ECMWF Re-Analysis Research Articles

Spatial Characteristics of Deep-Developed Boundary Layers and Numerical Simulation Applicability over Arid and Semi-Arid Regions in Northwest China

The spatial distribution and long-time variation of the deep-developed boundary layer are not well understood in arid and semi-arid regions of northwest China. ERA-Interim (ECMWF Reanalysis data, ECMWF: European Centre for Medium-Range Weather Forecasts) were used to study the deep-developed boundary layer in the five representative areas in summer and then the Weather Research Forecast (WRF) model was applied to simulate and verify its applicability. The results show that the boundary layer heights in the five representative areas are higher in late spring and summer (the highest is 2485~3502 m in June) and lower in autumn, winter and early spring (the lowest is 758~907 m in December). The seasonal variations of the boundary layer height are smaller at 02:00 BJT and 08:00 BJT, while the variations are relatively larger at 14:00 BJT and 20:00 BJT. The atmospheric boundary layer, with heights over 4000 m, generally exists in late spring and summer. The boundary layer heights are higher in the arid region than in the semi-arid region and the deep-developed boundary layer lasts longer in the arid region. The boundary layer heights present reductions from the northwest to the southeast, except for Minqin in the middle north. The numerical simulation results show that there is a significant difference between different combinations of parameterization schemes to simulate the deep-developed boundary layer in these areas. The combination Goddard+SLAB+ACM2 performs better in the extreme arid area, Dunhuang, and the arid areas, Jiuquan and Minqin, whereas the simulation effect of the combination Dudhia+Noah+ACM2 is better in the semi-arid areas, Yuzhong and Lanzhou. The difference between the schemes is related to the determination of the boundary layer height.

Characteristics and Formation of a Synoptic Situation Causing Sudden Turning of Mesoscale Convective Systems over South China

The characteristics and formation of a synoptic situation that causes a sudden turning motion of warm-sector mesoscale convective systems (MCSs) over South China are described, based on the collection and investigation of associated cases during April–June 2011–2017 using high-resolution observational data and ERA (ECMWF Re-Analysis)-Interim data. The results show that the blocking of a marked low-level high over eastern China (eastern high) on a strengthening low-level trough over southwestern China (southwestern trough) results in significant enhancement of southerly winds ahead of the trough, which produces a strong southeastward vertical wind shear at low levels near western Guangdong province. This low-level vertical wind shear results in sudden southeastward turning motion for the warm-sector MCSs entering into Guangdong province from Guangxi province. The formation of the eastern high is mainly attributable to the strong cyclonic wind anomaly over the northwestern Pacific Ocean, which continuously brings cold air from higher latitudes to eastern China, where high synoptic-scale transient anomaly of geopotential height (SSTA-GH) forms. This cyclonic wind anomaly is induced by a low SSTA-GH, which travels from the north and south sides of the Tibetan Plateau to the northwestern Pacific Ocean and develops significantly as a result of a strong upper-level low SSTA-GH coupling with it or approaching it. On the other hand, the high SSTA-GH over eastern China blocks the eastward extension of the low SSTA-GH originating from the Tibetan Plateau. Consequently, this low SSTA-GH turns to extend or move southeastward/southward to southwestern China, leading to intensification of the southwestern trough.

Development of a fine-resolution atmosphere-wave-ocean coupled forecasting model for the South China Sea and its adjacent seas

