Search

Increasing earth temperature due to the high level of greenhouse gas has affected the other climate elements on the earth surface. However, there was a little consideration of the differences between the global and local scale of climate change. This research included a comparison between the global climate change and the changes of climate elements that happened in Samawah city. The results showed that there is a significant difference between the increasing annual mean temperature globally and the annual mean temperature in the city. For example, when comparing the increase in annual mean temperature of the city for the period from 2006 to 2015 (ten years) with annual mean temperature globally based on the average of mean temperature for the previous 30 years (1975-2005), we note that there was increasing for the years 2010 and 2011 is almost four times and it was double for the years 2012, 2013, 2014 and 2015 higher than the increasing of annual mean temperature for the same years globally. Also, the mean temperature of the hot months of the summer season (JJA) in the city increased significantly compared to the rest of the months of the year and it is quite different from the change that occurred in the monthly mean temperature globally. Moreover, the annual average of precipitation in the city has fluctuated significantly due to the changes in climate and contrast to the increase in its global average. All these changes in the climate of the city will inevitably have an impact on the environment such as increasing drought, desertification and dust storms.

Rain-induced attenuation serves as a substantial factor influencing link power sizing in both terrestrial and satellite-based applications. The absence of in-situ rain rate measurements for localized link designs has led to generalized assumptions about rain-induced attenuation, contributing to increased instances of signal impairments during rainfall events. This study addresses this challenge by quantifying rain rate statistics over country capitals in Western and Central Africa. The Chebil and Moupfouma models were employed to estimate essential rain rate statistics, including the point rainfall rate R0.01, utilizing a 32-year data set of CRU rainfall accumulations. The results provide accurate rain-based statistics crucial for predicting, planning, and designing satellite and terrestrial links, especially for various microwave (MW) and millimeter-wave (mmW) technologies in specific locations. These rain rate insights are invaluable for engineers and designers working on communication systems, offering a comprehensive resource to enhance the accuracy of link budgeting and develop effective strategies for mitigating the impact of rainfall on signal quality. This research contributes to the optimization of communication systems, ensuring robust performance across diverse atmospheric conditions. [ABSTRACT FROM AUTHOR]

Extreme rainfall and flooding associated with landfalling tropical cyclones (TCs) have large societal impacts, both in fatalities and economic losses. This study examines the response of TC rainfall to climate change projected under future anthropogenic greenhouse emissions, focusing on Hurricane Irene, which produced severe flooding across the Northeastern United States in August 2011. Numerical simulations are made with the Weather Research and Forecasting model, placing Irene in the present‐day climate and one projected for the end of 21st century climate represented by Phase 5 of the Coupled Model Intercomparison Project Representative Concentration Pathway 8.5 scenario. Projected future changes to surface and atmospheric temperature lead to a storm rainfall increase of 32% relative to the control run, exceeding the rate expected by the Clausius‐Clapeyron relation given a ~3‐K lower atmospheric warming. Analyses of the atmospheric water balance highlight contributions to the increase in rainfall rate from both increased circulation strength and atmospheric moisture. Storm rainfall rate shows contrasting response to global warming during TC and extratropical transition periods. During the TC phase, Irene shows a significant increase of storm rainfall rate in inner core regions. This increase shifts to outer rainbands as Irene undergoes extratropical transition, collocated with the maximum tangential wind increase and the change of secondary circulation strength. Changes of storm track from the control run to global warming projections play a role in the change of spatial rainfall pattern. Distinct roles of surface and atmospheric warming in storm rainfall and structure changes are also examined. Plain Language Summary: Landfalling tropical cyclones (TCs) can undergo the process of extratropical transition, through which storm structure and dynamics transform, enabling them to persist (and extend their hazards) to middle‐ and high‐latitude regions, which have large‐scale conditions hostile to TCs. These so‐called post‐TCs can produce enhanced rainfall relative to typical TCs, leading to more severe flood hazards. For example, Hurricane Irene (2011) produced extreme flooding along the East Coast of the United States and Canada, especially in mid‐Atlantic regions and New England. Future changes of post‐TCs have strong implications for flood risk assessment and management. To provide new insights on this issue, we conducted a case study focusing on Hurricane Irene (2011) by placing Irene in a projected warmer climate, which allows us to examine aspects of the influence of climate change on future storm rainfall rate. Irene produced heavier rainfall in a warming climate than the current climate. This increase is mainly concentrated in the inner core region at the TC phase and shifts to outer regions at the post‐TC phase. The magnitude of Irene rainfall rate increase exceeds the rate of water vapor increase under the warmer climate, highlighting increased flood risk in the future. Key Points: Increase of Irene rain rate is observed in inner core regions for tropical cyclone phase but in outer rainbands during transition periodIncrease of Irene rain rate exceeds the rate of water vapor increase in a warming climate, suggesting the importance of dynamical effects [ABSTRACT FROM AUTHOR]

