ERA-Interim Reanalysis Dataset Research Articles

The Influence of Dynamical Downscaling and Boundary Layer Selection on Egypt’s Potential Evapotranspiration using a Calibrated Version of the Hargreaves-samani Equation: RegCM4 Approach

Potential Evapotranspiration (PET) is an important variable for monitoring daily agricultural activity as well as meteorological drought. Therefore, it is necessary to investigate the influence of different options of the physical dynamical downscaling and boundary layer schemes on the simulated PET. Using the RegCM4 regional climate model, four simulations were conducted (two for each case) in the period 1997 to 2017. In all simulations, the RegCM4 was configured with 25 km resolution and downscaled by the ERA-Interim reanalysis dataset. To ensure a reliable estimation of the PET, a calibrated version of the Hargreaves-Samani equation was adopted. A high-resolution product of the ERA5 was used as the observational dataset. Results showed that the simulated PET is insensitive either to the dynamical downscaling or the boundary layer options. Concerning the annual climatological cycle, the RegCM4’s performance varies with month and location. Quantitatively, a root mean square error lies between 1 mm and 1.6 mm day-1, the Nash-Sutcliffe efficiency between 0.2 and 0.6, and the coefficient of determination between 0.5 and 0.75. Additionally, the Linear Scaling (LS) method showed its added value in the evaluation/validation periods. In conclusion, the RegCM4 can be used to develop a regional PET map of Egypt using the LS either in the present climate or under different future scenarios.

Modeling of Future Streamflow Hazards in Interior Alaska River Systems and Implications for Applied Planning

There is a growing need for proactive planning for natural hazards in a changing climate. Computational modeling of climate hazards provides an opportunity to inform planning, particularly in areas approaching ecosystem state changes, such as Interior Alaska, where future hazards are expected to differ significantly from historical events in frequency and severity. This paper considers improved modeling approaches from a physical process perspective and contextualizes the results within the complexities and limitations of hazard planning efforts and management concerns. Therefore, the aim is not only to improve the understanding of potential climate impacts on streamflow within this region but also to further explore the steps needed to evaluate local-scale hazards from global drivers and the potential challenges that may be present. This study used dynamically downscaled climate forcing data from ERA-Interim reanalysis datasets and projected climate scenarios from two General Circulation Models under a single Representative Concentration Pathway (RCP 8.5) to simulate an observational gage-calibrated WRF-Hydro model to assess shifts in streamflow and flooding potential in three Interior Alaska rivers over a historical period (2008–2017) and two future periods (2038–2047 and 2068–2077). Outputs were assessed for seasonality, streamflow, extreme events, and the comparison between existing flood control infrastructure in the region. The results indicate that streamflow in this region is likely to experience increases in seasonal length and baseflow, while the potential for extreme events and variable short-term streamflow behavior is likely to see greater uncertainty, based on the divergence between the models.

The spatiotemporal variation of land surface heat fluxes in Tibetan Plateau during 2001–2022

The surface energy budget is important for understanding of energy and water cycle processes in the Tibetan Plateau (TP). In this study, the daily sensible (SH) and latent (LE) heat fluxes at the horizontal resolution of 1° are first estimated using the maximum entropy production (MEP) model (hereinafter SHMEP and LEMEP) in the entire TP during 2001–2022. The MEP model is built on physical and statistical principles to simulate surface heat fluxes. The surface net radiation, soil moisture (SM), and land surface temperature (LST) are the main driving variables for MEP model. To select the relatively accurate MEP input data, the merged surface net radiation (Rn–merged) under all-sky conditions are generated from CERES, ISCCP-FH, and ERA5 using the Bayesian Model Averaging scheme. Besides, the TP SM and LST from various data sources are evaluated using the in-situ observations at site scale. Based on the daily Rn–merged, ERA5 SM, CERES LST, and the MEP model, the daily SH and LE are estimated in the entire TP. The results show the daily SHMEP and LEMEP perform well at the validation sites, with the regional mean correlation coefficient (R) above 0.7, root-mean-square error (RMSE) of <19 W m−2, absolute value of bias and mean absolute error (MAE) below 11 W m−2. The monthly SHMEP has the regional mean R of 0.96 and RMSE of 6.30 W m−2 at all the measurement stations. For LEMEP, the regional mean R and RMSE values are 0.93 and 10.01 W m−2, respectively. The MEP simulation results are superior to the SH and LE in ERA5, ERA-Interim, MERRA-2, and JRA-55 reanalysis datasets and previous studies, especially for LE. Based on this new dataset, the spatial and temporal varying characteristics of SH and LE in the TP are analyzed. The annual mean SHMEP value are large in the western TP, the Qaidam Basin in the northern TP, and the Himalaya ranges, and small in the southeastern TP. The annual mean LEMEP has the maximum value in southeastern TP, and minimum value in western TP and the Qaidam Basin. The annual mean SHMEP and LEMEP over the entire TP are 34.79 W m−2 and 20.16 W m−2, with the significant declining trends of −0.17 W m−2 year−1 and − 0.052 W m−2 year−1 during the study period, respectively. The spatial distributions of the MEP surface heat fluxes and their trends are mainly influenced by the model inputs of Rn and SM in the TP.

