Search Results (314)

Large-scale windstorms represent an important atmospheric hazard in the Northeastern US (NE) and are associated with substantial socioeconomic losses. Regional simulations performed with the Weather Research and Forecasting (WRF) model using lateral boundary conditions from three Earth System Models (ESMs: Geophysical Fluid Dynamics Laboratory (GFDL), Hadley Centre Global Environment Model (HadGEM) and Max Planck Institute (MPI)) are used to quantify possible future changes in windstorm characteristics and/or changes in the parent cyclone types responsible for windstorms. WRF nested within MPI ESM best represents important aspects of historical windstorms and the cyclone types responsible for generating windstorms compared with a reference simulation performed with the ERA-Interim reanalysis for the historical climate. The spatial scale and frequency of the largest windstorms in each simulation defined using the greatest extent of exceedance of local 99.9th percentile wind speeds (U > U₉₉₉) plus 50-year return period wind speeds (U_50,RP) do not exhibit secular trends. Projections of extreme wind speeds and windstorm intensity/frequency/geolocation and dominant parent cyclone type associated with windstorms vary markedly across the simulations. Only the MPI nested simulations indicate statistically significant differences in windstorm spatial scale, frequency and intensity over the NE in the future and historical periods. This model chain, which also exhibits the highest fidelity in the historical climate, yields evidence of future increases in 99.9th percentile 10 m height wind speeds, the frequency of simultaneous U > U₉₉₉ over a substantial fraction (5–25%) of the NE and the frequency of maximum wind speeds above 22.5 ms⁻¹. These geophysical changes, coupled with a projected doubling of population, leads to a projected tripling of a socioeconomic loss index, and hence risk to human systems, from future windstorms. Full article

The continental United States is a global hotspot of severe thunderstorms and therefore is particularly vulnerable to social and economic damages from high-impact severe convective weather (SCW), such as tornadoes, thunderstorm winds, and large hail. However, our knowledge of the spatiotemporal climatology and variability of SCW occurrence is still lacking, and the potential change in SCW frequency and intensity in response to anthropogenic climate warming is highly uncertain due to deficient and sparse historical records and the global and regional climate model’s inability to resolve thunderstorms. This study investigates SCW in the Central and Eastern United States in spring and early summer for the current and future warmed climate using two multi-year continental-scale convection-permitting Weather Research and Forecasting (WRF) model simulations. The pair of simulations consist of a retrospective simulation, which downscales the ERA-Interim reanalysis during October 2000–September 2013, and a future climate sensitivity simulation based on the perturbed reanalysis-derived boundary conditions with the CMIP5 ensemble-mean high-end emission scenario climate change. A proxy based on composite reflectivity and updraft helicity threshold is applied to infer the simulated SCW occurrence. Results indicate that the retrospective simulation captures reasonably well the spatial distributions and seasonal variations of the observed SCW events, with an exception of an overestimate along the Atlantic and Gulf coast. In a warmer-moister future, most regions experience intensified SCW activity, most notably in the early-middle spring, with the largest percentage increase in the foothills and higher latitudes. In addition, a shift of simulated radar reflectivity toward higher values, in association with the significant thermodynamic environmental response to climatic warming, potentially increases the SCW severity and resultant damage. Full article

The Global Precipitation Measurement Mission (GPM) improved spaceborne precipitation data. The GPM dual-frequency precipitation radar (DPR) provides information on total precipitation (TP), snowfall precipitation (SF) and snowfall flags (surface snowfall flag (SSF) and phase near surface (PNS)), among other variables. Especially snowfall data were hardly validated. This study compares GPM DPR TP, SF and snowfall flags on the Tibetan Plateau (TiP) against TP and SF from six well-known model-based data sets used as ground truth: ERA 5, ERA 5 land, ERA Interim, MERRA 2, JRA 55 and HAR V2. The reanalysis data were checked for consistency. The results show overall high agreement in the cross-correlation with each other. The reanalysis data were compared to the GPM DPR snowfall flags, TP and SF. The intercomparison performs poorly for the GPM DPR snowfall flags (HSS = 0.06 for TP, HSS = 0.23 for SF), TP (HSS = 0.13) and SF (HSS = 0.31). Some studies proved temporal or spatial mismatches between spaceborne measurements and other data. We tested whether increasing the time lag of the reanalysis data (+/−three hours) or including the GPM DPR neighbor pixels (3 × 3 pixel window) improves the results. The intercomparison with the GPM DPR snowfall flags using the temporal adjustment improved the results significantly (HSS = 0.21 for TP, HSS = 0.41 for SF), whereas the spatial adjustment resulted only in small improvements (HSS = 0.12 for TP, HSS = 0.29 for SF). The intercomparison of the GPM DPR TP and SF was improved by temporal (HSS = 0.3 for TP, HSS = 0.48 for SF) and spatial adjustment (HSS = 0.35 for TP, HSS = 0.59 for SF). Full article