Copyright of Journal of Agricultural Economics & Social Sciences is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar (DPR) provides a unique set of three-dimensional radar precipitation estimates across much of the globe. Both terrain and climatic conditions can have a strong influence on the reliability of these estimates. Switzerland provides an ideal testbed to evaluate the performance of the DPR in complex terrain: it consists of a mixture of very complex terrain (the Alps) and the far flatter Swiss Plateau. It is also well instrumented, covered with a dense gauge network as well as a network of four dual-polarization C-band weather radars, with the same instrument network used in both the Plateau and the Alps. Here an evaluation of the GPM DPR rainfall rate products against the MeteoSwiss radar rainfall rate product for the first two years of the GPM DPR's operation is presented. Errors in both detection and estimation are considered, broken down by terrain complexity, season, precipitation phase, precipitation type, and precipitation rate. Errors are considered both integrated across the entire domain and spatially, and consistent underestimation of precipitation by GPM is found. This rises to −51% in complex terrain in the winter, primarily due to the predominance of DPR measurements wholly in the solid phase, where problems are caused by lower reflectivities. The smaller vertical extent of precipitation in winter is also likely a cause. Both detection and estimation performance are found to be significantly better in summer than in winter, in liquid than in solid precipitation, and in flatter terrain than in complex terrain. [ABSTRACT FROM AUTHOR]

Copyright of An-Najah University Journal for Research, B: Humanities is the property of An-Najah National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Drainage networks emerge due to the movement of sediment driven by climatic and tectonic forcings. Previous observations revealed the dependence of drainage density (Dd) on climatic factors such as mean annual precipitation (MAP). Specifically, it has been observed in intermediate climate (~175 mm < MAP < 700 mm) that Dd decreases with increasing MAP. This declining trend has been argued to be attributed to biotic activity, that is, the dominance of vegetation growth over runoff erosive force. Using high‐resolution topographic data from a physical experiment, we show that increasing rainfall may result in decreasing Dd even in the absence of biotic activity. Increasing rainfall rate results in narrower and less variable bifurcation angle and relatively longer links. The response of the evolving network in terms of bifurcation angle continues beyond the time when Dd has reached a new stable value, indicating that the network's topological response is relatively slower than the geomorphic response. Key Points: Drainage density decreases with increasing rainfall rate in a physical experiment without vegetationConvergent and divergent features show distinct responses to the change in rainfallHigher rainfall rate results in narrower and less variable bifurcating angles and longer links [ABSTRACT FROM AUTHOR]

The Regional Climate Model system version 4 (RegCM4) has been used to dynamically downscale outputs from four different general circulation models (GCM) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) to the horizontal resolution of 25 km × 25 km, in order to study changes in the Southern China hydrological cycle according to the Representative Concentration Pathway (RCP) 8.5 between 2050‐to‐2099 and 1979‐to‐2003. Accompanying wetter boreal spring and summer, the interannual rainfall variability for these seasons is also enhanced. A novel moisture budget analysis shows that changes in mean background humidity (anomalous wind convergence) dominate the increase in the interannual variability in spring (summer). Extreme daily precipitation in these seasons (based on the 95th percentile) is projected to become more intense, roughly following the Clausius–Clapeyron (CC) relation for the aforementioned seasons. On the other hand, the annual number of maximum consecutive dry days (CDD) is found to increase by about 3 to 5 days over locations south of 32° N, where autumn mean rainfall rate is projected to reduce (although this might be subjected to models' ability in capturing tropical cyclone activities). Analyses of the GCM raw outputs indicate that strengthened northerlies over coastal East Asia, which is likely associated with the so‐called tropical expansion, are responsible for the drier autumn. [ABSTRACT FROM AUTHOR]

