of different climate comfort levels in summer and winter, it is found that the comfortable summer climate is scarcer in CPEC and is a monopoly resource. The comfortable winter climate is widely distributed, belonging to the ubiquitous resources. These findings can be helpful for the tourism development of local climate resources.

Factors Affecting the Weakening Rate of Tropical Cyclones over the Western North Pacific

Abstract In this study, based on the 6-hourly tropical cyclone (TC) best track data and the ERA-Interim reanalysis data, statistical analyses as well as a machine learning approach, XGBoost, are used to identify and quantify factors that affect the overwater weakening rate (WR) of TCs over the western North Pacific (WNP) during 1980–2017. Statistical analyses show that the TC rapid weakening events usually occur when intense TCs cross regions with a sharp decrease in sea surface temperature (DSST) with relatively faster eastward or northward translational speeds, and move into regions with large environmental vertical wind shear (VWS) and dry conditions in the upshear-left quadrant. Results from XGBoost indicate that the relative intensity of TC (TC intensity normalized by its maximum potential intensity), DSST, and VWS are dominant factors determining TC WR, contributing 26.0%, 18.3%, and 14.9% to TC WR, and 9, 5, and 5 m s−1 day−1 to the variability of TC WR, respectively. Relative humidity in the upshear-left quadrant of VWS, zonal translational speed, divergence at 200 hPa, and meridional translational speed contribute 12.1%, 11.8%, 8.8%, and 8.1% to TC WR, respectively, but only contribute 2–3 m s−1 day−1 to the variability of TC WR individually. These findings suggest that the improved accurate analysis and prediction of the dominant factors may lead to substantial improvements in the prediction of TC WR.

Spatial-Temporal Pattern Changes of UTCI in the China-Pakistan Economic Corridor in Recent 40 Years

This paper investigated the spatial and temporal variations of the Universal Thermal Climate Index (UTCI) of the China-Pakistan Economic Corridor (CPEC) from 1979 to 2018. The European Centre for Medium-Range Weather Forecasts Re-Analysis-Interim (ERA-Interim) reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) is selected for UTCI calculation in the region and analyzed by a linear trend and correlation analysis. The results showed that (1) the UTCI of CPEC is decreased with the increase of latitude and altitude. There is obvious spatial heterogeneity in the seasonal scale and the spatial distribution of different thermal stress categories. (2) UTCI generally exhibited a positive trend of 0.33 °C/10a over the past 40 years, and the seasonal variation characteristics of UTCI show an upward trend in all four seasons, of which spring is the fastest. On the space scale, the growth trend has significant spatial variations. (3) Temperature has a positive correlation with UTCI. The influence of temperature on UTCI is greater than that of wind speed. The results of this study will be helpful for regional planning and also contribute to comprehending the characteristics of the thermal environment in CPEC.

Quasi-Biweekly Oscillation of the Bay of Bengal–East Asia–Pacific Teleconnection in Boreal Summer

AbstractThe study reported in this paper used ERA-Interim reanalysis data to investigate the intraseasonal variability of the Bay of Bengal (BOB)–East Asia–Pacific teleconnection (BEAP) during the summer between 1979 and 2016. Over this period, the intraseasonal oscillation of the BEAP fell mainly within the quasi-biweekly oscillation (QBWO) band. Variations in atmospheric circulation and precipitation, which may contribute to extreme weather events, showed a significant correlation with the phase transition of the BEAP from the BOB to East Asia and the Pacific. The evolution of the BEAP–QBWO is closely associated with the westward propagation of convective anomalies to the southwestern BOB. Dynamical analysis revealed that anomalous vertical motion coupled with anomalous convective activity over the southern BOB plays an important role in leading the phase propagation of the BEAP–QBWO, and that the horizontal advection anomalies can strengthen the BEAP–QBWO. Linear baroclinic model experiments confirmed that variations in convection over the southern BOB play a leading role in the BEAP–QBWO phase changes. Further research suggests that the boreal summer intraseasonal oscillation can trigger the BEAP–QBWO through downstream propagation of convective disturbances to the southern BOB. This study provides insights into the cause and effect of the BEAP–QBWO, which will help to improve understanding of flood and drought patterns in the Asia–Pacific region.

