Meteorology and Atmospheric Physics最新文献

The main functions of climate normals are twofold. They offer a reference point for evaluating recent or ongoing observations and form the basis for various climate datasets that rely on anomalies. Additionally, they are frequently employed to predict the probable conditions that one might encounter in a specific area. The World Meteorological Organization (WMO) advises regularly reviewing climate normals every decade to keep up with the evolving climate. Atmospheric Science and Meteorological Research Center (ASMERC) is proud to release “Iran Climate Normals” for the periods of 1981–2010 and 1991–2020 including a suite of monthly and annual statistics that are based on temperature, precipitation, sea-level pressure, vapor pressure, station-level pressure, snow-depth, wind speed, visibility, soil temperature, relative humidity, dew point, and cloud amount measurements. This study documents the procedures used for quality control, homogenization of daily observations, and calculation of normal values. For each station and each parameter, the results of the outliers due to the error and the homogeneity assessment are reported. Out of all the parameters, the soil temperature has the highest error percentage. However, this does not necessarily imply that it has the most measurement errors; it could be due to the ease of detecting errors for this specific parameter. Of the 143 stations, 56 had a breakpoint recorded in two parameters or more at a specific point in time. According to the analysis of the temperature and precipitation parameters, (a) the new normal of mean, maximum, and minimum temperatures are 0.47, 0.5, and 0.6 °C above the 1981–2010 period; (b) the normal annual precipitation has increased by an average of 5.4 mm in 1991–2020 compared to 1981–2010; (c) comparing the two periods, the changes in precipitation normals vary in different parts of Iran and different months, while the temperature normals increase in all stations across Iran except for four stations (Gorgan, Kerman, Shiraz, Bandar-e Lengeh); (d) changes in the fourth quintile of monthly precipitation are more than average, and minimum temperature changes are higher than maximum and mean temperatures; and (e) generally, the latter period is characterized by a warmer climate almost across Iran, wetter conditions over the Zagros mountain range and the western part of the Caspian Sea coasts, and drier conditions over the east, center, and west of Iran.

Heat waves are prolonged periods of excessively hot weather, which can have significant impacts on human health, agriculture, and the environment. Climate change has been linked to an increase in the frequency, intensity, and duration of heat waves. As the global average temperature rises, heat waves are becoming more common and more severe. The Arabian Peninsula is warming at a faster rate as compared to the globe in the recent decades. In this paper, the mild, moderate, severe, and extreme heat waves defined by 85th, 90th, 95th and 99th percentile, respectively, are analyzed over Saudi Arabia using historical daily maximum and minimum temperature observations for the period 1985–2021. The large number of mild heat waves are observed all over Saudi Arabia while extreme heat waves are dominant in the northwestern region. Moderate and severe heat waves are observed less in both the Red Sea and the Arabian Gulf coastal regions. The heat waves are intense in the northern and central areas as compared to other regions of the country. Heat wave frequency, intensity and length in Saudi Arabia are in increasing trends, along with the increase in the heat wave season length. Heat wave frequency and intensity are largely observed during the ENSO La Nina and neutral phases along with NAO negative phase as well as IOD negative and neutral phases. However, further investigation is required to see the occurrence of heat waves in different climate zones over Saudi Arabia at various seasons and their teleconnection to large-scale circulations.