Extreme droughts and corresponding Summer Monsoon: A Case Study of 2009 Indian Drought

Drought is a sustained result of continuous surface and atmospheric heating and moisture deficit. In general, drought assessment is made based on various indices. However, the drought dynamics and associated surface energetics about the corresponding Indian Summer Monsoon (ISM, i.e., June, July, August and September-JJAS) still needs to be better understood. Prolonged surface heating causes reduction of soil moisture, surface/subsurface runoff and atmospheric moisture. Excess surface heating results from positive surface energy budget, which is computed using the term, surface net solar radiation (SNSR), surface net thermal radiation (SNTR), surface sensible heat flux (SSHF), and surface latent heat flux (SLHF). It may also be the possible reason for enhanced convection. Convection also depends on the moisture holding capacity of the atmosphere, which increases with increasing air temperature. These processes lead to moisture content deficit and rainfall suppression due to moisture divergence from the convective sources. India Meteorological Department (IMD) (station and 0.25° gridded) and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis (0.25° resolution) datasets are used to study the extreme drought events. Drought indices such as Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI), Soil Moisture Index (SMI) and Sensible Heat Index (SHI) are used. Results indicate that anomalous lowering of available surface soil moisture and increase of surface sensible heat flux is a possible cause for enhancing extreme drought during the 2009 ISM. The associated Hadley circulation shows anomalous weakening, which led to reduced northward moisture transport from the southern oceans, further acerbating moisture deficit. Most parts of India suffered from anomalous decrement in specific humidity in the lower to upper troposphere and related precipitation scarcity during the drought period. The atmosphere’s increased moisture holding capacity sets a weak monsoon due to moisture divergence from ocean/local convection. However, likely, the excessive surface warming (due to SNSR/SNTR trapped into the surface) led to the extreme drought during 2009 ISM.

A sub-seasonal oscillation of sea surface temperature in the Southern Indian Ocean during DJF and its excitation mechanism

Southern Indian Ocean dipole (SIOD) is a dipole SST anomaly in the Southern Indian Ocean that plays an important role in tropical climate variability. However, previous studies focused on the interannual and interdecadal scales. In this paper, the characteristics on sub-seasonal scale of SIOD are revealed from December to February (DJF) based on the ERA-Interim reanalysis dataset, and the excitation mechanisms of SIOD are also discussed. The results show that the two dominant modes of SST in the Southern Indian Ocean are the spatial distribution of Southwest-Northeast direction dipole (SIOD) and triple (SIOT) respectively, which has obvious period of quasi 50–60 days. Moreover, the intensity and zonal oscillation of the Mascarene high are conducive to the formation of SIOD (SIOT). The air–sea interaction during the formation process is composed of three stages. In the first stage the atmospheric forces the ocean to result in the Mascarene high westward (eastward) and enhances the abnormal anticyclone in the Southern Indian Ocean. There are abnormal northerly (southerly) flows on the west (east) sides of the abnormal anticyclone respectively, which weakens (enhances) the southeast trade wind in the climatology. The surface latent heat flux release decreases (increases) and SST is warmed (cooled). During the following stage, the ocean feedback the atmosphere. The warm SST continues to increase, resulting in low-level convective enhancement, which weakens the abnormal anticyclone. The third stage is again the atmosphere forcing the ocean. The abnormal anticyclone gradually turns into an abnormal cyclone and the meridional wind direction is reversed. The release of the latent heat flux increases (decreases) significantly which leads to the cooling (warming) of SST on the west (east) sides of an abnormal cyclone. In addition, the formation and extinction of SIOT are easier affected by the southern annular mode (SAM) than SIOD. The abnormal zonal wave train with wavenumber 4 (3) propagates the Southern Indian Ocean by the westerly jet waveguide and results in an SST anomaly of SIOD (SIOT), accompanied by an obvious sub-seasonal meridional variation of the precipitation in Southern Africa.