A 72-h fine-resolution atmosphere-wave-ocean coupled forecasting system was developed for the South China Sea and its adjacent seas. The forecasting model domain covers from from 15°S to 45°N in latitude and 99°E to 135°E in longitude including the Bohai Sea, the Yellow Sea, the East China Sea, the South China Sea and the Indonesian seas. To get precise initial conditions for the coupled forecasting model, the forecasting system conducts a 24-h hindcast simulation with data assimilation before forecasting. The Ensemble Adjustment Kalman Filter (EAKF) data assimilation method was adopted for the wave model MASNUM with assimilating Jason-2 significant wave height (SWH) data. The EAKF data assimilation method was also introduced to the ROMS model with assimilating sea surface temperature (SST), mean absolute dynamic topography (MADT) and Argo profiles data. To improve simulation of the structure of temperature and salinity, the vertical mixing scheme of the ocean model was improved by considering the surface wave induced vertical mixing and internal wave induced vertical mixing. The wave and current models were integrated from January 2014 to October 2015 driven by the ECMWF reanalysis 6 hourly mean dataset with data assimilation. Then the coupled atmosphere-wave-ocean forecasting system was carried out 14 months operational running since November 2015. The forecasting outputs include atmospheric forecast products, wave forecast products and ocean forecast products. A series of observation data are used to evaluate the coupled forecasting results, including the wind, SHW, ocean temperature and velocity. The forecasting results are in good agreement with observation data. The prediction practice for more than one year indicates that the coupled forecasting system performs stably and predict relatively accurate, which can support the shipping safety, the fisheries and the oil exploitation.

Solar radiation estimation at high latitudes: Assessment of the CMSAF databases, ASR and ERA5

There is a growing demand for the estimation of solar energy potential at high latitude locations. This study compares four datasets; Cloud, Albedo, Radiation dataset Edition 2 (CLARA), Surface Solar Radiation dataset – Heliosat Edition 2 (SARAH), ECMWF Reanalysis 5 (ERA5) and Arctic System Reanalysis v2 (ASR) on high latitude locations. Global horizontal irradiance (GHI) from these datasets is compared with in-situ ground-measurements over multiple locations in Norway. The first two datasets are mainly based on satellite estimation of solar radiation, while the latter two are based on a combination of a weather-prediction model, satellite data, and other observations. The datasets are evaluated against quality-controlled in-situ measurements of solar radiation from pyranometers. Overall, CLARA, SARAH, and ERA5 show moderate errors, while those of ASR are considerably larger. Monthly averages of global horizontal irradiance have mean absolute deviation (MAD) of 5.6 Wm−2, 5.0 Wm−2, 6.8 Wm−2, and 16.1 Wm−2 for CLARA, SARAH, ERA5, and ASR, respectively. Seasonal error analysis of these datasets reveals that CLARA and SARAH have low errors in all seasons. The datasets are classified into clear-sky, intermediate-cloudiness, and overcast categories, by using two thresholds of cloudiness based on the ratio of radiation at ground to its corresponding clear-sky value (clear-sky index). The categories obtained from satellite and reanalysis data are then compared against estimates based on corresponding in-situ observations; this analysis shows that both CLARA and SARAH perform better than ERA5 and ASR for these categories. SARAH and CLARA perform similarly in all types of conditions, but a gradual increase in errors for an increase of cloudiness is observed for ERA5 and ASR. Yearly energy analysis shows that CLARA performs better than other datasets for locations above latitude 65°N, and SARAH performs better in locations below 65°N. A further analysis is performed to assess the cloud sensing abilities of ERA5. On a shorter time scale, there are errors due to inaccurate representation of clouds, however on longer time scales i.e. months and years, these errors are considerably reduced. ERA5 is observed to overestimate TCWC (the total cloud water content defined as the mass of water and ice in a cloud) in clear-sky and intermediate-cloudy categories, while in overcast category it is underestimated. Generally, an overestimation of solar radiation is observed in reanalysis and an underestimation is observed in satellite methods.

Global trend analysis in primary and secondary production of marine aerosol and aerosol optical depth during 2000–2015