Raindrop size distribution (DSD) plays a significant role in understanding the microphysical process of rainfall and the quantitative precipitation estimation (QPE) in hydrology, especially in urban environments which has spatial and temporal variability. In this study, the seasonal variation in DSD and its response to cloud regimes over two contrasting coastal sites (i.e. Kolkata (22.58° N, 88.45° E) and Trivandrum (8.43° N, 76.98° E) of India obtained using laser precipitation monitor (LPM) disdrometer for more than 2 years are investigated. The results show a significant difference in DSD spectra between Kolkata and Trivandrum. It is observed that the smaller-size (< 0.5 mm) particles are more dominant over Trivandrum than at Kolkata. During the monsoon, larger raindrops (D > 2 mm) dominate over Kolkata when compared with Trivandrum and clear separations in DSD were observed in the pre-monsoon season. The percentage contribution of the rain types to the total rainfall duration over Kolkata (Trivandrum) is found to be about 74.13% (80.50%), 18.97% (15.35%) and 6.98% (4.13%) for stratiform, transition and convective, respectively. In the convective rain, the smaller (mid-size, 1 < D < 3 mm and large, D > 3 mm) drops concentrations are higher (lower) over Trivandrum, while mid-size and larger (smaller, D < 0.5 mm) drops are higher (lower) over Kolkata. The convective rains are dominated by continental/maritime and maritime over Kolkata and Trivandrum, respectively. As the rain rate increases, the DSD spectra have larger widths with peaks around diameter D ~ 0.5 mm over both the locations. Further, the empirical relations between reflectivity (Z) and rain rate (R) were established, which are found to be different for different rain types. In each rain type, the Z-R relationship over Kolkata (Trivandrum) is Z = 56.4*R^1.94 (Z = 21.3*R^2.18), Z = 118.8*R^1.89 (Z = 106.4*R^1.83), and Z = 388.0*R^1.54 (Z = 303.1*R^1.38) for convective, transition and stratiform rains, respectively. These results clearly indicate that the two locations are dominated by different cloud systems and microphysical processes. Therefore, the present results are expected to provide a better understanding of regional DSD variability and Z-R relationship with seasons, rain types and cloud microphysical processes, which is the significance of the present study.

This study investigates the trend in the projected rainfall and temperature over undivided Sudan and its major cities of political, trade, and agricultural significance under two different Representative Concentration Pathways (RCPs; RCP2.6 and RCP8.5). Available high-resolution datasets from the Coordinated Regional Climate Downscaling Experiment- Coordinated Output for Regional Evaluations (CORDEX-CORE) at a resolution of 25 km along with their ensemble are considered. The study analyzes projected climate conditions, with a specific emphasis on the near future (2036–2060) and far future (2071–2095). The rainfall distribution is projected to decline across South Sudan (undivided Sudan) under RCP2.6 (RCP8.5). The projected temperature is significantly increasing while rainfall is decreasing across all cities, with these trends being more pronounced under the RCP8.5 scenario. These changes could potentially result in various climate extremes such as severe heatwaves, droughts, and wildfires, which could have significant impacts on the ecosystems, agriculture, public health and ultimately, the livelihood and socio-economic condition of the people. The findings of the study will assist the governments, local administration and town planners in formulating short-term and long-term strategies for adaptation and mitigation, aimed at reducing the impacts of climate change. The study suggests specific measures to address the extreme heat and water deficit at the local scale, hence making it a valuable policy document for addressing the changing climate in undivided Sudan.

This study examines the combined influence of El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on Upper Troposphere Lower Stratosphere (UTLS) ozone variability. The investigation employs data from the Microwave Limb Sounder (MLS) aboard the Aura Satellite and the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis, spanning the period 2005–2020 across tropical latitudes (20º N–20º S). Three specific events were chosen for analysis: a strong La Niña event in 2010, the co-occurrence of El Niño and moderate IOD in 2015, and a robust IOD event in 2019. During years marked by the simultaneous occurrence of ENSO and IOD events, the UTLS (100 hPa altitude is considered for the present study. 82 hPa is the altitude just above the tropopause, therefore also shown in the results) ozone mixing ratio demonstrates a decline in absolute values. The Quasi-biennial Oscillation (QBO) was also investigated, revealing a synchronized variation with the ozone anomaly in the UTLS region. Furthermore, the calculated eddy heat flux, utilized as a proxy for the Brewer–Dobson Circulation (BDC), aligns with the UTLS ozone anomalies, indicating a positive (negative) anomaly during periods of intense tropical downwelling (upwelling). To quantitatively elucidate the contributions of ENSO, IOD, and QBO to the observed ozone anomaly, a multivariate linear regression analysis was executed utilizing the least square method. The findings underscore that a notable fraction—about one-fourth of the observed UTLS ozone anomaly within the study timeframe (2005–2020) can be attributed collectively to ENSO, IOD, and QBO. This preliminary exploration underscores the substantial role played by large-scale climate drivers emanating from the Pacific and Indian oceans in shaping UTLS ozone distribution. These insights emphasize the significance of considering these climatic influences when examining the intricate dynamics and variability of UTLS ozone patterns.