Assessing the daily water requirements of crops and understanding the severity of drought necessitates precise estimation of potential evapotranspiration (PET), particularly in regions with arid climates such as Egypt. In the present study, the RegCM4 regional climate model was used to investigate the sensitivity of the PET of Egypt to two land surface schemes and boundary layer parameterizations. The land surface schemes are the Biosphere Atmosphere Transfer System (BATS) and the Community Land Model version 4.5 (CLM45). The boundary layer schemes considered are the HOLTSLAG (HOLT) and University of Washington (UW). To accomplish this task, four 32-year simulations were conducted spanning from 1979 to 2010, with the first two years considered as spin up. The ERA-Interim reanalysis was used to downscale the RegCM4 model. The simulated PET was evaluated with respect to the high-resolution ERA5-land PET-based product (hPET). The results showed that the BATS showed a bias of −0.8 to −1.8 mm day⁻¹, while the CLM45 showed a bias of −0.8 to −3 mm day⁻¹. Also, fine-tuning the coefficient of the daily mean air temperature succeeded in reducing the PET bias. Additionally, the UW had a lower PET bias than that noted in HOLT. To further reduce the PET bias, the linear-scaling (LS) bias-correction method was used. The LS showed its potential skills in reducing the mean bias of the PET from −2.2 to +0.4 mm day⁻¹ in the evaluation period and to ±0.2 mm day⁻¹ in the validation period. Furthermore, the added value of the LS was confirmed concerning the climatological annual cycle in different locations representing different climate zones of Egypt. In conclusion, accurate estimation of the PET can be ensured using the BATS, the UW schemes, and the LS technique in the present climate or under different warming scenarios. Full article

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. Full article

This study aimed to examine the spatio-temporal variations in the atmospheric boundary layer height (ABLH) over the Tarim Basin (TB). Monthly ABLH data from the ERA-Interim dataset from January 1979 to December 2018 were used. Periodicity analysis and the Mann–Kendall Abrupt Changes test were employed to identify the change cycle and abrupt change year of the boundary layer height. The Empirical Orthogonal Function (EOF) method was utilized to determine the spatial distribution of the boundary layer height, and the RF method was used to establish the relationship between the ABLH and influencing factors. The results demonstrated that the highest values of ABLH (over 1900 m) were observed in the middle parts of the study area in June, and the ABLH exhibited a significant increase over the TB throughout the study period. Abrupt changes in the ABLH were also identified in 2004, as well as in 2-, 5-, 9-, and 15-year changing cycles. The first EOF ABLH mode indicated that the middle and northeast regions are relatively high ABLH areas within the study area. Additionally, the monthly variations in ABLH show a moderately positive correlation with air temperature, while exhibiting a negative correlation with air pressure and relative humidity. Full article