Evaluating Multiple WRF Configurations and Forcing over the Northern Patagonian Icecap (NPI) and Baker River Basin

The use of numerical weather prediction (NWP) model to dynamically downscale coarse climate reanalysis data allows for the capture of processes that are influenced by land cover and topographic features. Climate reanalysis downscaling is useful for hydrology modeling, where catchment processes happen on a spatial scale that is not represented in reanalysis models. Selecting proper parameterization in the NWP for downscaling is crucial to downscale the climate variables of interest. In this work, we are interested in identifying at least one combination of physics in the Weather Research Forecast (WRF) model that performs well in our area of study that covers the Baker River Basin and the Northern Patagonian Icecap (NPI) in the south of Chile. We used ERA-Interim reanalysis data to run WRF in twenty-four different combinations of physics for three years in a nested domain of 22.5 and 4.5 km with 34 vertical levels. From more to less confident, we found that, for the planetary boundary layer (PBL), the best option is to use YSU; for the land surface model (LSM), the best option is the five-Layer Thermal, RRTM for longwave, Dudhia for short wave radiation, and Thompson for the microphysics. In general, the model did well for temperature (average, minimum, maximum) for most of the observation points and configurations. Precipitation was good, but just a few configurations stood out (i.e., conf-9 and conf-10). Surface pressure and Relative Humidity results were not good or bad, and it depends on the statistics with which we evaluate the time series (i.e., KGE or NSE). The results for wind speed were inferior; there was a warm bias in all of the stations. Once we identify the best configuration in our experiment, we run WRF for one year using ERA5 and FNL0832 climate reanalysis. Our results indicate that Era-interim provided better results for precipitation. In the case of temperature, FNL0832 gave better results; however, all of the models’ performances were good. Therefore, working with ERA-Interim seems the best option in this region with the physics selected. We did not experiment with changes in resolution, which may have improved results with ERA5 that has a better spatial and temporal resolution.

A Combined Stokes Drift Profile under Swell and Wind Sea

AbstractA combined directional Stokes drift profile for swell and wind sea is presented. The profile can be used to calculate the shear under crossing seas and as such is relevant for Langmuir turbulence and Stokes–Coriolis forcing, but also for material advection. The swell is represented as either a monochromatic wave or as a Phillips spectrum, while the wind sea is represented as a Phillips spectrum. The profile is found to compare well against the full directional Stokes drift calculated from the 2D spectrum of ERA-Interim in an open-ocean location in the North Atlantic. The error compared to a Phillips-type unidirectional Stokes drift profile is markedly lower for a combined profile with a monochromatic swell Stokes profile. However, representing the swell as a Phillips-type Stokes drift profile yields even better results. The combined profile relies on integrated wave parameters readily available from wave models and can be calculated at low cost. The global Stokes drift climate is investigated using ERA-Interim reanalysis data with the intention of identifying regions dominated by crossing Stokes drift. We find that the eastern equatorial Pacific Ocean probably experiences the greatest degree of crossing Stokes drift, and the entire subtropical band 20°–30°S/N exhibits a significant degree of crossing Stokes drift and swell dominance over the Stokes drift.

Analyzing the Arctic Feedback Mechanism between Sea Ice and Low-Level Clouds Using 34 Years of Satellite Observations

AbstractSatellite-based cloud, radiation flux, and sea ice records covering 34 years are used 1) to investigate autumn cloud cover trends over the Arctic, 2) to assess its relation with declining sea ice using Granger causality (GC) analysis, and 3) to discuss the contribution of the cloud–sea ice (CSI) feedback to Arctic amplification. This paper provides strong evidence for a positive CSI feedback with the capability to contribute to autumnal Arctic amplification. Positive low-level cloud fractional cover (CFClow) trends over the Arctic ice pack are found in October and November (ON) with magnitudes of up to about +9.6% per decade locally. Statistically significant anticorrelations between sea ice concentration (SIC) and CFCloware observed in ON over melting zones, suggesting an association. The GC analysis indicated a causal two-way interaction between SIC and CFClow. Interpreting the resultingFstatistic and its spatial distribution as a relation strength proxy, the influence of SIC on CFClowis likely stronger than the reverse. ERA-Interim reanalysis data suggest that ON CFClowis impacted by sea ice melt through surface–atmosphere coupling via turbulent heat and moisture fluxes. Due to weak solar insolation in ON, net cloud radiative forcing (CRF) exerts a warming effect on the Arctic surface. Increasing CFClowinduces a large-scale surface warming trend reaching magnitudes of up to about +8.3 W m−2per decade locally. Sensitivities of total CRF to CFClowranges between +0.22 and +0.66 W m−2per percent CFClow. Increasing surface warming can cause a melt season lengthening and hinders formation of perennial ice.

