ERA-Interim Reanalysis Dataset Research Articles

Vertical structure of stratocumulus clouds and associated dynamics over the Arabian Sea during Indian summer monsoon season

Five years of CloudSat observations during the Indian summer monsoon (ISM) season are used to investigate the vertical structure of stratocumulus (Sc) clouds and associated dynamics over the western part of Arabian Sea. The amount of Sc clouds formed over these regions are quantified in terms of their frequency of occurrence (FOC) and the same is used to study their vertical structure, which is very important from their radiative impact standpoint. The analysis revealed that Sc clouds predominantly form in the 0.5- to 3-km altitude region with mean thickness of 2.5 km over the study region. However, the maximum FOC of Sc clouds is found at ∼1.2-km altitude. The prevailing meteorological conditions over the study region are also investigated using ERA-Interim reanalysis datasets, to figure out why the Sc clouds persistently form over this region during ISM period. The analysis revealed that the presence of strong thermal inversion at 850-hPa level formed due to large-scale subsidence, presence of a low-level jet at 850-hPa level, and the advection of dry air at 650-hPa level from the Arabian Desert lead to the inhibition of vertical development of Sc clouds over the Arabian Sea. The significance of the present study lies in characterizing the vertical structure of Sc clouds formed persistently over the Arabian Sea during ISM and divulging the prevailing dynamics and thermal structure responsible for the formation of the Sc clouds over the study region.

The analysis of a complex fire event using multispaceborne observations

This study documents a complex fire event that occurred on October 2016, in Middle East belligerent area. Two fire outbreaks were detected by different spacecraft monitoring instruments on board of TERRA, CALIPSO and AURA Earth Observation missions. Link with local weather conditions was examined using ERA Interim Reanalysis and CAMS datasets. The detection of the event by multiple sensors enabled a detailed characterization of fires and the comparison with different observational data.

Evaluation of in-situ wind speed and wave height measurements against reanalysis data for the Greek Seas

ERA-Interim, ECMWF’s reanalysis product, includes wave and atmospheric characteristics, with high temporal and spatial scale, providing more information on the marine state. Even though their assimilation process has been validated and verified in numerous studies, their performance in more local scales is still under examination. This research focuses on the evaluation of performance of ERA-Interim reanalysis datasets in the Greek Seas for wind and wave characteristics in comparison to POSEIDON buoy data. The results prove fair to good correlation for wave height (r = 0.67-0.94) and wind speed (r= 0.71-0.83) and different error statistics per sub-region. The upper 10% analysis shows an underestimate of 10-15% for wind speed and wave height from ERA-Interim in relation to the buoy measurements. The ERA-Interim and the buoy monthly means and standard deviations are also presented and discussed according to seasonal patterns. The results of the study are compared to other researches of wave hindcasting and wind reanalysis data for the Greek Seas and globally. It is shown that ERA-Interim products could be regarded as representative for the Greek Seas, although their application should be made with caution regarding the assessment of extreme conditions (i.e. given in analyses of upper percentiles) and especially at nearshore locations due to complex coastline configuration enhanced by the great number of islands.

Analysis of source regions and meteorological factors for the variability of spring PM10 concentrations in Seoul, Korea

CSEOF analysis is applied for the springtime (March, April, May) daily PM10 concentrations measured at 23 Ministry of Environment stations in Seoul, Korea for the period of 2003–2012. Six meteorological variables at 12 pressure levels are also acquired from the ERA Interim reanalysis datasets. CSEOF analysis is conducted for each meteorological variable over East Asia. Regression analysis is conducted in CSEOF space between the PM10 concentrations and individual meteorological variables to identify associated atmospheric conditions for each CSEOF mode. By adding the regressed loading vectors with the mean meteorological fields, the daily atmospheric conditions are obtained for the first five CSEOF modes. Then, HYSPLIT model is run with the atmospheric conditions for each CSEOF mode in order to back trace the air parcels and dust reaching Seoul. The K-means clustering algorithm is applied to identify major source regions for each CSEOF mode of the PM10 concentrations in Seoul. Three main source regions identified based on the mean fields are: (1) northern Taklamakan Desert (NTD), (2) Gobi Desert and (GD), and (3) East China industrial area (ECI). The main source regions for the mean meteorological fields are consistent with those of previous study; 41% of the source locations are located in GD followed by ECI (37%) and NTD (21%). Back trajectory calculations based on CSEOF analysis of meteorological variables identify distinct source characteristics associated with each CSEOF mode and greatly facilitate the interpretation of the PM10 variability in Seoul in terms of transportation route and meteorological conditions including the source area.