Recurrent Rossby waves and south-eastern Australian heatwaves

Abstract. In the Northern Hemisphere, recurrence of transient synoptic-scale Rossby wave packets in the same phase over periods of days to weeks, termed RRWPs, may repeatedly create similar surface weather conditions. This recurrence can lead to persistent surface anomalies. Here, we first demonstrate the significance of RRWPs for persistent hot spells in the Southern Hemisphere (SH) using the ERA-Interim (ERA-I) reanalysis dataset and then examine the role of RRWPs and blocks for heatwaves over south-eastern Australia (SEA). A Weibull regression analysis shows that RRWPs are statistically associated with a significant increase in the duration of hot spells over several regions in the SH, including SEA. Two case studies of heatwaves in SEA in the summers of 2004 and 2009 illustrate the role of RRWPs in forming recurrent ridges (anticyclonic potential vorticity – PV – anomalies), aiding in the persistence of the heatwaves. Then, using a weather-station-based dataset to identify SEA heatwaves, we find that SEA heatwaves are more frequent than climatology during days with extreme RRWPs activity over SEA (high RSEA). On days with both high RSEA and heatwaves, circumglobal zonal wavenumber 4 and 5 (WN4, WN5) anomaly patterns are present in the composite mean of the upper-level PV field, with an anticyclonic PV anomaly over SEA. The Fourier decomposition of the PV and meridional wind velocity fields further reveals that the WN4 and WN5 components in the suitable phase aids in forming the ridge over SEA for days with high RSEA. In addition, we find anomalous blocking over the Indian and the South Pacific oceans during SEA heatwaves, which may help to modulate the phase of RRWPs.

Variability in Antarctic surface climatology across regional climate models and reanalysis datasets

Abstract. Regional climate models (RCMs) and reanalysis datasets provide valuable information for assessing the vulnerability of ice shelves to collapse over Antarctica, which is important for future global sea level rise estimates. Within this context, this paper examines variability in snowfall, near-surface air temperature and melt across products from the Met Office Unified Model (MetUM), Regional Atmospheric Climate Model (RACMO) and Modèle Atmosphérique Régional (MAR) RCMs, as well as the ERA-Interim and ERA5 reanalysis datasets. Seasonal and trend decomposition using LOESS (STL) is applied to split the monthly time series at each model grid cell into trend, seasonal and residual components. Significant systematic differences between outputs are shown for all variables in the mean and in the seasonal and residual standard deviations, occurring at both large and fine spatial scales across Antarctica. Results imply that differences in the atmospheric dynamics, parametrisation, tuning and surface schemes between models together contribute more significantly to large-scale variability than differences in the driving data, resolution, domain specification, ice sheet mask, digital elevation model and boundary conditions. Despite significant systematic differences, high temporal correlations are found for snowfall and near-surface air temperature across all products at fine spatial scales. For melt, only moderate correlation exists at fine spatial scales between different RCMs and low correlation between RCM and reanalysis outputs. Root mean square deviations (RMSDs) between all outputs in the monthly time series for each variable are shown to be significant at fine spatial scales relative to the magnitude of annual deviations. Correcting for systematic differences results in significant reductions in RMSDs, suggesting the importance of observations and further development of bias-correction techniques.