Climate change (CC) impacts on hydrology pose significant global concerns due to their effects on water availability, thereby impacting various human activities reliant on this essential resource. This study assesses the influence of CC on the water supply in the Angostura-Bolivia basin. We employed the RegCM4 system, which develops its own regional climate models (RCMs) tailored to the Angostura basin using specific convective schemes, diverging from reliance on pre-existing RCMs, like those provided by CORDEX. Methodologically, the study involves hydrometeorological data collection and analysis, utilizing dynamic and statistical downscaling methods to refine the RCMs derived from ERA-Interim reanalysis data. Subsequently, precipitation and temperature projections are generated under CC scenarios (RCP 4.5 and RCP 8.5) for both near (2045–2055) and far (2065–2075) future periods, compared to the historical period (1981–2010). The final stage employs the HydroBID system to project future runoff, considering both perturbed and unperturbed hydrometeorological data under CC effects. The analysis of flow duration curves for 50%, 75%, and 90% exceedance probabilities reveals a significant reduction in flows across all scenarios, indicating a noteworthy impact on water availability. These findings underscore the urgency of comprehending and adapting to CC on hydrology, emphasizing the critical importance of sustainable water resource management amidst evolving climatic conditions. Full article

To improve the simulation performance of the RegCM4 model in climate simulations over the Yangtze River Basin (YRB), it is essential to determine the optimal cumulus convection and land surface process schemes from the numerous physical parameterization options within RegCM4. In this study, we selected five cumulus convection schemes (Kuo, Grell, Emanuel, Tiedtke, and Kain–Fritsch) and three land surface process schemes (BATS, CLM3.5, and CLM4.5) to configure 72 mixed schemes. Four years of short-term simulations (1990–1993) with a horizontal resolution of 50 km were conducted using ERA-Interim as the initial and boundary conditions for the 72 schemes. The climate simulation performance of all schemes in the YRB was comprehensively evaluated using a multi-criteria scoring approach. The results indicate that among the selected cumulus convection schemes, the Kain–Fritsch scheme, applied to both ocean and land, demonstrates optimal performance in simulating precipitation over the YRB, with spatial correlation coefficients between simulated and observed annual precipitation around 0.3. Compared to the Community Land Models (CLM3.5 and CLM4.5), BATS exhibits superior capabilities in reproducing the temperature features of the region, with spatial correlation coefficients between simulated and observed values typically exceeding 0.99 and standard deviations within 1.25 °C. Under the optimal KF scheme, the simulated soil moisture in the YRB using CLMs is notably drier, ranging from −7.79 to −8.39 kg/m², compared to that achieved with BATS. The findings provide a localized reference for the parameterization schemes of RegCM4 in the YRB. Full article

Satellite precipitation products (SPPs) are undeniably subject to uncertainty due to retrieval algorithms and sampling issues. Many research efforts have concentrated on merging SPPs to create high-quality merged precipitation datasets (MPDs) in order to reduce these uncertainties. This study investigates the efficacy of dynamically weighted MPDs in contrast to those using static weights. The analysis focuses on comparing MPDs generated using the “dynamic clustered Bayesian averaging (DCBA)” approach with those utilizing the “regional principal component analysis (RPCA)” under fixed-weight conditions. These MPDs were merged from SPPs and reanalysis precipitation data, including TRMM (Tropical Rainfall Measurement Mission) Multi-satellite Precipitation Analysis (TMPA) 3B42V7, PERSIANN-CDR, CMORPH, and the ERA-Interim reanalysis precipitation data. The performance of these datasets was evaluated in Pakistan’s diverse climatic zones—glacial, humid, arid, and hyper-arid—employing data from 102 rain gauge stations. The effectiveness of the DCBA model was quantified using Theil’s U statistic, demonstrating its superiority over the RPCA model and other individual merging methods in the study area The comparative performances of DCBA and RPCA in these regions, as measured by Theil’s U, are 0.49 to 0.53, 0.38 to 0.45, 0.37 to 0.42, and 0.36 to 0.43 in glacial, humid, arid, and hyper-arid zones, respectively. The evaluation of DCBA and RPCA compared with SPPs at different elevations showed poorer performance at high altitudes (>4000 m). The comparison of MPDs with the best performance of SPP (i.e., TMPA) showed significant improvement of DCBA even at altitudes above 4000 m. The improvements are reported as 49.83% for mean absolute error (MAE), 42.31% for root-mean-square error (RMSE), 27.94% for correlation coefficient (CC), 40.15% for standard deviation (SD), and 13.21% for Theil’s U. Relatively smaller improvements are observed for RPCA at 13.04%, 1.56%, 10.91%, 1.67%, and 5.66% in the above indices, respectively. Overall, this study demonstrated the superiority of DCBA over RPCA with static weight. Therefore, it is strongly recommended to use dynamic variation of weights in the development of MPDs. Full article