SUMMARY This set of two companion papers aims at providing a statistical framework to quantify the inter-annual variability observed on the statistics of rain attenuation or rainfall rate derived from Earth-space propagation measurements. This part I is more specifically devoted to the theoretical study of the variance of estimation of empirical complementary cumulative distribution functions (ECCDFs) derived from Earth-space rain attenuation or rainfall rate time series. To focus the analysis on the statistical variability but without loss of generality, synthetic rain attenuation time series are considered. A large variability on the ECCDFs, which depends on the duration of the synthetic data, is first put into evidence. The variance of estimation is then derived from the properties of the statistical estimator. The formulation is validated numerically, by comparison with the ECCDF variances derived from the synthetic data. The variance of the fluctuations around the CCDF is then shown to be dependent on the average of the correlation function of the time series, on the probability level and on the measurement duration. This variance of estimation is needed as a prerequisite in conjunction with the knowledge of the climatic variability to characterize the yearly fluctuations of propagation statistics computed from experimental time series. The extensions from simulations to experiments as well as the application to system planning are detailed in part II. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Sciences, Life & Applied Sciences is the property of Arab Journal of Sciences & Research Publishing (AJSRP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recent climate changes have prompted changes in the hydrological cycle at a global scale, creating instability when predicting future climate conditions and related changes. Perturbations in global climate models have created the need to concentrate consequent changes in hydro climatic factors to comprehend the regional and territorial impacts of climate and environmental changes. Syria, as a Middle East country, is exposed to extreme climate events such as drought and flood. The aim of this study is to analyze rainfall trends in Syria in response to the likely climate change. The analysis was conducted for rainfall data collected from 71 stations distributed all over the country for the period (1991–2009). The trend analysis was performed in monthly and seasonal scales using Mann–Kendall non-parametric statistical tests. The results attained from Mann–Kendall trend analysis revealed decreasing trends at most of the stations. Additionally, rainfall analysis was conducted for the stations with significant trends for wet and dry periods, which also revealed decreasing trends at almost all the stations. From the analysis of the results, it is obvious that slight increasing trends in rainfall in Syria occurred in the fall period. However, in the winter and spring periods, significant decreasing trends have been observed at almost all the stations. This reveals that the country will suffer from shortage of water, because most rainfall occurs in the winter and spring, infrequently in fall and rarely in summer. The results are consistent with the IPCC's fifth report that predicted a decrease in rainfall in the Mediterranean and southern Asia. The results of this paper could help the management of water resources in Syria considering future climate changes. [ABSTRACT FROM AUTHOR]

Mounting evidence across South Africa's southwestern winter rainfall zone (WRZ) reflects consistent drying since ~ 1980, and projected trends suggest this will continue. However, limited evidence exists for changes in the region's rainfall seasonality. To improve our understanding of these WRZ drying trends, especially within the context of Cape Town's 2015–2017 "Day Zero" drought, it is necessary to explore long-term rainfall seasonality trends. Thus, we use the longest WRZ meteorological record from the South African Astronomical Observatory (SAAO) in Cape Town to investigate rainfall seasonality shifts during 1841–2020. Consistent with recorded poleward migrations of the subtropical high-pressure belt and mid-latitude westerlies, known drivers behind the drought and drying trends, calculated trends demonstrate strengthening of WRZ conditions, primarily from a later start-date trend leading to a shorter wet-season. Long-term drying trends are quantified for the wet and dry seasons; however, analysis of trend evolution reveals much variability, reflecting that drying has only persisted since ~ 1892. Comparative analyses of the first and last 59 years of 1841–2020 reveal a rainfall decline of almost 10% across both seasons—highlighting that the extreme "Day Zero" drought was not only driven by wet-season rainfall declines. Results demonstrate that these drying trends were consistently driven by a long-term decline in rain day counts and a more recent decline in average rainfall per rain day. Correspondence between our results and projected rainfall seasonality trends suggests the trends we quantified will likely continue; thus, improvements and continuation of existing water conservation and management strategies are imperative for Cape Town. [ABSTRACT FROM AUTHOR]