The global trends in sea spray aerosol (SSA) emissions, dimethyl sulfide (DMS) flux from sea to air, and aerosol optical depth (AOD) during 2000–2015 were analyzed using the satellite-based, ECMWF reanalysis, and model-predicted data. The SSA emissions were estimated using a widely used whitecap method with a sea surface temperature (SST) dependence. The sea-to-air DMS fluxes were estimated by a thin film model based on the DMS concentration in seawater and its gas transfer velocity. The yearly global mean anomaly in DMS fluxes showed a significant downward trend during the study period, whereas the SSA emissions showed an upward trend. In terms of regional trends, the increases in SSA emissions during 2000–2015 occurred over the tropical southeastern Pacific Ocean and Southern Ocean, whereas any downward trends in SSA emissions were localized. The DMS fluxes during the study period showed a clear downward trend over most oceans, except for the strong upward trend at low latitudes. In general, the AOD from the MODerate resolution Imaging SpectroRadiometer (MODIS) showed upward trends across the entire Southern Hemisphere (SH), whereas there were downward trends in most areas of the Northern Hemisphere (NH). Therefore, the upward trend of AOD in the SH were derived mainly from the SSA emission trend, due to smaller contribution of anthropogenic sources in the SH.

Characteristics of high-frequency gravity waves generated during pre-monsoon season over a tropical location: A case study

Mesoscale convection weather events, associated with deep cumulonimbus clouds transport moisture, energy and momentum to upper troposphere and lower stratosphere (UTLS), affect the energetics and general circulation of the middle atmosphere. Therefore, it is necessary to understand the atmospheric dynamics during pre–monsoon periods (when strong mesoscale convective events occur) for improving the parameterization of model physics. The present study attempts to investigate the characteristics of high-frequency gravity waves (GWs) generated over Gadanki (13.5° N, 79.2° E), India during one such severe convection event in the pre–monsoon period. For this purpose, the Mesosphere Stratosphere Troposphere (MST) radar at Gadanki was operated continuously for the period of ∼10 h during 27–28 May 2015. A wide spectrum of high frequency GWs with different generation mechanisms are found during this convective event whose vertical propagation characteristics fulfill the non-hydrostatic GWs dispersion relation. The temperature and wind data of ERA (ECMWF Re-Analysis)-interim reanalysis and GPS radiosonde, launched at Gadanki, are also analyzed for ten days around the event day to determine the background atmospheric thermodynamical conditions. Strong up- and downdrafts are observed in the altitude range of ∼3.6–20 km (radar limited top height); presence of which even up to ∼20 km height is quite rare. The WRF (Weather Research and Forecasting) model simulated relative humidity on 27–28 May 2015 clearly depicts the mid-tropospheric moisture intrusion. Presence of moisture is also observed at the higher heights ∼17–18 km which could be due to strong low level convergence leading to high divergence value of deep cumulonimbus clouds in UTLS region. Furthermore, this is supported by the Doppler Weather Radar (DWR) and simulated reflectivity of WRF model reaching the tropopause height of ∼18 km. The altitude profiles of phase of some oscillations during convection period depict that the sources of these waves are near ∼20 km which is first of its kind outcome and it is corroborated with high resolution WRF model simulations.

Modeling lightning density using cloud top parameters

The Price-Rind 92 parameterization (Price and Rind, 1992) that utilizes cloud top height as predictor for the estimation of lightning density is widely used by modelers in an attempt to forecast electrical activity in thunderstorms. In the present paper new parameterizations for the estimation of lightning density of convective clouds are formulated. LINET lightning data, NWC SAF (Satellite Application Facility on support to Nowcasting and Very Short-Range Forecasting) products and ERA-Interim (ECMWF-Re Analysis) data, covering the summer of 2016 over continental Europe, are used. The proposed models estimate the lightning density of convective clouds, using cloud top height, cloud top pressure and cold cloud depth as predictors. Model efficiency statistics calculated over an independent dataset, suggest that the proposed models can be considered successful over the specific area (continental Europe) and period (summer). The new cloud top height model differs from the PR92 and other parameterizations, which is not an unexpected result, since every model has its own characteristics, strengths and weaknesses. The new parameterizations could be utilized in numerical model simulations to produce quantitative estimations of the amount of strokes over convective areas.