A climatological-dynamical analysis of tropopause folds over Southwest Asia in the period of 1989–2018

Tropopause folding is believed to be connected to the development of cyclonic systems in midlatitudes as well as the larger-scale, lower-frequency processes in the lower latitudes. To investigate such connections, a statistical and dynamical analysis of tropopause folds occurred in Southwest Asia is carried out for the period of 1989–2018. Tropopause folds are identified using the Era-Interim reanalysis dataset from the European Centre for Medium-Range Weather Forecasts. The spatial–temporal distributions of tropopause folding show that the frequency of folding is higher in the winter hemisphere than in the summer hemisphere and greater values of the frequency are found mostly within an elongated zonal band which is situated between 20 and 40 degrees latitude. Southwest Asia also has strong positive anomalous values of tropopause folding frequency and achieves the values more than five times the average of the Northern Hemisphere in the summer, especially in the northern latitudes of this region including Afghanistan, Iran and the eastern Mediterranean. This can be attributed mainly to the formation of summer monsoon in the subtropical latitudes of the Indian Ocean. In this regard, the examination of the effects of El Niño and La Niña on the spatial–temporal distributions of tropopause folding reveals that the values of 3-month running average of tropopause folding frequency coincident with La Niña tend to be larger than those with El Nino in both the hemispheres and Southwest Asia. This result is consistent with the previous findings on the tendency for higher occurrence of anticyclonic (cyclonic) baroclinic wave life cycles during La Niña (El Niño). Dynamically, the folds occurred in the study area are associated with the formation of waves at 500 hPa level and subsequently the creation of surface cyclones. In areas of high frequency of folding events, strong meridional shear of the zonal winds and jet stream amplification are observed at 200 hPa level. The analysis of wave activity flux and its divergence for the selected month of June 2015 shows two regions of wave propagation, one with a wave-packet like signature of flux divergence/convergence centers in the upper troposphere and one over the lower troposphere. The upper-tropospheric wave packet ends with an area of flux convergence related with the receipt and decay of Rossby waves, while in the lower troposphere, a flux divergence region as a source of stationary waves associated with the Indian monsoon activity is identified.

A Synoptic Framework for Forecasting the Urban Rainfall Effect Using Composite and K-Means Cluster Analyses

Observational and numerical modeling studies continue to affirm the existence of the “urban rainfall effect” (URE), or a discernible anomaly in warm season precipitation due to urbanization. However, the literature has been lacking a progression towards the predictability of the URE. Atlanta, Georgia has consistently appeared in the literature because of its well-studied urban rainfall anomalies. Using the Multi-sensor Precipitation Estimates (MPE) dataset and the ERA-Interim reanalysis dataset, an 18-year period (2002–2019) is examined. Three similar but distinct methods are used to define urban rainfall days (URDs), or periods when the precipitation in the urbanized areas of Atlanta are greater than the surrounding rural areas. A combination of compositing, wind rose, and k-means cluster analyses are employed to extract the synoptic framework supportive of the URE in Atlanta, Georgia. The synoptic-scale compositing analysis reveals that there are a consistent set of meteorological ingredients that are needed to produce an URD, including weaker-than-average southwesterly-to-northwesterly flow at 700 hPa, copious amounts of moisture throughout the tropospheric column, and a background low-level convergent flow. Composite atmospheric soundings reveal that there is enhanced moisture throughout the tropospheric column on URDs, leading to marginal instability that favors localized convection across the Atlanta metropolitan area. The study also provides clarity on how often the URE is present (roughly 8% of the time) during warm season days across the Atlanta metropolitan area. Taken together, this synoptic framework will aid in the forecasting of the URE in Atlanta and can be easily applied to other cities.

Sensitivity of South America Climate to Positive Extremes of Antarctic Sea Ice.

Global climate change is expected to increasingly affect climate-sensitive sectors of society, such as the economy and environment, with significant impacts on water, energy, agriculture and fisheries. This is the case in South America, whose economy is highly dependent on the agricultural sector. Here, we analyzed the sensitivity of South American climate to positive extremes of Antarctic sea ice (ASI) extent and volume at continental and regional scales. Sensitivity ensemble experiments were conducted with the GFDL-CM2.1 model and compared with the ERA-Interim reanalysis dataset. The results have shown significant impacts on the seasonal regime of precipitation, air temperature and humidity in South America, such as a gradual establishment of the South Atlantic Convergence Zone, the formation of the Upper Tropospheric Cyclonic Vortex, the strengthening of Bolivian High and the presence of a low level cyclonic circulation anomaly over the South Atlantic Subtropical High region which contributed, for instance, to increased precipitation over the Southeastern Brazil. A northward shift of the Intertropical Convergence Zone was initially also a response pattern to the increased ASI. Moreover, the greatest variance of the climatic signal generated from the disturbances applied on the high southern latitudes has occurred in the interseasonal timescale (110-120 days), especially over the Brazilian Amazon and the Southeastern Brazil regions.