The analysis of spatial and temporal variability in the number of non-Gaussian extreme anomalies of climatic parameters was carried out for both the initial time series and synoptic variability in the troposphere of the Northern Hemisphere over the period 1979–2018, based on ERA-Interim reanalysis data. There are predominantly three types of empirical distribution densities at 850 hPa, each characterizing the processes of advective and convective heat transfer. At the beginning of the 21st century, compared to the end of the 20th century, there was an increase in the number of anomalies in vertical wind speed and specific humidity for the Northern Hemisphere. Additionally, there is an increase in the number of zonal wind speed anomalies in the low and middle latitudes. Regions with the maximum number of anomalies are primarily located over the continents, while for vertical wind speed anomalies, they are predominantly over the oceans. The application of R/S analysis and multifractal analysis has established that the identified tendencies (which are persistent processes) will continue in the identified regions. The time series of non-Gaussian anomalies (both initial and synoptic scales) exhibit a long-term memory of approximately four years, and synoptic extreme anomalies were found to be more predictable. Full article

Accurate information on potential evapotranspiration (PET) is mandatory for arid regions (such as Egypt) to assess crop water requirements. Such precision is limited by the dynamical downscaling options and the physical settings used in regional climate models (like the RegCM4). To address these issues, four simulations were run as part of the current study. The first two simulations take direct (DIR) and one-way nesting (NEST) into account, while the other two use two boundary layer techniques (HOLTSLAG; HOLT) and (the University of Washington; UW). All simulations were driven via an ERA-Interim reanalysis of 1.5 degrees. The simulated PET was evaluated for the high-resolution reanalysis gridded derived product of ERA5-Land (hereafter ERA5). The findings revealed no discernible difference between DIR and NEST regarding global incident solar radiation (RSDS). Also, NEST had a higher mean air temperature (TMP) than DIR. Additionally, UW had a lower TMP than HOLT, but switching between HOLT and UW did not significantly impact the simulated RSDS. Concerning PET, it is neither affected by DIR and NEST nor HOLT and UW. Such results suggest that the RSDS is the main driver in controlling PET variability, followed by TMP. Therefore, by using the DIR downscaling option and UW boundary layer scheme throughout the period of 1990–2020, as recommended by the World Meteorological Organization, the RegCM4 can be used to develop a regional PET map of Egypt. Full article

Satellite and reanalysis precipitation estimates of high quality are widely used for hydrological modeling, especially in ungauged or data-scarce regions. To improve flood simulations by merging different precipitation inputs or directly merging streamflow outputs, this study comprehensively evaluates the accuracy and hydrological utility of nine corrected and uncorrected precipitation products (TMPA-3B42V7, TMPA-3B42RT, IMERG-cal, IMERG-uncal, ERA5, ERA-Interim, GSMaP, GSMaP-RNL, and PERSIANN-CCS) from 2006 to 2018 on a daily timescale using the Coupled Routing and Excess Storage (CREST) hydrological model in two flood-prone tributaries, the Beijiang and Dongjiang Rivers, of the Pearl River Basin, China. The results indicate that (1) all the corrected precipitation products had better performance (higher CC, CSI, KGE’, and NSCE values) than the uncorrected ones, particularly in the Beijiang River, which has a larger drainage area; (2) after re-calibration under Scenario II, the two daily merged precipitation products (NSCE values: 0.73–0.87 and 0.69–0.82 over the Beijiang and Dongjiang Rivers, respectively) outperformed their original members for hydrological modeling in terms of BIAS and RMSE values; (3) in Scenario III, four evaluation metrics illustrated that merging multi-source streamflow simulations achieved better performance in streamflow simulation than merging multi-source precipitation products; and (4) under increasing flood levels, almost all the performances of streamflow simulations were reduced, and the two merging schemes had a similar performance. These findings will provide valuable information for improving flood simulations and will also be useful for further hydrometeorological applications of remote sensing data. Full article