Fronts and precipitation in CMIP5 models for the austral winter of the Southern Hemisphere

Wintertime fronts climatology and the relationship between fronts and precipitation as depicted by a group of CMIP5 models are evaluated over the Southern Hemisphere (SH). The frontal activity is represented by an index that takes into account the vorticity, the gradient of temperature and the specific humidity at the 850 hPa level. ERA-Interim reanalysis and GPCP datasets are used to assess the performance of the models in the present climate. Overall, it is found that the models can reproduce adequately the main features of frontal activity and front frequency over the SH. The total precipitation is overestimated in most of the models, especially the maximum values over the mid latitudes. This overestimation could be related to the high values of precipitation frequency that are identified in some of the models evaluated. The relationship between fronts and precipitation has also been evaluated in terms of both frequency of frontal precipitation and percentage of precipitation due to fronts. In general terms, the models overestimate the proportion between frontal and total precipitation. In contrast with frequency of total precipitation, the frequency of frontal precipitation is well reproduced by the models, with the higher values located at the mid latitudes. The results suggest that models represent very well the dynamic forcing (fronts) and the frequency of frontal precipitation, though the amount of precipitation due to fronts is overestimated.

Influence of sudden stratospheric warming and quasi biennial oscillation on western disturbance over north India

This study demonstrates the variability in Western Disturbance during the sudden stratospheric warming (SSW) period and its eventual influence on the north Indian weather pattern. The modulations in the north Indian winter under the two phases of the Quasi-biennial oscillation (QBO) during SSW periods are also examined. The analysis has been carried out by using the ERA interim reanalysis dataset for different pressure levels in the stratosphere and upper troposphere during the time period of 1980–2010. The daily minimum surface temperature data published by India Meteorological Department from 1969 to 2013 has been used for the analysis of temperature anomaly over north India during SSW. The period of intense stratospheric warming witnesses a downward propagation and intensification of kinetic energy from stratosphere to upper troposphere over the Mediterranean and Caspian Sea. When QBO is in easterly phase, the cooling over north India is much larger when compared to the westerly phase during instances of SSW. SSW coincident with the easterly phase of QBO causes an intensified subtropical jet over the mid-latitude regions. The modulation in circulation pattern in stratosphere and upper troposphere when ENSO occurs during SSW period is also analysed separately. This study provides the link among SSW, Western Disturbances and the north Indian cooling during winter season.

Separating volcanic deformation and atmospheric signals at Mount St. Helens using Persistent Scatterer InSAR