Wave trains of 10–30-day meridional wind variations over the North Pacific during summer

AbstractThe present study investigates the intraseasonal oscillations over the North Pacific during summer based on the ERA-Interim reanalysis dataset. It is shown that the main component of intraseasonal variations in meridional wind is dominated by 10–30-day variability. Zonally-oriented wave trains are identified over the North Pacific at this band, with a zonal wavenumber 6. The wave trains exhibit an equivalent-barotropic structure, with the maximum amplitude in the upper troposphere, and are manifested as quasi-stationary Rossby waves with the energy dispersing eastward. The wave trains do not show a phase-locking feature, that is, they have no preferred geographical locations in the zonal direction. Furthermore, energy analyses suggest that the intraseasonal waves gain energy through baroclinic energy conversion, while the barotropic energy conversion plays a negligible role. The present results have implications for better understanding and forecasting weather and climate in North America, since the intraseasonal waves over the North Pacific may act as precursory signals for extreme events occurring over North America.

Improvement in the Prediction of Summer Precipitation in the North China−Hetao Region Using the Tropospheric Temperature Over the Tibetan Plateau in Spring

We investigated the relationship between the spring tropospheric temperature over the Tibetan Plateau (TPT) and summer precipitation in eastern China on an interannual timescale using the monthly mean ERA-Interim reanalysis dataset, the HadISST dataset and the daily mean precipitation dataset for China. We found that there is a significant positive correlation between the spring TPT and summer precipitation in the North China−Hetao region. The relationship is manifested in the context of the East Asia–Pacific pattern teleconnection. In the high spring TPT index years, the geopotential height anomalies over East Asia and the western North Pacific present a negative phase of the East Asia–Pacific pattern teleconnection in the subsequent summer. This circulation pattern is beneficial for the water vapor transport from the western Pacific to inland, which further transport to the North China−Hetao region from the Yangtze River–Yellow rivers region. Anomalous upward motion occurs in the North China–Hetao region, which increases precipitation. The East Asian subtropical westerly jet shifts further north and the South Asian high weakens and shrinks westward. These conditions all favor an increase in precipitation over the North China–Hetao region. The spring TPT plays an important part in the prediction of summer precipitation in the North China−Hetao region. The improvement in the use of the spring TPT to predict summer precipitation in the North China–Hetao region is examined by comparing the prediction equations with and without the prediction factor of the spring TPT on the basis of the sea surface temperatures in key regions. After considering the impact of the spring TPT, the explanatory variance of the prediction equation for precipitation in the North China–Hetao region increases by 17.3%.

Comparison of the Prediction of Indian Monsoon Low Pressure Systems by Subseasonal-to-Seasonal Prediction Models

AbstractThis study analyzes the prediction of Indian monsoon low pressure systems (LPSs) on an extended time scale of 15 days by models of the Subseasonal-to-Seasonal (S2S) prediction project. Using a feature-tracking algorithm, LPSs are identified in 11 S2S models during a common reforecast period of June–September 1999–2010, and then compared with 290 and 281 LPSs tracked in ERA-Interim and MERRA-2 reanalysis datasets. The results show that all S2S models underestimate the frequency of LPSs. They are able to represent transits, genesis, and lysis of LPSs; however, large biases are observed in the Australian Bureau of Meteorology, China Meteorological Administration (CMA), and Hydrometeorological Centre of Russia (HMCR) models. The CMA model exhibits large LPS track position error and the intensity of LPSs is overestimated (underestimated) by most models when verified against ERA-Interim (MERRA-2). The European Centre for Medium-Range Weather Forecasts and Met Office models have the best ensemble spread–error relationship for the track position and intensity, whereas the HMCR model has the worst. Most S2S models are underdispersive—more so for the intensity than the position. We find the influence of errors in the LPS simulation on the pattern of total precipitation biases in all S2S models. In most models, precipitation biases increase with forecast lead time over most of the monsoon core zone. These results demonstrate the potential for S2S models at simulating LPSs, thereby giving the possibility of improved disaster preparedness and water resources planning.