Abstract

An accurate quantification of fluxes from heterogeneous sites and further bifurcation into contributing homogeneous fluxes is an active field of research. Among such sites, fragmented croplands with varying surface roughness characteristics pose formidable challenges for footprint analysis. We conducted two flux monitoring experiments in fragmented croplands characterized by two dissimilar surfaces with objectives to: (i) evaluate the performance of two analytical footprint models in heterogeneous canopy considering aggregated roughness parameters and (ii) analyze the contribution of fluxes from individual surfaces under changing wind speed. A set of three eddy covariance (EC) towers (one each capturing the homogenous fluxes from individual surfaces and a third, high tower capturing the heterogeneous mixed fluxes) was used for method validation. High-quality EC fluxes that fulfill stationarity and internal turbulence tests were analyzed considering daytime, unstable conditions. In the first experiment, source area contribution from a surface is gradually reduced by progressive cut, and its effect on high-tower flux measurements is analyzed. Two footprint models (Kormann and Meixner ‘KM’; analytical solution to Lagrangian model ‘FFP’) with modified surface roughness parameters were applied under changing source area contributions. FFP model has consistently over predicted the footprints (RMSE_FFP = 0.31 m⁻¹, PBIAS_FFP = 19.00), whereas KM model prediction was gradually changed from over prediction to under prediction towards higher upwind distances (RMSE_KM = 0.02 m⁻¹, PBIAS_KM = 8.50). Sensitivity analysis revealed that the models are more sensitive to turbulent conditions than surface characteristics. This motivated to conduct the second experiment, where the fractional contribution of individual surfaces (α and β) to the heterogeneous fluxes measured by the high tower (T3) was estimated using the principle of superposition (FT3 = α FT1 + β FT2). Results showed that α and β are dynamic during daylight hours and strongly depend on mean wind speed (U) and friction velocity (u*). The contribution of fluxes from adjoining fields [1 − (α + β)] is significant beyond 80% isopleth. Our findings provide guidelines for future analysis of fluxes in heterogeneous, fragmented croplands.

This paper presents a first-time satellite-based air mass analysis over the Indian region using Indian National SATellite System (INSAT)-3DR sounder data. The Indian region is characterized by circulations and air mass fronts which have an influential role in deciding the synoptic weather. Usually, air mass analysis is carried out using radiosonde and atmospheric model-based reanalysis data. Both these datasets have intrinsic limitations due to sparse observations and other error sources. The present study is carried out using meteorologically significant satellite-derived 850 hPa level mixing ratio, optical depth, and equivalent potential temperature. The study elicits relative movements and mixing of different air masses during different seasons over the Indian region. The air mass features are well represented by mixing ratio and optical depth compared to potential temperature. The study brings forth prominent interacting air masses and their relative abundance during different seasons. The statistical analysis of air masses during different seasons at 850 hPa estimates the average values of physical attributes concerning different air masses. From the case analysis of air masses, at 850 hPa, a dry pool of mixing ratio is observed during the pre-monsoon (April–May) months. The analysis suggests that the reason for the formation of dry pool over Bay of Bengal and Arabian Sea is frequent anticyclonic formation during the period. The present study limelights the potential of satellite-derived mixing ratio profiles to understand the weather features associated with air mass interactions over the Indian region.

The nonlinear scaling of meteorological processes is an issue of much interest. The objectives of the present work were (a) to investigate cross-correlations between pairs of meteorological time series using different resolutions and (b) to explore the long-range cross-correlations through different scaling exponents. We used 13 years of daily records of rainfall, relative humidity, cloudiness and vapor pressure ranging from January 1st 1996 to December 31st 2009. Data sets were compiled from Veguita agro-meteorological station at Granma province, Cuba. Detrended cross-correlation analysis, multiscale sample entropy, Lévy-stable laws and Hurst–Kolmogorov dynamics were the main methodological and theoretical tools. The detrended cross-correlation coefficient showed significant cross-correlation between rainfall, relative humidity, cloudiness and actual vapor pressure at all investigated time scales. The individual Hurst exponents were in the range 0.62 ≤ H ≤ 0.72 which is consistent with long-range correlated patterns. Bivariate Hurst exponents (H_xy) were larger than the average exponents of the separate processes (H_x and H_y, respectively). The Hurst–Kolmogorov exponents estimated from the climacograms were in the range 0.6 ≤ H ≤ 0.7 (0.603 ≤ β ≤ 0.798) consistent with the values estimated from detrended fluctuation analysis. Each pair of meteorological variables fitted reasonably well bistable distributions with approximately the same Lévy index (α ≅ 0.736). Hurst–Kolmogorov and infinite variance processes are important drivers of the atmospheric dynamics which can explain the persistence of extreme events (droughts) usually observed in the studied region. The multivariate multiscale sample entropy method and multivariate stable distributions could be valuable candidates for describing daily atmospheric processes.