Over the past two decades, GPS and leveling surveys have recorded cycles of inflation and deflation associated with dome building eruptions at Mount St. Helens. Due to spatial and temporal limitations of the data, it remains unknown whether any deformation occurred prior to the most recent eruption of 2004, information which could help anticipate future eruptions. Interferometric Synthetic Aperture Radar (InSAR), which boasts fine spatial resolution over large areas, has the potential to resolve pre-eruptive deformation that may have occurred, but eluded detection by campaign GPS surveys because it was localized to the edifice or crater. Traditional InSAR methods are challenging to apply in the Cascades volcanic arc because of a combination of environmental factors, and past attempts to observe deformation at Mount St. Helens were unable to make reliable observations in the crater or on much of the edifice.In this study, Persistent Scatterer InSAR, known to mitigate issues of decorrelation caused by environmental factors, is applied to four SAR data sets in an attempt to resolve localized sources of deformation on the volcano between 1995 and 2010. Many interferograms are strongly influenced by phase delay from atmospheric water vapor and require correction, evidenced by a correlation between phase and topography. To assess the bias imposed by the atmosphere, we perform sensitivity tests on a suite of atmospheric correction techniques, including several that rely on the correlation of phase delay to elevation, and explore approaches that directly estimate phase delay using the ERA-Interim and NARR climate reanalysis data sets. We find that different correction methods produce velocities on the edifice of Mount St. Helens that differ by up to 1cm/yr due to variability in how atmospheric artifacts are treated in individual interferograms. Additionally, simple phase-based techniques run the risk of minimizing any surface deformation signals that may themselves be correlated with elevation. The atmospherically corrected PS InSAR results for data sets overlapping in time are inconsistent with one another, and do not provide conclusive evidence for any pre-eruptive deformation at a broad scale or localized to the crater or edifice leading up to the 2004 eruption. However, we cannot rule out the possibility of deformation less than ~1cm/yr, or discern whether deformation rates increased in the months preceding the eruption. The results do significantly improve the spatial density of observations and our ability to resolve or rule out models for a potential deformation source for the pre-eruptive period.

Spatio-temporal rainfall patterns around Atlanta, Georgia and possible relationships to urban land cover

Spatio-temporal patterns in mean and extreme rainfall are examined around the city of Atlanta, Georgia using the Multi-sensor Precipitation Estimates (MPE) and ERA-Interim reanalysis datasets. The analysis spans the period 2002 to 2015 and employs a 9-cell gridded framework centered on downtown Atlanta. Statistically significant anomalies in daily precipitation were found over and downwind (predominately east to northeast) of Atlanta. The pattern of rainfall anomalies is most evident in the early evening hours of the day and is hypothesized to be related to the evolution of the skin or surface urban heat island (UHI), rather than the canopy layer UHI. The study formally proposes the term “flow regime dependent” downwind anomaly regions. Like previous results, the study reveals that downwind anomaly regions can vary as a function of prevailing wind regime. Using a metric called the Wet Millimeter Day (WMD), the study also finds that there is a tendency for extreme rainfall to cluster in the climatological downwind area of Atlanta. The work builds upon previous findings while employing different datasets to provide novel additional contributions related to the temporal evolution of the “urban rainfall effect” and the patterns of extreme rainfall.

Evaluation of present-day rainfall simulations over West Africa in CORDEX regional climate models

The objective of this study is to evaluate the ability of seven CORDEX regional climate models (RCMs), driven by ERA-Interim reanalysis dataset to simulate the observed rainfall characteristics over West Africa during the period of 1990–2008. The seasonal climatology, annual rainfall cycles, interannual variability, 850 hPa specific humidity, and wind fields of the RCMs outputs were assessed over a number of spatial scales covering three climatically homogenous subregions (Guinea Coast, Savannah, and Sahel) and the entire West Africa domain. The ability of the RCMs to simulate the response to El Nino and La Nina events were further assessed. Results indicate that the RCMs captured the spatial pattern of rainfall and the three distinctive phases of the West African monsoon reasonably. It is worth noting that RCA and CRCM5 failed to distinctively reproduce the monsoon jump while CCLM, HIRHAM, and REMO largely overestimated the amount of the pre- and the post-monsoon rainfall. The analysis also showed significant biases in individual models depending on the subregion and season under consideration. These biases appear to be linked to the model’s failure to resolve convective processes and topography accurately. The majority of the RCMs used were consistent with the ground observation in capturing the dry (wet) conditions associated with the El Nino (La Nina) events. Statistical analysis conclusively revealed that the RCMs performance varies over the subregions and seasons, implying that no single model is best at all time. In general, REGCM3 was found to be the most outstanding of all the RCMs and is therefore recommended for use in rainfall assessment over West Africa.