The Impact of the Stratospheric Polar Vortex Shift on the Arctic Oscillation

AbstractUsing the ERA-Interim reanalysis dataset for the time period 1979–2016, we analyzed the influence of the stratospheric polar vortex shift on the Arctic Oscillation (AO) in winter (December–March). The results show that a shift in the stratospheric polar vortex toward the Eurasian continent is favorable for the occurrence of the negative phase of the AO. The duration of the AO events accompanied by the stratospheric polar vortex shift toward the Eurasian continent (AO-shift events) is longer than that of the remaining negative AO events (AO-noshift events), and the intensity of AO-shift events is greater than that of AO-noshift events from day 4 to day 15 of the life cycle of the events. The enhancement in the AO intensity during AO-shift events is likely due to downward extension of the stratospheric northern annular mode (NAM) signals and more poleward-propagating planetary waves in the troposphere and lower stratosphere and their convergence in the mid-high latitudes. Furthermore, the polar vortex shift can lead to changes in the intensity of the three action centers in the AO spatial pattern at 500 hPa. In general, during AO-shift events, the three action centers are stronger than those during AO-noshift events. There is an overall westward shift of the Arctic action center during AO-shift events, which may be closely related to the changes of Greenland blocking frequency.

High-resolution dynamical downscaling of ERA-Interim temperature and precipitation using WRF model for Greece

This study presents the results of high-resolution dynamical downscaling of 5 km on maximum (TX) and minimum (TN) air temperature and precipitation, for Greece, with the Weather Research and Forecasting (WRF) model. The ERA-Interim (ERA-I) reanalysis dataset is used for initial and boundary conditions. The model results (WRF_5) are evaluated against available ground observations for the period 1980–2004 through the calculation of mean climatology, statistical metrics, and distributions of extreme events on daily, monthly and seasonal scales. WRF_5 model captures very well the geographical distribution of TX and TN of the study area, and illustrates finely the seasonal differences. Statistical results for TX (TN) indicate a cold (warm) bias of − 0.6 °C (1 °C) regarding WRF_5 and − 3 °C (0.5 °C) for ERA-I. The efficiency metrics for temperatures showed a highly improved performance of the model compared to reanalysis for all temporal scales investigated. The observed mean annual cycle and inter-annual variability of precipitation are also well represented by model simulation. Although WRF_5 overestimates rainfall during most of the year, the seasonal pattern of WRF_5 presented similar correlation coefficients for all stations with a range of 0.6–0.85, showing a good model ability to simulate the precipitation in Greece. The results reveal the capability of the configured WRF high resolution model to reproduce the main climatological variables of the study area, outperforming the coarse resolution ERA-Interim in a region that is dominated by highly variable topographic characteristics. This is deemed necessary for undertaking any further studies concerning future climate change impacts in various sectors.

Effects of Stationary and Transient Transport of Ozone on the Ozone Valley Over the Tibetan Plateau in Summer