Copyright of Alexandria Science Exchange Journal is the property of Alexandria Science Exchange Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Knutson et al. recently published a metastudy that gives multimodel projections for changes in various properties of tropical cyclones under climate change. They considered frequency of tropical cyclones, frequency of very intense tropical cyclones, intensity of tropical cyclones, and total rainfall rate of tropical cyclones. For each of these properties, they reported changes globally and by basin for the six major tropical cyclone basins. The changes were pre- sented as the change that would occur with 28C warming of global mean surface temperature. These projections are po- tentially of great use to the tropical cyclone risk modeling community. However, most risk models use temporal baselines, such as the period from 1950 to 2019, and the Knutson et al. results can only be applied to risk models after some steps of adjustment involving past and future global mean surface temperature values. We derive the necessary adjustments and present and discuss some of the resulting projections, for different properties, basins, RCPs, and baselines.We find that the results are sensitive to the baseline being used, which implies that users of tropical cyclone risk models need to make sure they clearly understand what baseline their model represents before they adjust the model for climate change. One part of our analysis derives estimates of the implied impact of climate change so far on TC properties, relative to a representative baseline. The computer code we use to calculate the adjustments is available online. [ABSTRACT FROM AUTHOR]

Greenland ice sheet rainfall is expected to increase under a warming climate. Yet, there have been no active long‐term in‐situ rainfall records on the ice sheet due to observational difficulties. Here, we utilize the state‐of‐the‐art 5 km polar non‐hydrostatic regional climate model NHM‐SMAP to evaluate the ice sheet's rainfall over 40 years (1980–2019). The largest trends include a fourfold increase in annual rainfall for the northwestern ice sheet; 3.1 Gt year−1 or 12 mm m−2 year−1. September ice‐sheet‐wide rainfall amount and intensity increase by 7.5 Gt month−1 and 20.8 mm h−1 year−1. In the last two decades, the increasing September maximum hourly rainfall rate exceeded 50 mm h−1 six times. The increased surface water delivery has numerous implications, including for snow metamorphism and ice flow dynamics. Plain Language Summary: We find that rainfall has increased over the Greenland ice sheet from 1980 to 2019. Among the eight major ice‐sheet drainage areas, the northwestern sector stands out as an increasing rainfall hotspot where the annual rainfall has increased fourfold. For the entire ice sheet, September's total rainfall and its intensity increased by 224% and 54% above the 1981–2010 baseline over the last 40 years. An increase in late melt season rainfall is expected to contribute to an increase in late summer snow and ice melt. Our results provide the first detailed quantification of the state of ice sheet rainfall climatology. Key Points: A 5 km horizontal resolution non‐hydrostatic regional climate model is used to evaluate Greenland ice sheet rainfall from 1980 to 2019The northwestern sector stands out as a hotspot of increasing rainfallBoth the amount and intensity of September ice‐sheet‐wide rainfall have significantly increased in the 40 years from 1980 to 2019 [ABSTRACT FROM AUTHOR]

Trend analysis for the long-term average temperature and rainfall of Ethiopia during 1901 to 2015 has been performed to understand the pattern of these important meteorological features under climate change. The rainfall characterizations viz., precipitation concentration index (PCI), seasonality index (SI), rainfall anomaly index (RAI) and departure analysis of rainfall (DAR) have been calculated and interpreted. The annual rainfall recorded for the whole period was 816.3 ± 90.82 mm/year. During kiremt (long rainy) season, maximum seasonal rainfall of 453.2 mm were recorded while, its minimum value (39.6 mm) were received in bega (dry) season, respectively. The analysis of probability distribution for the time series data showed slightly positive skewness and kurtosis in monthly, seasonal and annual rainfall from the normal distribution. The results of Modified Mann–Kendall trend analysis for average temperature revealed a significant increasing trend from 1961 to 2015. Conversely, dry season (bega) rainfall, showed an increasing trend while kiremt season rainfall with decreasing trend for the period of 1901–2015. However, annual and other seasonal rainfall did not show any statistically significant trend. Study concludes that there is an increase in the average temperature in Ethiopia but, it constitutes a high degree of stability in rainfall rate and distribution. [ABSTRACT FROM AUTHOR]