Characteristics of Water Vapor in the UTLS over the Tibetan Plateau Based on AURA/MLS Observations

Water vapor (WV) has a vital effect on global climate change. Using satellite data observed by AURA/MLS and ERA-Interim reanalysis datasets, the spatial distributions and temporal variations of WV were analyzed. It was found that high WV content in the UTLS over the southern Tibetan Plateau is more apparent in summer, due to monsoon-induced strong upward motions. The WV content showed the opposite distribution at 100 hPa, though, during spring and winter. And a different distribution at 121 hPa indicated that the difference in WV content between the northern and southern plateau occurs between 121 and 100 hPa in spring and between 147 and 121 hPa in winter. In the UTLS, it diminishes rapidly with increase in altitude in these two seasons, and it shows a “V” structure in winter. There has been a weak increasing trend in WV at 100 hPa, but a downtrend at 147 and 215 hPa, during the past 12 years. At the latter two heights, the WV content in summer has been much higher than in other seasons. Furthermore, WV variation showed a rough wave structure in spring and autumn at 215 hPa. The variation of WV over the Tibetan Plateau is helpful in understanding the stratosphere-troposphere exchange (STE) and climate change.

Validation of INSAT-3D sounder data with in situ measurements and other similar satellite observations over India

Abstract. To date, several satellites measurements are available which can provide profiles of temperature and water vapour with reasonable accuracies. However, the temporal resolution has remained poor, particularly over the tropics, as most of them are polar orbiting. At this juncture, the launch of INSAT-3D (Indian National Satellite System) by the Indian Space Research Organization (ISRO) on 26 July 2013 carrying a multi-spectral imager covering visible to long-wave infrared made it possible to obtain profiles of temperature and water vapour over India with higher temporal and vertical resolutions and altitude coverage, besides other parameters. The initial validation of INSAT-3D data is made with the high temporal (3 h) resolution radiosonde observations launched over Gadanki (13.5° N, 79.2° E) during a special campaign and routine evening soundings obtained at 12:00 UTC (17:30 LT). We also compared INSAT-3D data with the radiosonde observations obtained from 34 India Meteorological Department stations. Comparisons were also made over India with data from other satellites like AIRS, MLS and SAPHIR and from ERA-Interim and NCEP reanalysis data sets. INSAT-3D is able to show better coverage over India with high spatial and temporal resolutions as expected. Good correlation in temperature between INSAT-3D and in situ measurements is noticed except in the upper tropospheric and lower stratospheric regions (positive bias of 2–3 K). There is a mean dry bias of 20–30 % in the water vapour mixing ratio. Similar biases are noticed when compared to other satellites and reanalysis data sets. INSAT-3D shows a large positive bias in temperature above 25° N in the lower troposphere. Thus, caution is advised when using these data for tropospheric studies. Finally it is concluded that temperature data from INSAT-3D are of high quality and can be directly assimilated for better forecasts over India.

STEFLUX, a tool for investigating stratospheric intrusions: application to two WMO/GAW global stations

Abstract. Stratospheric intrusion (SI) events are a topic of ongoing research, especially because of their ability to change the oxidation capacity of the troposphere and their contribution to tropospheric ozone levels. In this work, a novel tool called STEFLUX (Stratosphere-to-Troposphere Exchange Flux) is presented, discussed, and used to provide a first long-term investigation of SI over two global hot-spot regions for climate change and air pollution: the southern Himalayas and the central Mediterranean Basin. The main purpose of STEFLUX is to obtain a fast-computing and reliable identification of the SI events occurring at a specific location and during a specified time window. It relies on a compiled stratosphere-to-troposphere exchange (STE) climatology, which makes use of the ERA-Interim reanalysis dataset from the ECMWF, as well as a refined version of a well-established Lagrangian methodology. STEFLUX results are compared to the SI observations (SIO) at two high-mountain WMO/GAW global stations in these climate hot spots, i.e., the Nepal Climate Observatory-Pyramid (NCO-P, 5079 m a.s.l.) and Mt. Cimone (2165 m a.s.l.), which are often affected by SI events. Compared to the observational datasets at the two specific measurement sites, STEFLUX is able to detect SI events on a regional scale. Furthermore, it has the advantage of retaining additional information concerning the pathway of stratospheric-affected air masses, such as the location of tropopause crossing and other meteorological parameters along the trajectories. However, STEFLUX neglects mixing and dilution that air masses undergo along their transport within the troposphere. Therefore, the regional-scale STEFLUX events cannot be expected to perfectly reproduce the point measurements at NCO-P and Mt. Cimone, which are also affected by small-scale (orographic) circulations. Still, the seasonal variability in SI events according to SIO and STEFLUX agrees fairly well. By exploiting the fact that the ERA-Interim reanalysis extends back to 1979, the long-term climatology of SI events at NCO-P and Mt. Cimone is also assessed in this work. The analysis of the 35-year record at both stations denies the existence of any significant trend in the SI frequency, except for winter seasons at NCO-P. Furthermore, for the first time, by using the STEFLUX outputs, we investigate the potential impact of specific climate factors (i.e. ENSO, QBO, and solar activity) on SI frequency variability over the Mediterranean Basin and the Himalayas.