Dust storms are one of the most frequent weather phenomena in the Middle East and North Africa (MENA) region. Therefore, the daily forecast of dust events is vital for different sectors. Many regional models can be used to forecast atmospheric dust storms. Here, the ICTP regional climate model (RegCM4) was used to simulate atmospheric dust emission, transportation, and deposition, using the optical properties of dust particles, over the MENA region. In the current work, the dust optical depth (DOD) obtained using RegCM4 was compared with the aerosol optical depth (AOD) measured by AERONET at different stations and by MODIS. In the first experiment, two datasets (NCEP/GFS and ERA-Interim) for the meteorological initial and boundary conditions have been used, whereas in the second experiment, GFS with two dust emission schemes have been used. In the last experiment, GFS with two values of the erodibility factor (1 and 0.5) have been used. The RegCM4 forecast with GFS and the first dust emission scheme provided higher values of DOD than AERONET. However, when using the reanalysis data of ERA-Interim or the second dust emission scheme, there was no significant difference, but the erodibility factor decreases led to a reduction in the overestimated values. Full article

Daily maximum air temperature (TMX) and daily minimum air temperature (TMN) are sensitive to the soil moisture status and land surface parameterization. However, this point has not been addressed in arid regions (e.g., Egypt). To address this issue, four 13-year simulations were conducted within the framework of the regional climate model (RegCM4). The first two considered the soil moisture status (bare soil versus global satellite soil moisture product; ESACCI). The other two considered the sensitivity to the two land surface schemes coupled to the RegCM4: Biosphere Atmosphere Transfer System (BATS) and version 4.5 of the community land model (CLM45). In all simulations, the RegCM4 was downscaled using the Era-Interim reanalysis with 25 km grid spacing. The simulated TMX and TMN were evaluated with respect to the Climate Research Unit (CRU) and station data. The results showed that switching from bare soil to ESACCI has a considerable influence on the simulated TMX and TMN. Compared to the CRU, the CLM45 outperforms the BATS on the coasts of the Mediterranean Sea and Red Sea (in terms of the TMX) and in the inland regions (in terms of the TMN). When compared with the station data, the behavior of the BATS/CLM45 varies with the location and month. Despite the noted biases, the RegCM4 can be recommended for future studies concerning the seasonal forecast or climate change of Egypt when it is configured with the CLM45 land surface model and initialized with the ESACCI satellite product. Full article

This study estimates the radiative forcing by biomass burning and dust aerosols over the Indian subcontinent, with emphasis on the Indo-Gangetic Plains (IGP) during the period from January 2021 to April 2021, based on multiple satellite and reanalysis datasets. In this respect, we used retrievals from the Moderate Resolution Spectroradiometer (MODIS) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) system, as well as reanalysis data from the Goddard Earth Observing System, version 5 (GEOS-5), the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), the Copernicus Atmosphere Monitoring Service (CAMS), and ERA-Interim. According to the MERRA-2 and the CAMS, the highest black carbon (BC) concentrations in January 2021 were 7–8 µg m⁻³, which were significantly lower than measurements performed in main cities along the IGP, such as Patiala, Delhi, and Kanpur. The meteorological data analysis accompanied by the CALIPSO lidar measurements showed that the vertical distribution of total attenuated backscatter (TAB) could reach altitudes of up to ~4–5 km and could be transported over the central Himalayan region. The spatial-averaged daily aerosol radiative forcing (ARF) values over the Indian subcontinent from January 2021 to April 2021 were found to range from −51.40 to −6.08 W m⁻² (mean of −22.02 ± 9.19 W m⁻²), while on a monthly basis, the ARF values varied widely, from −146.24 to −1.63 W m⁻² (mean of −45.56 ± 22.85 W m⁻²) over different parts of the study region. Furthermore, the spatial-averaged daily BC radiative forcing ranged from −2.23 to −0.35 (−1.01 ± 0.40 W m⁻²), while it varied from −15.29 to −0.31 W m⁻² (−2.46 ± 2.32 W m⁻²) over different regions of southern Asia, indicating a rather small contribution to the total aerosol radiative effect and a large presence of highly scattering aerosols. Our findings highlight the importance of growing biomass burning, in light of recent climate change and the rapid decline in air quality over North India and the Indian Ocean. Full article