We studied the effects of the stationary and transient transport of ozone in the upper troposphere and lower stratosphere (UTLS) on the ozone valley over the Tibetan Plateau (OVTP) in summer using the daily ERA-Interim reanalysis dataset for the time period 1979–2016. We used the Lorenz circulation decomposition method to separate the stationary and transient transport of ozone into terms related to either the mean flow or eddies. The decrease in the total ozone concentration in summer is associated with the transport of ozone, which, in turn, reinforces the OVTP. The zonal (meridional) transport of ozone, which combines stationary and transient transport, strengthens (weakens) the ozone valley. The stationary zonal (meridional) transport of ozone strengthens (weakens) the ozone valley. The transient zonal (meridional) transport of ozone weakens (strengthens) the ozone valley, but this effect is weaker than that of stationary transport. The mean flow has the dominant role, especially in the stationary component. The effect of eddies on the zonal transient transport of ozone is as strong as that of the mean flow. For stationary transport, the zonal deviation of ozone transported by the zonal mean flow in the zonal (meridional) direction C(O3∗¯ [u]¯)(C(O3∗¯ [v]¯)) dominates total zonal (meridional) change of ozone C(O3¯ u¯)(C(O3¯ v¯)), which strengthens (weakens) the ozone valley. The transient transport of the zonal mean ozone by eddies (C([O3]′u∗′¯)), the zonal deviation of ozone by the zonal mean flow (C(O3∗′[u]′¯)) and the zonal deviation of ozone by eddies (C(O3∗′u∗′¯)) all have a strong effect on the ozone valley. By contrast, the transient transport of the zonal mean ozone by eddies in the meridional direction (C([O3]′v∗′¯)) has a much weaker and the smallest effect. Both the zonal deviation of ozone by the zonal mean flow and by eddies in the meridional direction (C(O3∗′[v]′¯) and C(O3∗′v∗′¯)) have major roles in transient meridional transport, but their roles are the opposite of each other. The contributions of stationary and transient transport to zonal transport are consistent, whereas their contributions to meridional transport are the opposite of each other. The influence of transient transport on the formation and maintenance of OVTP is not negligible.

A new methodology for offshore wind speed assessment integrating Sentinel-1, ERA-Interim and in-situ measurement

Offshore Wind (OW) speed assessment is a key aspect for the development of new wind farms at sea. Satellites can be used to globally obtain ocean and sea distribution, compensating limited in-situ measurements. In this study, a new methodology to estimate the wind’s speed potential is here proposed. Preliminary, Sentinel-1 (S-1) images have been analyzed by means of the Sentinel Application Platform (SNAP) software, extrapolating wind speed data for each cell pixel size of a testing area. Then GIS (Geographic Information System) software has been used to map wind data and find the best pixel location comparing these data with in-situ data. Furthermore, wind speed has been analyzed using the ERA-Interim reanalysis dataset for areas within 11 km and 40 km from the Lillgrund OW farm in the Baltic Sea to better understand wind regimes. Finally, wind speed parameters obtained by S-1 in Sea Surface Water (SSW) with the 10 m standard high have been compared with wind speed recorded by Supervisory Control and Data Acquisition (SCADA) systems of two turbine using wind profile formula. Obtained results show the comparison accuracy of wind speed assessment for each center of the pixels by S-1 satellite images and in-situ (SCADA) measurements. Data actually depends on the distance between the selected center pixel and the location of the turbines. The obtained wind speed differences (0.26 m/s - RMSE = 1.38 and 0.92 m/s - RMSE = 1.82) pinpointed the direct effect of the distance between the selected pixel center and the in-situ measurements location in the S-1 imagery for wind speed potential assessment. Obtained results proved an improvement of the OW assessment accuracy using multiple satellite observations, demonstrating that SAR wind maps can support OW speed sites assessment by introducing observations in different phases of an OW farm project.

Cutoff low over the southeastern Pacific Ocean: a case study

Cutoff lows (COLs) are infrequent events in the tropics that can cause extreme rainfall, flash flooding and landslides in arid areas, such as western South America. In this study, the life cycle of a COL in the southeastern Pacific at the beginning of April 2012 was analysed using the ERA-Interim reanalysis dataset. This paper examines: (1) the precursor flow evolution prior to the COL, its development and dissipation by applying the quasi-geostrophic and vorticity equations; and (2) the influence of the COL in the heavy precipitation events over the western Peruvian Andes. During April 2012, the highest amount of precipitation was recorded in Chosica (850 masl) with 37 mm on 5 April. Days prior to the formation of the COL, a subtropical trough deepened by the amplification of a ridge over the tropical Pacific and the incursion of cold air from medium and low levels into the trough. The strong cyclonic vorticity advection was intensified by a short-wave trough embedded inside a long-wave one that strengthened the system on 5 April 2012. In the dissipation stage, warm vertical advection predominated, resulting in the reabsorption of the COL by a new trough. Understanding the behaviour COL systems is important for reducing the impact of these extreme weather events on lives and infrastructure in densely populated areas.