Current-climate precipitation and temperature extremes have been identified by decision makers in West Africa as among the more impactful weather events causing lasting socioeconomic damage. In this article, we use a plausible future-climate scenario (RCP8.5) for the end of the twenty-first century to explore the relative commonness of such extremes under global warming. The analysis presented considers what a typical day in the future climate will feel like relative to current extrema. Across much of West Africa, we see that the typical future-climate day has maximum and minimum temperatures greater than 99.5% of currently experienced values. This finding exists for most months but is particularly pronounced during the Boreal spring and summer. The typical future precipitation event has a daily rainfall rate greater than 95% of current storms. These findings exist in both a future scenario model run with and without parameterised convection, and for many of the Coupled Model Inter-comparison Project version 5 ensemble members. Additionally, agronomic monsoon onset is projected to occur later and have greater inter-annual variability in the future. Our findings suggest far more extreme conditions in future climate over West Africa. The projected changes in temperature and precipitation could have serious socioeconomic implications, stressing the need for effective mitigation given the potential lack of adaptation pathways available to decision makers. [ABSTRACT FROM AUTHOR]

The outage performance of line-of-sight fixed wireless access channels operating above 10 GHz is predominantly controlled by rain attenuation. In this paper, a prediction model, appropriate for heavy rain climatic regions based on gamma distribution assumption for the rainfall rate and the rain attenuation is being reviewed to incorporate the recently released ITU-R rainmaps. The model exhibits a very good performance, as validated by tests against the ITU-R databank Moreover, the above model is extended to evaluate the outage performance of a dual-polarized mm-wave fixed wireless access link located in heavy rain climatic regions. The obtained numerical results focus on the investigation of the effects of various operational parameters upon the outage performance of the microwave communication link. [ABSTRACT FROM AUTHOR]

Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (Tb) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the oblique incidence of current radiometers. Because of the horizontal averaging that occurs away from the nadir direction, the beam-filling error is found to be only a fraction of what has been reported previously in the literature based upon plane-parallel calculations. For a FOV representative of the 19-GHz radiometer channel (18 km × 28 km) aboard the Tropical Rainfall Measuring Mission (TRMM), the mean beam-filling correction computed in this study for tropical atmospheres is 1.26 instead of 1.52 computed from plane-parallel techniques. The slant-path solution is also less sensitive to finescale rainfall inhomogeneity and is, thus, able to make use of 4-km radar data from the TRMM Precipitation Radar (PR) in order to map regional and seasonal distributions of observed rainfall inhomogeneity in the Tropics. The data are examined to assess the expected errors introduced into climate rainfall records by unresolved changes in rainfall inhomogeneity. Results show that global mean monthly errors introduced by not explicitly accounting for rainfall inhomogeneity do not exceed 0.5% if the beam-filling error is allowed to be a function of rainfall rate and freezing level and does not exceed 2% if a universal beam-filling correction is applied that depends only upon the freezing level. Monthly regional errors can be significantly larger. Over the Indian Ocean, errors as large as 8% were found if the beam-filling correction is allowed to vary with rainfall rate and freezing level while errors of 15% were found if a universal correction is used. [ABSTRACT FROM AUTHOR]

The urgent need for timely and accurate precipitation estimations in the face of ongoing climate change and the increasing frequency and/or intensity of extreme weather events underscores the necessity for innovative approaches. Recently, several studies have focused on estimating the precipitation rate through induced attenuation of radio frequency (RF) signals, which are abundant in modern communication systems. Most research has concentrated on frequencies exceeding 10 GHz, as attenuation at lower frequencies is minimal, posing measurement challenges. This study aims to confront this limitation by introducing a high-precision experimental setup capable of detecting this subtle attenuation at frequencies under 10 GHz. The setup includes a transmitter and receiver optimized for operation at 2.07, 4.63, and 6.22 GHz, where minimal worldwide research exists. A power resolution below 10−5 dB in preliminary measurements demonstrated its effectiveness in quantifying signal attenuation due to precipitation across the specified frequencies. Moreover, a strong power law relationship was observed between signal attenuation and precipitation rate for all three frequencies, while, as expected, the higher the frequency, the more pronounced the signal attenuation was. [ABSTRACT FROM AUTHOR]