Detection and attribution of upper-tropospheric warming over the tropical western Pacific

Both model and satellite observations suggest that the warming in the tropical upper troposphere is more pronounced than in the lower troposphere. This study describes the tropical upper-tropospheric-warming (UTW) in the ECMWF Reanalysis Interim dataset, and reveals radiative and non-radiative processes contributing to the long-term change in UTW. The maximum intensity of the UTW is found between 250 and 400 hPa with a warming rate about 3K/decade over the tropical Atlantic and western Pacific oceans. The warming is more prominent from boreal winter to early spring than the rest of the year. In the tropical western Pacific, where the warmest ocean water resides, the long-term change in the annual mean UTW is mainly contributed by the variations of atmospheric deep convection and the oceanic dynamical process and heat storage (Ocn) with the latter playing a more important role. The UTW caused by the deep convection is mainly through the latent heat release associated with enhanced upward motion and condensation. The UTW related to Ocn is mainly a result of enhanced upward long-wave radiation from the ocean surface due to the large heat storage in the thermocline. The variations in Ocn mainly contribute to the UTW from winter to early spring, while the changes in deep convection play a more essential role from summer to fall. Also shown by the differences in deep convection, a strengthening of the Walker circulation since the early 2000s is also found in the reanalysis, which is most apparent in boreal summer and fall over the tropical Pacific, facilitating the deep convection to dominate.

A Weibull Distribution Based Technique for Downscaling of Climatic Wind Field

This study proposes a simple approach based on Weibull distribution parameters for downscaling climatic wind speed and direction. In this method, the Weibull parameters of a Global Climate Model (GCM) are modified using Weibull parameters of the reference data (ECMWF). To correct the wind direction, the downscaling technique was applied to the eastward and northward wind components. All the wind components were simply transformed to positive values in order to fit a Weibull distribution. The unbiased wind speed was calculated by integrating the corrected wind components. Moreover, other models were considered to directly modify the wind speed (not wind components) using the same methodology. Performance and ability of the proposed approach were evaluated against the existing statistical downscaling techniques such as Multiplicative Shift Method (MSM), quantile mapping and support vector regression. In the models, the 6-h GCM wind component/speed was the sole predictor and the ECMWF reanalysis wind data was considered as the predictand. It is demonstrated that direct application of the proposed method on the wind speed slightly gives better estimation of the predictand rather than its application on wind components. The results indicate the Weibull distribution based method outperforms the other techniques for wind direction and magnitude. The method provides sound predictions for a wide range of wind speed from low to high values. By using the proposed downscaling technique for wind components, wind direction can be adjusted accordingly.

A new MesosphEO data set of temperature profiles from 35 to 85 km using Rayleigh scattering at limb from GOMOS/ENVISAT daytime observations

Abstract. Given that the scattering of sunlight by the Earth's atmosphere above 30–35 km is primarily due to molecular Rayleigh scattering, the intensity of scattered photons can be assumed to be directly proportional to the atmospheric density. From the measured relative density profile it is possible to retrieve an absolute temperature profile by assuming local hydrostatic equilibrium, the perfect gas law, and an a priori temperature from a climatological model at the top of the atmosphere. This technique has been applied to Rayleigh lidar observations for over 35 years. The GOMOS star occultation spectrometer includes spectral channels used to observe daytime limb scattered sunlight along the line of sight to a reference star. GOMOS Rayleigh scattering profiles in the spectral range of 420–480 nm have been used to retrieve temperature profiles between 35 and 85 km with a 2 km vertical resolution. Using this technique, a database of more than 309 000 temperature profiles has been created from GOMOS measurements. A global climatology was constructed using the new GOMOS database and is compared to an external model. In the upper stratosphere, the external model is based on the ECMWF reanalysis and the agreement with GOMOS is better than 2 K. In the mesosphere the external model follows the MSIS climatology and 5 to 10 K differences are observed with respect to the GOMOS temperature profiles. Comparisons to night-time collocated Rayleigh lidar profiles above the south of France show some vertical structured temperature differences, which may be partially explained by the contributions of the thermal diurnal tide. The equatorial temperature series shows clear examples of mesospheric inversion layers in the temperature profiles. The inversion layers have global longitudinal extension and temporal evolution, descending from 80 to 70 km over the course of a month. The climatology shows a semi-annual temperature variation in the upper stratosphere, a stratopause altitude varying between 47 and 54 km, and an annual variation in the temperatures of the mesosphere. The technique that derive temperature profiles from Rayleigh limb scattering can be applied to any other limb-scatter sounder, providing that the observations are in the spectral range 350–500 nm. Due to the simplicity of the principles involved, this technique is also a good candidate for a future missions where constellations of small satellites are deployed.