A modeling study of the impact of stratospheric intrusion on ozone enhancement in the lower troposphere over the Hong Kong regions, China

Stratospheric intrusion is of great importance to transporting ozone (O3)-enriched air from stratosphere into the middle and lower troposphere. The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) was employed to simulate a typical stratospheric intrusion episode occurring on March 24, 2010 and examine the impact of stratospheric intrusion on the O3 enhancement in the lower troposphere. An upper boundary condition scheme was applied to the simulations to overcome the limitation of WRF-Chem in which O3 chemistry in the stratosphere is not included. The simulations were evaluated with various observational data including O3 sounding, surface O3, as well as the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis data. The WRF-Chem showed reasonable performance on simulating the meteorological processes that control the stratospheric intrusion. Several findings were identified from the detailed analyses of the modeling results. First, the subtropical high-level jet was responsible for this stratospheric intrusion event. When Hong Kong was located at the south side of the subtropical jet where subsidence was dominated, the O3-enriched air was transported from stratosphere to troposphere. Second, the stratospheric intrusion caused substantial enhancement of O3 with the maximum O3 concentration higher than 80.0 ppbv in the lower above the atmospheric boundary layer in the Hong Kong region. Finally, the process analyses (PA) method is performed to quantify the impact of stratosphere intrusion on the O3 enhancement in the lower troposphere. The PA result illustrates that a substantial increase in the lower troposphere O3 is highly associated with vertical transport from the upper troposphere. These results indicated important role of stratospheric intrusion on O3 enhancement events and more observations are advised to better constrain and quantify its effects.

Sensitivity of WRF-simulated 10 m wind over the Persian Gulf to different boundary conditions and PBL parameterization schemes

A sensitivity analysis of the Weather Research and Forecasting (WRF) mesoscale model with the Advanced Research WRF (ARW) dynamical solver for wind simulation at 10 m above ground level was conducted through different initial and boundary conditions datasets, and various planetary boundary layer (PBL) schemes throughout the year 2017 over the Persian Gulf region. Owing to the wide variety of approaches and development periods of analysis and reanalysis data (e.g. assimilation system) as well as different methods for PBL parameterization (closure formulations), this paper aims to obtain an efficient set up of the WRF model configuration in terms of the lowest error in simulating surface wind. Three datasets including ERA-Interim reanalysis, NCEP-R2 reanalysis, and NCEP-FNL analysis as initial and boundary conditions to the model and six PBL schemes including ACM2, BouLac, MYJ, MYNN, QNSE, and YSU accompanied by their relevant surface-layer schemes were used to accomplish this goal. Available observational wind data including 23 synoptic weather stations located in the region were used to compare the model wind simulation. Comparing WRF wind simulations with observations at synoptic weather stations indicates that; irrespective of the type of PBL scheme, ERA-Interim, and NCEP-FNL datasets exhibit better performance than the NCEP-R2. In addition, in the case of considering PBL schemes, results show that the configuration including the YSU scheme and ERA-Interim reanalysis data leads to the best estimation of wind speed and configuration including YSU and NCEP-FNL data produces the least error for wind direction. The performance of the model in summer shows higher errors compared to the winter season. It is due to the obvious differences between initial and boundary conditions data with observation data. The success of the YSU scheme in comparison with other schemes is rooted in the nonlocal closure of this scheme, which includes local gradients correction and entrainment sentences.

Climatic aspects and vertical structure circulation associated with the severe drought in Northeast Brazil (2012–2016)

This study provides an updated dynamical analysis of the observed climate conditions during the longest, most severe and continuous drought (2012–2016) ever recorded in Northeast Brazil (NEB). This investigation was carried out based on temperature, precipitation, sea surface temperature, outgoing long-wave radiation, and ERA-Interim reanalysis data from 1981 to 2016. This was done by first looking for the area of the NEB where the drought was most severe, and then calculating the main rainy season anomalies and atmospheric parameters from 2012 to 2016 in relation to the climatological conditions (1981–2010). Results show this drought event was influenced mainly by two distinct oceanic conditions that induced anomalous atmospheric circulation patterns. The observed negative precipitation anomalies were firstly related to the northward displacement of the Intertropical Convergence Zone (ITCZ), followed by an anomalous upward motion over the Western Amazon, as well as the anomalous precipitation deficit along the South Atlantic Convergence Zone, that was slightly displaced southward of the climatological position. From 2015 to 2016 the subsidence over NEB Brazil was linked to the descending branch of the Walker circulation, as well as to the strong anomalous flow induced by convection in the ITCZ over Africa and Gulf of Mexico.