Climatological aspects of cyclonic tracks associated with flood events in Crete, Greece

In this study, an attempt was made to identify the tracks of the synoptic-scale cyclones associated with flood events in Crete, a Greek island in the southern Aegean Sea and to investigate their kinematic and dynamic characteristics and vertical structure for a period of 25 years. Furthermore, a comparison is made with the corresponding characteristics of the population of surface cyclones passing over Crete during the same period. The Melbourne University Cyclone Tracking Algorithm was employed to examine the genesis and movement of these cyclones while their vertical profile was examined with the aid of the vertical tracing software, Vertical Tracking Scheme (VTS). The input data are based on ERA INTERIM reanalysis datasets with resolution 0.5° × 0.5° during the period 1990 to 2014. It was found that the vast majority originate mainly over the north African coasts, contrasting the preference of all cyclones passing over Crete to develop within the Southeast Mediterranean. Cyclones associated with the flood events are more intense than the cyclonic population, being mainly characterized by long duration and track length. Furthermore, they reveal characteristics of vertically organized baroclinic systems, suggesting that they are mainly driven by baroclinic processes at upper and lower levels.

A model-based climatology analysis of wind power resources at 100-m height over the Bohai Sea and the Yellow Sea

China has set ambitious goals for the development of offshore wind energy to meet the increasing energy demand of coastal provinces. Many studies have assessed the potential offshore wind energy in Chinese territorial waters. However, few studies have focused on the climatology, variability, and extreme climate of wind speeds and wind power, especially at hub height in this area. This type of study is important for selecting promising sites for offshore wind farms. In the present study, a 35-year (1979–2013) high-resolution (7km) wind hindcast over the Bohai Sea and the Yellow Sea (BYS) at 100-m height was constructed using the regional climate model COSMO-CLM (CCLM) driven by the ERA-Interim reanalysis dataset. The quality of wind speeds reconstructed by CCLM was assessed by a comparison with observation data at several stations. After verification, the climatology, variability, and extreme climate of winds over the BYS were spatially and temporally investigated. The results show that the 35-year mean wind speed is mostly between 7.0 and 7.5m/s; in the coastal areas of the BYS, the mean is less than 7.0m/s, and in the remote offshore areas, the mean is greater than 7.5m/s. The daily mean wind speed is stronger (weaker) in winter (summer) half year, with stronger (weaker) spatial variability. Wind power density is mainly 300–500W/m2. The interannual variability of annual mean wind speed and the wind power are in the range of 0.1–0.3m/s and 10–40W/m2, respectively. Decadal variances of the mean wind speed and the wind power are roughly within ±2% and ±5%, respectively, with a stronger variability along the southwestern coasts of the Yellow Sea. The distribution patterns of extreme winds (i.e., 5, 10, 30, and 50-year return values) are generally similar, with strength increasing from the northwest to the southeast. The wind energy characteristics for water areas and potential wind farm sites are summarized.