A 4D feature‐tracking algorithm: A multidimensional view of cyclone systems

An objective four‐dimensional (4D) algorithm developed to track extratropical relative vorticity anomaly 3D structure over time is introduced and validated. The STACKER algorithm, structured with the TRACKER single‐level tracking algorithm as source of the single‐level raw tracks, objectively combines tracks from various levels to determine the 3D structure of the cyclone (or anticyclone) events throughout their life cycle. STACKER works progressively, beginning with two initial levels and then adding additional levels to the stack in a bottom‐up and/or top‐down approach. This allows an iterative stacking approach, adding one level at a time, resulting in an optimized 4D determination of relative vorticity anomaly events.A two‐stage validation process is carried out with the ECMWF reanalysis ERA‐Interim dataset for the 2015 austral winter. First the overall tracking capability during an austral winter, taking into account a set of climate indicators and their impacts on Southern Hemisphere circulation, was compared to previous climatologies, in order to verify the density and distribution of the cyclone events detected by STACKER. Results show the cyclone density distribution is in very good agreement with previous climatologies, after taking into account potential differences due to climate variability and different tracking methodologies. The second stage focuses on three different long‐lived events over the Southern Hemisphere during the winter of 2015, spanning seven different pressure levels. Both GOES satellite imagery, infrared and water vapour channels, and ERA‐Interim cloud cover products are used in order to validate the tracks obtained as well as the algorithm's capability and reliability. The observed 3D cyclone structures and their time evolution are consistent with current understanding of cyclone system development. Thus, the two‐stage validation confirms that the algorithm is suitable to track multilevel events, and can follow and analyse their 3D life cycle and develop full 3D climatologies and climate variability studies.

Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data

Precipitable water vapor (PWV) content detection is vital to heavy rain prediction; up to now, lots of different measuring methods and devices are developed to observe PWV. In general, these methods can be divided into two categories, ground-based or space-based. In this study, we analyze the advantages and disadvantages of these technologies, compare retrieved atmosphere parameters by different RO (radio occultation) observations, like FORMOSAT-3/COSMIC (Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere, and Climate) and FY3C (China Feng Yun 3C), and assess retrieved PWV precision with a radiosonde. Besides, we interpolate PWV from NWP (numerical weather prediction) reanalysis data for more comparison and analysis with RO. Specifically, ground-based GNSS is of high precision and continuous availability to monitor PWV distribution; in our paper, we show cases to validate and compare GNSS retrieving PWV with a radiosonde. Except GNSS PWV, we give two different radio occultation sounding results, COSMIC and FY3C, to validate the precision to monitor PWV from space in a global area. FY3C results containing Beidou (China Beidou Global Satellite Navigation System) radio occultation events need to be emphasized. So, in our study, we get the retrieved atmospheric profiles from GPS and Beidou radio occultation observations and derive atmosphere PWV by a variational retrieval method based on these data over a global area. Besides, other space-based methods, such as microwave satellite, are also useful in detecting PWV distribution situations in a global area from space; in this study, we present a case of retrieved PWV using microwave satellite observation. NWP reanalysis data ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim and the new-generation reanalysis data ERA5 provide global grid atmosphere parameters, like surface temperature, different-level pressures, and precipitable water. We show cases of retrieved PWV and validate the precision with radiosonde results and compare new reanalysis dataset ERA5 with ERA-Interim, finding that ERA5 can get higher precision-retrieved atmosphere parameters and PWV. In the end, from our comparison, we find that the retrieved PWV from RO (FY3C and COSMIC) and ECMWF reanalysis data (ERA-Interim and ERA5) have a high positive correlation and that almost all R2 values exceed 0.9, compare retrieved PWV with a radiosonde, and find that whether it is RO and ECMWF reanalysis data, ground-based GNSS, or microwave satellite, they all show small biases.