Seasonal Forecast of Early Summer Rainfall at Stations in South China Using a Statistical Downscaling Model

AbstractCurrent dynamic models are not able to provide reliable seasonal forecasts of regional/local rainfall. This study aims to improve the seasonal forecast of early summer rainfall at stations in South China through statistical downscaling. A statistical downscaling model was built with the canonical correlation analysis method using 850-hPa zonal wind and relative humidity from the ERA-Interim reanalysis data. An anomalous southwesterly wind that carries sufficient water vapor encounters an anomalous northeasterly wind from the Yangtze River, resulting in a wet anomaly over all of South China. This model provided good agreement with observations in both the training and independent test periods. In an independent test, the average temporal correlation coefficient (TCC) at 14 stations was 0.52, and the average root-mean-square error was 21%. Then, the statistical downscaling model was applied to the Climate Forecast System, version 2 (CFSv2), outputs to produce seasonal forecasts of rainfall for 1982–2018. A statistical downscaling model improved CFSv2 forecasts of station rainfall in South China with the average TCC increasing from 0.14 to 0.31. Forecasts of South China regionally averaged rainfall were also improved with the TCC increasing from 0.11 to 0.53. The dependence of forecast skill for regional average rainfall on ENSO events was examined. Forecast error was reduced, but not statistically significant, when it followed an El Niño event in both CFSv2 and the downscaling model. While when it followed an EP-type El Niño, the significantly reduced forecast error (at the 0.1 level) could be seen in the downscaling model and CFSv2.

Planetary Layer Lapse Rate Comparison of Tropical,Montane and Hot Semi-Arid Climates of Nigeria

This study assessed the pattern of planetary layer lapse rate across the major climate belts of Nigeria. Six years’ data (2010-2015) for air temperature values between 1000 mbar and 850 mbar atmospheric pressure levels were acquired from Era-Interim Re-analysis data centre. The data was retrieved at 6-hourly synoptic hours: 0000H, 0600H, 1200H and 1800H at 0.125o grid resolution. Results showed that the lower tropospheric layers throughout the various climate belts has a positive lapse rate. Findings also revealed that the average annual lapse rate condition were: Tropical wet zone (Port Harcourt) -5.6 oC/km; Bi-modal Tropical continental zone (Enugu) 5.8 oC/km; Montane zone (Jos) -6.5 oC/km; Mono-modal Tropical continental zone (Kano) -6.6 oC/km; and Hot semi-arid zone (Maiduguri) -6.6 oC/km. This average values presents the lapse rates to be close to the Saturated Adiabatic Lapse Rate (SALR). Average diurnal results for the climate belts showed that lapse rate is higher during the afternoon and transition periods than the rest periods and increases from the coastal areas northward. The seasonal periods of highest lapse rates during the day time are from December – May (i.e. 5.8-9.5 oC/km) with slight decrease from June – November. The positive lapse rate of range -1.8 – -5.9 oC/km observed during the period of dawn across the entire region showed that infrared radiation was still being released and modified by less energetic mechanical turbulence that characterizes the surface layer across Nigeria. This also indicates that global warming is real and in substantial effect. The study findings imply that conditional instability prevailed over the entire region, therefore, the planetary layer environment will be of slow to moderate dispersive potential and will require forceful mechanism to lift emissions are introduced into it. It is recommended that industrial stacks are above 50 m to enhance the dispersion of emissions aloft.

Evaluation of the 15-year ROM SAF monthly mean GPS radio occultation climate data record