Seasonal Heat and Salt Balance in the Upper Gulf of California

ABSTRACT Montes, J.M.; Lavin, M.F., and Pares-Sierra, A.F., 2016. Seasonal heat and salt balance in the Upper Gulf of California. The salinity and heat balance, as well as the seasonal variation of the average absolute salinity (〈SA〉) and conservative temperature (〈Θ〉), were described by using data from 24 cruises within four domains in the Upper Gulf of California (UGC). Monthly values of SA and Θ, and surface fluxes obtained from ERA-Interim reanalysis data sets were fitted to a seasonal signal, and the horizontal fluxes of salinity and heat content were calculated by using balance equations. The UGC exports salt and heat to the Northern Gulf of California (NGC) almost all year, with an annual mean of 1.6 g/kg per year for the salinity flux and 0.16 terawatts (TW) for the heat flux. The results suggest that the net excess of evaporation (∼0.8 m/y) and heat gain by the surface (∼70 W/m2) are the main factors controlling the exchange of salinity and heat between the UGC and the NGC. To help identify the r...

HOAPS and ERA-Interim precipitation over the sea: validation against shipboard in situ measurements

Abstract. The satellite-derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) and ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim reanalysis data sets have been validated against in situ precipitation measurements from ship rain gauges and optical disdrometers over the open ocean by applying a statistical analysis for binary estimates. For this purpose collocated pairs of data were merged within a certain temporal and spatial threshold into single events, according to the satellites' overpass, the observation and the ERA-Interim times. HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially in the tropics and subtropics. Although precipitation rates are difficult to compare because along-track point measurements are collocated with areal estimates and the number of available data are limited, we find that HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide average precipitation rate is close to measurements. However, when regionally averaged over latitudinal belts, deviations between the observed mean precipitation rates and ERA-Interim exist. The most obvious ERA-Interim feature is an overestimation of precipitation in the area of the intertropical convergence zone and the southern subtropics over the Atlantic Ocean. For a limited number of snow measurements by optical disdrometers, it can be concluded that both HOAPS and ERA-Interim are suitable for detecting the occurrence of solid precipitation.

Influence of Climate Variability on Extreme Ocean Surface Wave Heights Assessed from ERA-Interim and ERA-20C

AbstractExtreme ocean surface wave heights significantly affect coastal structures and offshore activities and impact many vulnerable populations of low-lying islands. Therefore, better understanding of ocean wave height variability plays an important role in potentially reducing risk in such regions. In this study, global impacts of natural climate variability such as El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and Pacific decadal oscillation (PDO) on extreme significant wave height (SWH) are analyzed using ERA-Interim (1980–2014) and ECMWF twentieth-century reanalysis (ERA-20C; 1952–2010) datasets for December–February (DJF). The nonstationary generalized extreme value (GEV) analysis is used to determine the influence of natural climate variability on DJF maxima of SWH (Hmax), wind speed (Wmax), and mean sea level pressure gradient amplitude (Gmax). The major ENSO influence on Hmax is found over the northeastern North Pacific (NP), with increases during El Niño and decreases during La Niña, and its counter responses are observed in coastal regions of the western NP, which are consistently observed in both Wmax and Gmax responses. The Hmax response to the PDO occurs over similar regions in the NP as those associated with ENSO but with much weaker amplitude. Composite analysis of different ENSO and PDO phase combinations reveals stronger (weaker) influences when both variability modes are of the same (opposite) phase. Furthermore, significant NAO influence on Hmax, Wmax, and Gmax is observed throughout Icelandic and Azores regions in relation to changes in atmospheric circulation patterns. Overall, the response of extreme SWH to natural climate variability modes is consistent with seasonal mean responses.