Future flood risk assessment has primarily focused on heavy rainfall as the main driver, with the assumption that projected increases in extreme rain events will lead to subsequent flooding. However, the presence of and changes in vegetation have long been known to influence the relationship between rainfall and runoff. Here, we extract historical (1850–1880) and projected (2070–2100) daily extreme rainfall events, the corresponding runoff, and antecedent conditions simulated in a prominent large Earth system model ensemble to examine the shifting extreme rainfall and runoff relationship. Even with widespread projected increases in the magnitude (78% of the land surface) and number (72%) of extreme rainfall events, we find projected declines in event‐based runoff ratio (runoff/rainfall) for a majority (57%) of the Earth surface. Runoff ratio declines are linked with decreases in antecedent soil water driven by greater transpiration and canopy evaporation (both linked to vegetation greening) compared to areas with runoff ratio increases. Using a machine learning regression tree approach, we find that changes in canopy evaporation is the most important variable related to changes in antecedent soil water content in areas of decreased runoff ratios (with minimal changes in antecedent rainfall) while antecedent ground evaporation is the most important variable in areas of increased runoff ratios. Our results suggest that simulated interactions between vegetation greening, increasing evaporative demand, and antecedent soil drying are projected to diminish runoff associated with extreme rainfall events, with important implications for society. Plain Language Summary: Climate change is leading to increases in the magnitude and number of extreme rainfall events. These increases in extreme rainfall events are often assumed to lead to an increase in extreme flooding events. However, using a climate model ensemble, our results indicate that changes in vegetation and atmospheric water demand may alter the relationship between extreme rainfall and extreme runoff. Notably, for a majority of the Earth surface, we find that projected changes in atmospheric aridity and vegetation lead to drier soil conditions prior to the extreme rainfall event that reduces the amount of hydrologic runoff generated. These findings have important implications for water resources management. Key Points: The number and magnitude of extreme rainfall events are projected to increase throughout the global land surfaceProjected declines in event‐based runoff ratio are found for a majority of the global land surfaceProjected runoff ratio declines are linked to decreased antecedent soil water from changes in individual evapotranspiration components [ABSTRACT FROM AUTHOR]

Characteristics and global distribution of regional extreme rainfall are presented using 12 yr of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) measurements. By considering each rainfall event as a set of contiguous PR rainy pixels, characteristic values for each event are obtained. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile on a 2.5° × 2.5° horizontal-resolution grid. The geographical distribution of extreme rainfall rates shows clear regional differences. The size and volumetric rainfall of extreme events also show clear regional differences. Extreme rainfall rates show good correlations with the corresponding rain-top heights and event sizes over oceans but marginal or no correlation over land. The time of maximum occurrence of extreme rainfall events tends to be during 0000-1200 LT over oceans, whereas it has a distinct afternoon peak over land. There are also clear seasonal differences in which the occurrence over land is largely coincident with insolation. Regional extreme rainfall is classified by extreme rainfall rate (intensity) and the corresponding event size (extensity). Regions of 'intense and extensive' extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of 'intense but less extensive' extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of 'extensive but less intense' extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones. [ABSTRACT FROM AUTHOR]

Land-falling tropical cyclones along the Queensland coastline can result in serious and widespread damage. However, the effects of climate change on cyclone characteristics such as intensity, trajectory, rainfall, and especially translation speed and size are not well-understood. This study explores the relative change in the characteristics of three case studies by comparing the simulated tropical cyclones under current climate conditions with simulations of the same systems under future climate conditions. Simulations are performed with the Weather Research and Forecasting Model and environmental conditions for the future climate are obtained from the Community Earth System Model using a pseudo global warming technique. Results demonstrate a consistent response of increasing intensity through reduced central pressure (by up to 11 hPa), increased wind speeds (by 5-10% on average), and increased rainfall (by up to 27% for average hourly rainfall rates). The responses of other characteristics were variable and governed by either the location and trajectory of the current climate cyclone or the change in the steering flow. The cyclone that traveled furthest poleward encountered a larger climate perturbation, resulting in a larger proportional increase in size, rainfall rate, and wind speeds. The projected monthly average change in the 500 mb winds with climate change governed the alteration in the both the trajectory and translation speed for each case. The simulated changes have serious implications for damage to coastal settlements, infrastructure, and ecosystems through increased wind speeds, storm surge, rainfall, and potentially increased size of some systems. [ABSTRACT FROM AUTHOR]