Abstract. We here present results from an evaluation of the Radio Occultation Meteorology Satellite Application Facility (ROM SAF) gridded monthly mean climate data record (CDR v1.0), based on Global Positioning System (GPS) radio occultation (RO) data from the CHAMP (CHAllenging Minisatellite Payload), GRACE (Gravity Recovery and Climate Experiment), COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate), and Metop satellite missions. Systematic differences between RO missions, as well as differences of RO data relative to ERA-Interim reanalysis data, are quantified. The methods used to generate gridded monthly mean data are described, and the correction of monthly mean RO climatologies for sampling errors, which is essential for combining data from RO missions with different sampling characteristics, is evaluated. We find good overall agreement between the ROM SAF gridded monthly mean CDR and the ERA-Interim reanalysis, particularly in the 8–30 km height interval. Here, the differences largely reflect time-varying biases in ERA-Interim, suggesting that the RO data record has a better long-term stability than ERA-Interim. Above 30–40 km altitude, the differences are larger, particularly for the pre-COSMIC era. In the 8–30 km altitude region, the observational data record exhibits a high degree of internal consistency between the RO satellite missions, allowing us to combine data into multi-mission records. For global mean bending angle, the consistency is better than 0.04 %, for refractivity it is better than 0.05 %, and for global mean dry temperature the consistency is better than 0.15 K in this height interval. At altitudes up to 40 km, these numbers increase to 0.08 %, 0.11 %, and 0.50 K, respectively. The numbers can be up to a factor of 2 larger for certain latitude bands compared to global means. Below about 8 km, the RO mission differences are larger, reducing the possibilities to generate multi-mission data records. We also find that the residual sampling errors are about one-third of the original and that they include a component most likely related to diurnal or semi-diurnal cycles.

35 Years of Vegetation and Lake Dynamics in the Pechora Catchment, Russian European Arctic

High-latitude regions are a hot spot of global warming, but the scarce availability of observations often limits the investigation of climate change impacts over these regions. However, the utilization of satellite-based remote sensing data offers new possibilities for such investigations. In the present study, vegetation greening, vegetation moisture and lake distribution derived from medium-resolution satellite imagery were analyzed over the Pechora catchment for the last 35 years. Here, we considered the entire Pechora catchment and the Pechora Delta region, located in the northern part of European Russia, and we investigated the vegetation and lake dynamics over different permafrost zones and across the two major biomes, taiga, and tundra. We also evaluated climate data records from meteorological stations and re-analysis data to find relations between these dynamics and climatic behavior. Considering the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Moisture Index (NDMI) in the summer, we found a general greening and moistening of the vegetation. While vegetation greenness follows the evolution of summer air temperature with a delay of one year, the vegetation moisture dynamics seems to better concur with annual total precipitation rather than summer precipitation, and also with annual snow water equivalent without lag. Both NDVI and NDMI show a much higher variability across discontinuous permafrost terrain compared to other types. Moreover, the analyses yielded an overall decrease in the area of permanent lakes and a noticeable increase in the area of seasonal lakes. While the first might be related to permafrost thawing, the latter seems to be connected to an increase of annual snow water equivalent. The general consistency between the indices of vegetation greenness and moisture based on satellite imagery and the climate data highlights the efficacy and reliability of combining Landsat satellite data, ERA-Interim reanalysis and meteorological data to monitor temporal dynamics of the land surface in Arctic areas.

A Three-Dimensional Perspective on Extratropical Cyclone Impacts

AbstractCyclones can be identified from gridded pressure data at different levels of the troposphere, with vertical structure known to influence the temporal development and impacts of midlatitude cyclones. However, studies of midlatitude cyclones typically focus on cyclones identified at a single atmospheric level. This paper examines how the frequency of vertically organized or deep cyclones varies around the world, with a focus on southeastern Australia. About 50% of global cyclones identified from mean sea level pressure show a coherent vertical structure extending to at least 500 hPa, based on ERA-Interim reanalysis data, and shallow cyclones are most common in the global midlatitudes. Using a combination of reanalysis data and satellite-based rainfall and lightning, we show that in southeast Australia deep cyclones have higher intensities, longer durations, and more severe winds and rainfall than either shallow surface cyclones or upper-level cyclones with no surface low, motivating a three-dimensional approach for future cyclone analyses.

Lidar observations of aerosol enhancement in the upper troposphere and lower stratosphere

The upper troposphere and the lower stratosphere (UTLS) are the transition areas between the troposphere and stratosphere. Water vapor, cirrus clouds and aerosols in this area have a strong modulation effect on solar short-wave radiation and earth long-wave radiation. Changes in the content and distribution of aerosols in this level will have a radiant forcing impact on the climate. This article uses the observation data of MPL lidar (micropulse lidar) at SACOL station (Semi-arid Climate and Environment Observation Station of Lanzhou University, 34.946°N, 104.93°E) and ERA-Interim reanalysis data from June to December 2011 to study the changes of stratospheric aerosol over SACOL station after Nabro volcano eruption on June 12, 2011. The result indicates that after the Nabro volcanic eruption, there is an aerosol layer with significantly enhanced scattering ratio over the SACOL station, and the depolarization ratio of particles in the aerosol layer is relatively small, mainly spherical particles; by analyzing the backward trajectory of the stronger aerosol layer, it can be determined that the special aerosol layer was caused by the Nabro volcanic eruption.