Bio-Economic Assessment of Climate-Smart Tea Production in The Northern Mountainous Region of Vietnam

Agricultural production in the face of climate change requires a climate-smart transformation and reorientation at multiple scales. Vietnam is one of the developing countries that is agriculture-based and severely affected by climate change; therefore it is crucial that the agricultural system advances toward this transformation. While climate-smart agriculture has gained a significant attention in global fora, context-specific evidence is still scarce in Vietnam. This study examines climate-smart agriculture potentials in tea production systems in the northern mountainous region of Vietnam. Since the climate-smart agriculture concept is multidimensional, which includes food security and adaptation and mitigation, an interdisciplinary analytical framework is employed in this research to assess the economic and biophysical dimensions. Enterprise budgets and representative farms (i.e., farms or households having one or more activities or enterprises) are developed for tea and alternative crops, as well as livestock production, to analyze the productivity dimension of food security. In evaluating the adaptation potential of tea production, local farmers’ perceptions and experiences of extreme weather events are combined with ERA-Interim data (1989-2013) and household survey data on income levels (reanalysis dataset taken from the European Centre for Medium-Range Weather Forecasts; ERA stands for ECMWF Reanalysis). Greenhouse gas emissions and carbon sequestration potentials are estimated through partial Carbon Footprint Life Cycle Assessment. Results show that tea production systems generate net margins, returns to capital, and family labor higher than the alternatives. Farmers, therefore, have high incentives to switch from other crops to tea production. In the face of climate change, tea has shown a strong biophysical adaptive capacity compared to other crops in the northern mountainous region. Tea production systems have a high capability for carbon storage. Evidence of strong synergies between food security and mitigation and adaptation is demonstrated for tea production systems in the northern mountainous region, and potential tradeoffs were highlighted, where relevant.

Effect of hydrometeor species on very-short-range simulations of precipitation using ERA5

The impact of five hydrometeor species provided by the fifth generation of ECMWF ReAnalysis (ERA5) on the skill of precipitation forecasts is investigated in very-short-range numerical weather prediction modeling using WRF. Three sets of experiments using different numbers of hydrometeors as input in the initial and lateral boundary conditions were designed for 6-h forecasts run over the region of Korea in East Asia during two one-month periods of the summer and winter seasons: specific humidity only, additional specific cloud liquid water and cloud ice water, and additional specific rain water and snow water. The 6-class Thompson microphysics parameterization scheme that uses prognostic condensate variables was adopted for forecasts to represent the effect of using these hydrometeors in the initial conditions. Simulated precipitation was verified against surface observations in terms of both categorical scores based on contingency tables and object-oriented measures. The evaluation of the precipitation skill reveals that the forecasts using multiple hydrometeors as input generally show increased skill of precipitation forecasts compared to forecasts using only specific humidity as input. It is found that the increase of precipitation forecasting skill appears both in winter and in summer. Using more hydrometeors in the initial conditions reduces the spin-up time and accelerates the occurrence of resolved precipitation in the model. This effect is clearly shown in the first one to two hours of the forecast. Afterwards, the precipitation forecast skill is similar to that of forecasts that use only specific humidity as input in the initial conditions. The more hydrometeor species used in the initial conditions of the forecast model, the more skillful becomes its precipitation forecast in the initial hours. Another set of experiments using liquid- and ice-phase hydrometeors separately shows that initialization with ice-phase hydrometers would be slightly more important to improving precipitation forecasts. Note that the results reported here should be understood as valid under the specific experimental configuration in this paper.