The development, rate, and duration of extreme rainfall events over a region depend on the coexistence and strength of multiple atmospheric physical conditions. Then, understanding the synoptic and cloud-scale aspects is a continuous, crucial integrated task between universities and operational centers aiming for early warning and risk management. This study first evaluates the large-scale atmospheric circulation, instability behavior, and moisture parameters before and after the start of rainfall. It also investigates the dynamic triggering for an extreme rainfall event in Rio de Janeiro between April 08th and 09th, 2019. Secondly, this study intended to examine the microphysics cloud aspects using data from the Geostationary Operational Environmental Satellite (GOES-16). From monthly records and the 99th percentile of accumulated daily rainfall, it was possible to highlight the spatial rainfall dependence on seasonal and topography with higher rainfall values recorded in the south portion of the city of Rio de Janeiro. From the large-scale synoptic aspects, concomitant circulations related to upper, middle, and lower atmospheric levels creating a dynamic vertical structure favorable to convective development were verified over southeastern Brazil. The thermodynamic parameters showed different characteristics before and after rainfall started, suggesting multi-parameters' importance as so-called "instability ingredients" for evaluating the atmospheric potential for clouds and rainfall development. The velocity divergence in upper atmospheric levels was a determinant dynamic forcing for deep convection evolution. Lastly, regarding the wind circulations, northwest winds before precipitation and a change in wind direction were related to the region's frontal systems passage. The cloud microphysics aspects showed that the channel differences approach showed that monitoring top cloud glaciation, vertical development, and particle size are indicators of heavy rainfall when the cloud top offering considerable vertical growth was a helpful tool to identify regions with huge potential to develop heavy rain.

The Advanced Research Weather Research and Forecasting (WRF-ARW) model was used to simulate the downscale evolving atmospheric dynamical processes conducive to the intensification and propagation of the Tubbs Fire (2017). This wildfire impacted Napa and Sonoma Counties, California, spreading quickly and erratically through complex mountainous terrain due in large part to downslope Diablo Winds. The Tubbs Fire spread over 36,000 acres and destroyed 5,636 structures, killing 22. The simulations and supporting observations during the pre-Diablo Wind period indicate a well-defined inverted surface trough in Northern California’s Central Valley, along with a strong amplifying trough in the mid-troposphere and attendant cold frontogenesis over the Sierra Nevada. Mid-upper tropospheric jet streak flow, along with simulated and observed soundings from Reno, Nevada, indicate a mid-upper tropospheric jet indirect, exit-region descending, secondary circulation in conjunction with lower mid-tropospheric cold air advection caused by the southwestward low-level jet under the upper level jet’s entrance region. These adjustments enabled the organization of a deepening and ascending inversion over the Sierra Nevada, as well as a self-induced wave critical layer between 850 and 700 hPa prior to Diablo Wind formation. As the organizing jet streak departed, the discontinuously stratified atmosphere over the Sierra Nevada and coastal mountains in Northern California provided a favorable environment for mountain wave amplification. Intensifying leeside sinking motion coupled with wave steepening resulted in strong downslope winds in Northern California. Upward propagating mountain waves are present coinciding with the steepening of the isentropic surfaces consistent with the resonant interaction of nonlinear gravity waves. The model also simulated the development of a hydraulic jump in the lower troposphere on the lee side of the mountain range during Diablo Wind development. The simulation and observations indicate that the favorable environment for Diablo Winds resulted from the baroclinic jet-front system propagating over the Sierra Nevada when it produced a highly discontinuously stratified atmosphere favorable for nonlinear mountain wave amplification. However, the main surge of momentum down the leeside is only indirectly coupled with the jet streak’s exit region, being the result of cold frontogenesis, which allows for vertically differential cold air advection and its attendant discontinuously stratified vertical atmospheric structure.