Mechanisms controlling the SST air-sea heat flux feedback and its dependence on spatial scale

The turbulent air-sea heat flux feedback ( $$\alpha$$ , in $$\text {W m}^{-2}\text { K}^{-1}$$ ) is a major contributor to setting the damping timescale of sea surface temperature (SST) anomalies. In this study we compare the spatial distribution and magnitude of $$\alpha$$ in the North Atlantic and the Southern Ocean, as estimated from the ERA-Interim reanalysis dataset. The comparison is rationalized in terms of an upper bound on the heat flux feedback, associated with “fast” atmospheric export of temperature and moisture anomalies away from the marine boundary layer, and a lower bound associated with “slow” export. It is found that regions of cold surface waters ( $$\le$$ 10 $$^\circ \,$$ C) are best described as approaching the slow export limit. This conclusion is not only valid at the synoptic scale resolved by the reanalysis data, but also on basin scales. In particular, it applies to the heat flux feedback acting as circumpolar SST anomaly scales are approached in the Southern Ocean, with feedbacks of $$\le$$ 10 $$\text {W m}^{-2}\text { K}^{-1}$$ . In contrast, the magnitude of the heat flux feedback is close to that expected from the fast export limit over the Gulf Stream and its recirculation with values on the order of ≈40 $$\text {W m}^{-2}\text { K}^{-1}$$ . Further analysis suggests that this high value reflects a compensation between a moderate thermodynamic adjustment of the boundary layer, which tends to weaken the heat flux feedback, and an enhancement of the surface winds over warm SST anomalies, which tend to enhance the feedback.

Feature tracking in high-resolution regional climate data

In this paper, a suite of algorithms are presented which facilitate the identification and tracking of storm-indicative features, such as mean sea-level pressure minima, in high resolution regional climate data. The methods employ a hierarchical triangular mesh, which is tailored to the regional climate data by only subdividing triangles, from an initial icosahedron, within the domain of the data. The regional data is then regridded to this triangular mesh at each level of the grid, producing a compact representation of the data at numerous resolutions. Storm indicative features are detected by first subtracting the background field, represented by a low resolution version of the data, which occurs at a lower level in the mesh. Anomalies from this background field are detected, as feature objects, at a mesh level which corresponds to the spatial scale of the feature being detected and then refined to the highest mesh level. These feature objects are expanded to an outer contour and overlapping objects are merged. The centre points of these objects are tracked across timesteps by applying an optimisation scheme which uses five hierarchical rules. Objects are added to tracks based on the highest rule in the scheme they pass and, if two objects pass the same rule, the cost of adding the object to the track. An object exchange scheme ensures that adding an object to a track is locally optimal. An additional track optimisation phase is performed which exchanges segments between tracks and merges tracks to obtain a globally optimal track set. To validate the suite of algorithms they are applied to the ERA-Interim reanalysis dataset and compared to other storm-indicative feature tracking algorithms.

Using ERA-Interim reanalysis dataset to assess the changes of ground surface freezing and thawing condition on the Qinghai–Tibet Plateau

It is important to assess the freezing and thawing condition of ground surface for understanding the impacts of frozen ground on surface and subsurface hydrology, the surface energy and moisture balance, ecosystem conservation, and engineering construction on the Qinghai–Tibet Plateau (QTP). However, assessing the changes of ground surface freezing and thawing condition on the QTP still remains a challenge owing to data sparseness and discontinuous observations. The annual ground surface freezing index (GFI) and ground surface thawing index (GTI) could be used to predict changes of the thermal regime of permafrost and can be good indicators of climate change on the QTP, which has important engineering applications. In this study, we first calibrated the reanalysis ground surface temperature (GST) data using the methods of elevation correction on the QTP. After calibration, the quality of reanalysis data has been improved significantly. For the annual time series, the root mean square error decreased from 7.7 to 1.6 °C, the absolute value of mean bias error decreased from 7.5 to 0.0 °C, and the correlation coefficient increased from 0.62 to 0.86. Second, we estimated the annual and seasonal spatial distributions of GST. The spatial distribution of spring and autumn GST closely resembled the annual mean pattern. The long-term mean GFI and GTI from the calibrated reanalysis dataset were 1322.3 and 2027.9 °C/day, respectively. The GFI and GTI were presented as latitude and elevation zonation; it can also be seen that permafrost mostly occurred in the high GFI and low GTI regions. Estimating the GFI and GTI precisely will be utilized to model the permafrost distribution and estimate active layer thickness in the future.