Characterising droughts in Central America with uncertain hydro-meteorological data

Central America is frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation, monitoring and forecasting are potentially useful to support water resource management. Drought indices are designed for these purposes, but their ability to characterise droughts depends on the characteristics of the regional climate and the quality of the available data. Local comprehensive and high-quality observational networks of meteorological and hydrological data are not available, which limits the choice of drought indices and makes it important to assess available datasets. This study evaluated which combinations of drought index and meteorological dataset were most suitable for characterising droughts in the region. We evaluated the standardised precipitation index (SPI), a modified version of the deciles index (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), the CRN073 dataset, the Climate Research Unit (CRU), ECMWF Reanalysis (ERA-Interim) and a regional station dataset, and temperature from the CRU and ERA-Interim datasets. The gridded meteorological precipitation datasets were compared to assess how well they captured key features of the regional climate. The performance of all the drought indices calculated with all the meteorological datasets was then evaluated against a drought index calculated using river discharge data. Results showed that the selection of database was more important than the selection of drought index and that the best combinations were the EDI and DI calculated with CHIRPS and CRN073. Results also highlighted the importance of including indices like SPEI for drought assessment in Central America.

Medium earth orbit optical satellite communication networks: Ground terminals selection optimization based on the cloud‐free line‐of‐sight statistics

SummaryIn this paper, a methodology for the generation of cloud coverage time series correlated on both temporal and spatial domains and the estimation of cloud‐free line‐of‐sight (CFLOS) probability for a single optical ground station (OGS) and a network of OGSs (multiple OGS) for medium earth orbit (MEO) constellation satellite communication systems is presented. Spatial diversity is employed as a mitigation technique against cloud blockage to increase the availability of an OGS network (OGSN). In the second part of the paper, an effective algorithm based on the ant colony optimization (ACO) algorithm is proposed for the optimum selection of OGSs forming an OGSN. The proposed algorithm takes into consideration the spatial correlation between the OGSs. In the simulation results section, a MEO constellation system with 12 MEO satellites has been assumed. The integrated liquid water content (ILWC) statistical parameters that are necessary for the CFLOS time series are taken from ECMWF Re‐Analysis (ERA)‐Interim database, European Centre for Medium‐Range Weather Forecasts (ECMWF). Finally, numerical results for the optimum selection of OGSs using the proposed methodology are exhibited and commented. Interesting conclusions are drawn, and future work with technical challenges is briefly described.

Large‐Scale Drivers and Seasonal Predictability of Extreme Wind Speeds Over the North Atlantic and Europe

AbstractAs extreme wind speeds are responsible for large socioeconomic losses in the European domain, a skillful prediction would be of great benefit for disaster prevention as well as the actuarial community. Here we evaluate the patterns of atmospheric variability and the seasonal predictability of extreme wind speeds (e.g., >95th percentile) in the European domain in the dynamical seasonal forecast system European Centre for Medium‐Range Weather Forecasts (ECMWF) System 4 and compare to the predictability using a statistical prediction model. Further we compare the seasonal forecast system with ECMWF Re‐Analysis (ERA)‐Interim in order to advance the understanding of the large‐scale conditions that generate extreme winds. The dominant mean sea level pressure patterns of atmospheric variability show distinct differences between reanalysis and System 4 as most patterns in System 4 are extended downstream in comparison to ERA‐Interim. This dissimilar manifestation of the patterns across the two models leads to substantially different drivers associated with the generation of extreme winds: While the prominent pattern of the North Atlantic Oscillation could be identified as the main driver in the reanalysis, extreme winds in System 4 appear to be related to different large‐scale atmospheric pressure patterns. Thus, our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world. This circumstance is likely related to the unrealistic representation of the atmospheric patterns driving these extreme winds. Hence, our study points to potential improvements of dynamical prediction skill by improving the simulation of large‐scale atmospheric variability.