A Regional Blended Precipitation Dataset over Pakistan Based on Regional Selection of Blending Satellite Precipitation Datasets and the Dynamic Weighted Average Least Squares Algorithm

Substantial uncertainties are associated with satellite precipitation datasets (SPDs), which are further amplified over complex terrain and diverse climate regions. The current study develops a regional blended precipitation dataset (RBPD) over Pakistan from selected SPDs in different regions using a dynamic weighted average least squares (WALS) algorithm from 2007 to 2018 with 0.25° spatial resolution and one-day temporal resolution. Several SPDs, including Global Precipitation Measurement (GPM)-based Integrated Multi-Satellite Retrievals for GPM (IMERG), Tropical Rainfall Measurement Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42-v7, Precipitation Estimates from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), ERA-Interim (reanalysis dataset), SM2RAIN-CCI, and SM2RAIN-ASCAT are evaluated to select appropriate blending SPDs in different climate regions. Six statistical indices, including mean bias (MB), mean absolute error (MAE), unbiased root mean square error (ubRMSE), correlation coefficient (R), Kling–Gupta efficiency (KGE), and Theil’s U coefficient, are used to assess the WALS-RBPD performance over 102 rain gauges (RGs) in Pakistan. The results showed that WALS-RBPD had assigned higher weights to IMERG in the glacial, humid, and arid regions, while SM2RAIN-ASCAT had higher weights across the hyper-arid region. The average weights of IMERG (SM2RAIN-ASCAT) are 29.03% (23.90%), 30.12% (24.19%), 31.30% (27.84%), and 27.65% (32.02%) across glacial, humid, arid, and hyper-arid regions, respectively. IMERG dominated monsoon and pre-monsoon seasons with average weights of 34.87% and 31.70%, while SM2RAIN-ASCAT depicted high performance during post-monsoon and winter seasons with average weights of 37.03% and 38.69%, respectively. Spatial scale evaluation of WALS-RPBD resulted in relatively poorer performance at high altitudes (glacial and humid regions), whereas better performance in plain areas (arid and hyper-arid regions). Moreover, temporal scale performance assessment depicted poorer performance during intense precipitation seasons (monsoon and pre-monsoon) as compared with post-monsoon and winter seasons. Skill scores are used to quantify the improvements of WALS-RBPD against previously developed blended precipitation datasets (BPDs) based on WALS (WALS-BPD), dynamic clustered Bayesian model averaging (DCBA-BPD), and dynamic Bayesian model averaging (DBMA-BPD). On the one hand, skill scores show relatively low improvements of WALS-RBPD against WALS-BPD, where maximum improvements are observed in glacial (humid) regions with skill scores of 29.89% (28.69%) in MAE, 27.25% (23.89%) in ubRMSE, and 24.37% (28.95%) in MB. On the other hand, the highest improvements are observed against DBMA-BPD with average improvements across glacial (humid) regions of 39.74% (36.93%), 38.27% (33.06%), and 39.16% (30.47%) in MB, MAE, and ubRMSE, respectively. It is recommended that the development of RBPDs can be a potential alternative for data-scarce regions and areas with complex topography.

Statistical analysis of Central Asian vortices and their influence on precipitation in Xinjiang

Central Asian vortices (CAVs) are synoptic-scale systems affecting the weather over Central Asia and downstream regions. We established an historical dataset of CAVs for the time period 1980–2017 based on an improved objective identification and tracking method and the ERA-Interim reanalysis dataset. Based on the CAV and 6-h precipitation datasets, we analyzed the climatological features of 389 CAVs and carried out a composite analysis of the CAVs influencing precipitation in Xinjiang. The CAVs tended to move eastward and had two main high-frequency centers over the Central Asia. The occurrence of CAVs peaks in summer and there is a considerable interannual variability. Most CAVs have a lifetime of two to three days and a spatial size of about 1100 km. The CAV-related precipitation in Xinjiang is mainly located in the Tianshan mountains. The precipitation in the western part of southern Xinjiang in the warm seasons is more sensitive to CAVs. There is a significant convergence of moisture in the southeast quadrant of the CAVs influencing Xinjiang, along with strong divergence in the upper level and associated ascending motion, which both favor precipitation.