A 33-yr Mei-Yu-Season Climatology of Shear Lines over the Yangtze–Huai River Basin in Eastern China

AbstractA 33-yr climatology of shear lines occurring over the Yangtze–Huai River basin (YHSLs) of eastern China during the mei-yu season (i.e., June and July) of 1981–2013 is examined using the daily ERA-Interim reanalysis data and daily rain gauge observations. Results show that (i) nearly 75% of the heavy-rainfall days (i.e., >50 mm day−1) are accompanied by YHSLs, (ii) about 66% of YHSLs can produce heavy rainfall over the Yangtze–Huai River basin, and (iii) YHSL-related heavy rainfall occurs frequently in the south-central basin. The statistical properties of YHSLs are investigated by classifying them into warm, cold, quasi-stationary, and vortex types based on their distinct flow and thermal patterns as well as orientations and movements. Although the warm-type rainfall intensity is the weakest among the four, it has the highest number of heavy-rainfall days, making it the largest contributor (33%) to the total mei-yu rainfall amounts associated with YHSLs. By comparison, the quasi-stationary type has the smallest number of heavy-rainfall days, contributing about 19% to the total rainfall, whereas the vortex type is the more frequent extreme-rain producer (i.e., >100 mm day−1). The four types of YHSLs are closely related to various synoptic-scale low-to-midtropospheric disturbances—such as the southwest vortex, low-level jets, and midlatitude traveling perturbations that interact with mei-yu fronts over the basin and a subtropical high to the south—that provide favorable lifting and the needed moisture supply for heavy-rainfall production. The results have important implications for the operational rainfall forecasts associated with YHSLs through analog pattern recognition.

Estimating Typhoon Waves based on the Modified ECMWF ERA-5 Wind Data

ERA-5 is a recently released reanalysis meteorological dataset provided by European Centre for Medium-Range Weather Forecasts (ECMWF). This study evaluates the representation of tropical cyclones (TC) in ERA-5 and the widely used ECMWF ERA-Interim (ERA-I) reanalysis data in the northwest Pacific region during year 2013 to 2015. Although ERA-5 wind data has a great improvement of precision during TC period than ERA-I data, it is still not accurate enough for the description of TCs especially when it is applied to estimate typhoon waves. To effectively correct this data, an empirical correlation is established between the maximum wind speed of TCs in ERA-5 and Best-track data. Then the ERA-5 data can be improved using a directly modified method without the requirement of observation TC track data. The modified ERA-5 wind data, the original ERA-5 data and the ERA-I data are applied to drive the FVCOM-SWAVE wave model to estimate the typhoon waves. The typhoon waves driven by the modified ERA-5 data show a better performance than that driven by other two wind datasets. The method introduced in this study for modification of ERA-5 wind data provides an alternative for the correction of this data during TC period when the observation TC track is unavailable.

Applicability of ERA-Interim High-resolution Significant Wave Height Data in Global Sea Areas

Wan, Y.; Zhang, X.; Dai, Y.; Li, W.; Li, L., and Qu, X., 2020. Applicability of ERA-Interim high-resolution significant wave height data in global sea areas. In: Zheng, C.W.; Wang, Q.; Zhan, C., and Yang, S.B. (eds.), Air-Sea Interaction and Coastal Environments of the Maritime and Polar Silk Roads. Journal of Coastal Research, Special Issue No. 99, pp. 1-8. Coconut Creek (Florida), ISSN 0749-0208.In this paper, ERA-Interim high-resolution ocean wave reanalysis data provided by the European Center for Medium-range Weather Forecasts (ECMWF) are matched with time-space data from buoys in the China Sea, the United States East and West Coast, the Central Pacific Ocean and European seas. Taking the significant wave height (SWH) as an example, ERA-Interim wave field data are verified, and their applicabilities in sea areas around the world are analyzed. The results show that the means of the correlation coefficients (CCs) obtained by fitting in each sea area are greater than 0.7. Furthermore, in all areas except for the European waters, the root mean square errors (RMSEs) are less than 0.4 m. The linear regression method is used to correct the data in the European sea area, and the corrected results are significantly better than the uncorrected results. The corrected CC is reduced by 3.23% compared to the uncorrected CC. The corrected RMSE is increased by 24.24% compared to the uncorrected RMSE. This shows that corrected data better reflect the real situation of the ocean surface than uncorrected data.