Spatio-Temporal Characteristics of Tropospheric Ozone and Its Precursors in Guangxi, South China

The temporal and spatial distributions of tropospheric ozone and its precursors (NO2, CO, HCHO) are analyzed over Guangxi (GX) in South China. We used tropospheric column ozone (TCO) from the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) onboard the Aura satellite (OMI/MLS), NO2 and HCHO from OMI and CO from the Measurements of Pollution in the Troposphere (MOPITT) instrument in the period 2005–2016. The TCO shows strong seasonality, with the highest value in spring and the lowest value observed in the monsoon season. The seasonal variation of HCHO is similar to that of TCO, while NO2 and CO show slightly different patterns with higher values in spring and winter compared to lower values in autumn and summer. The surface ozone, NO2 and CO observed by national air quality monitoring network sites are also compared with satellite-observed TCO, NO2 and CO, showing good agreement for NO2 and CO but a different seasonal pattern for ozone. Unlike TCO, surface ozone has the highest value in autumn and the lowest value in winter. To reveal the difference, the vertical profiles of ozone and CO from the measurement of ozone and water vapor by airbus in-service aircraft (MOZAIC) observations over South China are also examined. The seasonal averaged vertical profiles of ozone and CO show obvious enhancements at 2–6 km altitudes in spring. Furthermore, we investigate the dependence of TCO and surface ozone on meteorology and transport in detail along with the ECMWF reanalysis data, Tropical Rainfall Measuring Mission (TRMM) 3BV42 dataset, OMI ultraviolet index (UV index) dataset, MODIS Fire Radiative Power (FRP) and back trajectory. Our results show that the wind pattern at 800 hPa plays a significant role in determining the seasonality of TCO over GX, especially for the highest value in spring. Trajectory analysis, combined with MODIS FRP suggests that the air masses that passed through the biomass burning (BB) region of Southeast Asia (SEA) induced the enhancement of TCO and CO in the upper-middle troposphere in spring. However, the seasonal cycle of surface ozone is associated with wind patterns at 950 hPa, and the contribution of the photochemical effect is offset by the strong summer monsoon, which results in the maximum surface ozone concentration in post-monsoon September. The variations in the meteorological conditions at different levels and the influence of transport from SEA can account for the vertical distribution of ozone and CO. We conclude that the seasonal distribution of TCO results from the combined impact of meteorology and long-term transport.

WET TROPOSPHERIC CORRECTION’S IMPACT ON SEA LEVEL ANOMALY AROUND THE INDONESIAN SEAS

Global sea level rise in the satellite altimetry era is about 3 mm/yr. The one of main source of uncertainty of global sea level is the wet tropospheric from onboard microwave radiometer which is up to 0.3 mm/yr. The focus of this study is to assess of various wet tropospheric correction impact on sea level anomaly in the Indonesian seas. The result of sea level anomaly linear trend difference between Global Navigation Satellite System and Microwave Radio Meter or ECMWF Re-Analysis Interim is 0.18 mm/yr in agreement with the global wet tropospheric uncertainty.

Representation of Multidecadal Sahel Rainfall Variability in 20th Century Reanalyses

Summer rainfall in the Sahel region has exhibited strong multidecadal variability during the 20th century causing dramatic human and socio-economic impacts. Studies have suggested that the variability is linked to the Atlantic multidecadal variability; a spatially persistent pattern of warm/cold sea surface temperatures in the North Atlantic. In the last few years, several promising century-long reanalysis datasets have been made available, opening up for further studies into the dynamics inducing the observed low-frequency rainfall variability in Sahel. We find that although three of the 20th century ECMWF reanalyses show clear multidecadal rainfall variability with extended wet and dry periods, the timing of the multidecadal variability in two of these reanalyses is found to exhibit almost anti-phase features for a large part of the 20th century when compared to observations. The best representation of the multidecadal rainfall variability is found in the ECMWF reanalysis that, unlike the other reanalyses (including NOAA’s 20th century), do not assimilate any observations and may well be a critical reason for this mismatch, as discussed herein. This reanalysis, namely ERA-20CM, is thus recommended for future studies on the dynamics driving the multidecadal rainfall variability in Sahel and its linkages to the low-frequency North Atlantic oceanic temperatures.