A vast amount of future climate scenario datasets, created by climate models such as general circulation models (GCMs), have been used in conjunction with watershed models to project future climate variability impact on hydrological processes and water quality. However, these low spatial-temporal resolution datasets are often difficult to downscale spatially and disaggregate temporarily, and they may not be accurate for local watersheds ( i.e ., state level or smaller watersheds). This study applied the US-EPA (Environmental Protection Agency)’s Climate Assessment Tool (CAT) to create future climate variability scenarios based on historical measured data for local watersheds. As a case demonstration, CAT was employed in conjunction with HSPF (Hydrological Simulation Program-FORTRAN) model to assess the impacts of the potential future extreme rainfall events and air temperature increases upon nitrate-nitrogen (NO 3 -N) and orthophosphate (PO 4 ) loads in the Lower Yazoo River Watershed (LYRW), a local watershed in Mississippi, USA. Results showed that the 10 and 20% increases in rainfall rate, respectively, increased NO 3 -N load by 9.1 and 18% and PO 4 load by 12 and 24% over a 10-year simulation period. In contrast, simultaneous increases in air temperature by 1.0 °C and rainfall rate by 10% as well as air temperature by 2.0 °C and rainfall rate by 20% increased NO 3 -N load by 12% and 20%, and PO 4 load by 14 and 26%, respectively. A summer extreme rainfall scenario was created if a 10% increase in rainfall rate increased the total volume of rainwater for that summer by 10% or more. When this event occurred, it could increase the monthly loads of NO 3 -N and PO 4 , by 31 and 41%, respectively, for that summer. Therefore, the extreme rainfall events had tremendous impacts on the NO 3 -N and PO 4 loads. It is apparent that CAT is a flexible and useful tool to modify historical rainfall and air temperature data to predict climate variability impacts on water quality for local watersheds. [ABSTRACT FROM AUTHOR]

TRMM PR 2A25, version 7 (V7), retrievals of reflectivity Z and rainfall rate R are compared with WSR-88D dual-polarimetric S-band radar data for 28 radars over the southeastern United States after matching their horizontal resolution and sampling. TRMM Ku-band measurements are converted to S-band approximations to more directly compare reflectivity estimates. Rain rates are approximated from WSR-88D data using the CSU-hydrometeor identification rainfall optimization (HIDRO) algorithm. Tropics-wide TRMM retrievals confirm previous findings of a low overlap fraction between extreme convective intensity, as approximated by the maximum 40-dB Z height, and extreme near-surface rain rates. WSR-88D data also confirm this low overlap but show that it is likely higher than TRMM PR retrievals indicate. For maximum 40-dB Z echo heights that extend above the freezing level, mean WSR-88D reflectivities at low levels are approximately 2 dB higher than TRMM PR reflectivities. Higher WSR-88D-retrieved rain rates for a given low-level reflectivity combine with these higher low-level reflectivities for a given maximum 40-dB Z height to produce rain rates that are approximately double those retrieved by the TRMM PR for maximum 40-dB Z heights that extend above the freezing level. TRMM PR path-integrated attenuation, and WSR-88D specific differential phase, differential reflectivity, and hail fraction indicate that the TRMM PR 2A25 V7 algorithm is possibly misidentifying low-midlevel hail and/or graupel as greater attenuating liquid, or vice versa. This misidentification, coupled with underestimation of path-integrated attenuation caused by nonuniform beamfilling and higher rain rates produced by specific differential phase (KDP)- R than Z- R relationships, results in low-biased 2A25 V7 rain rates in intense convection. [ABSTRACT FROM AUTHOR]

During the 2010-2011 wet season in Brazil, widespread landslides triggered by heavy rainfall killed hundreds of people and displaced nearly 35,000. The extreme precipitation was associated with the formation of the South Atlantic convergence zone (SACZ). Even though the physical mechanisms behind the formation and persistence of subtropical convergence zones are still unclear, we demonstrate that early predictions of heavy rainfall in the SACZ region are possible. Precipitation rate hindcasts from the NCEP Climate Forecast System version 2 are calibrated with the aid of a gridded precipitation dataset. When the calibration was applied to the 2010-2011 events, the hindcasts were able to depict both active and break phases of the SACZ with up to 2 weeks in advance during a period of relatively weak intraseasonal variability associated with the Madden-Julian Oscillation (MJO). [ABSTRACT FROM AUTHOR]

Copyright of Journal of Water & Land Development is the property of Polish Academy of Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Algae populate multiple habitats, including snow and ice, where they can form red blooms. These decrease snow albedo, accelerating snowmelt and potentially feeding back on snow and glacier decline caused by climate change. Quantifying this feedback requires the understanding of bloom evolution with climate change. Little, however, is known about the drivers of red snow blooms. Here, we develop an algorithm to analyze 5 y of satellite data from the European Alps and separate bloom occurrences from similarly colored Saharan dust depositions. In a second step, we combine the occurrences of blooms with meteorological data and snow simulations to identify the drivers of blooms. Results show that the upward migration of algae from the ground and blooming requires the presence of liquid water throughout the whole snow column for at least 46 d. Our limited data suggest that moderate dust amounts provide nutrients favorable to bloom, whereas large dust amounts hasten snowmelt and reduce its duration below the threshold required for blooming. Over the period studied, blooms cover 1.3% of the area above 1,800m elevation, advancing the snow melt-out date by 4 to 21 d in these areas. Under warmer climates, maximum snow mass will decrease whereas snowmelt duration, that controls algal blooms' occurrences, is less sensitive to global temperature increase. In this respect, the impact of bloom on snowmelt will either remain stable (RCP4.5) or decrease (RCP8.5). Algal blooms in the Alps therefore do not constitute a positive climate feedback. [ABSTRACT FROM AUTHOR]

The Western Ghats have been declared as a World Heritage Site by UNESCO. Besides, it is classified as one of the world’s 36 biodiversity hotspots by Conservation International. The Western Ghats of Kerala have experienced devastating landslides and floods in recent years, which are triggered by climate change. This alarming situation calls for policymakers to develop a comprehensive climate adaptation policy at the local level. However, no study has yet thoroughly investigated this critical issue. Therefore, this study explores the prospects and trade-offs of climate rehabilitation policies for families living in the highly landslide- and flood-prone areas of the Western Ghats in Kerala, India. We have undertaken a mixed methodology comprising four focus group discussions followed by empirical analyses. Towards this, a semi-structured questionnaire is framed to gather relevant information based on the outcomes. The data are analyzed using robust logistic regression models. The findings indicate that most agricultural worker families support the rehabilitation policy, given their lower opportunity costs due to the absence of farmland ownership. On the other hand, agricultural families face considerable trade-offs regarding rehabilitation. Most agricultural families prefer to rehabilitate within a short distance from the current residence or construct a retaining wall as they fear rehabilitation to distant places will gravely affect their livelihood. This research highlights the potential for implementing a rehabilitation policy for marginalized communities heavily exposed to climate risks. Additionally, constructing retaining walls should also be a primary focus of the Government. [ABSTRACT FROM AUTHOR]

We evaluate tropical cyclones (TCs) in a set of thermodynamic global warming (TGW) simulations over the continental United States (CONUS). A 12 km simulation forced by ERA5 provides a 40‐year historical (1980–2019) control. Four complimentary future scenarios are generated using thermodynamic deltas applied to lateral boundary, interior, and surface forcing. We curate a data set of 4,498 6‐hourly TC snapshots in the control and find a corresponding "twin" in each counterfactual, permitting a paired comparison. Warming results in an increase in mean dynamical TC intensity and moisture‐related quantities, with the latter being more pronounced. TC inner cores contract slightly but outer storm size remains unchanged. The frequency with which TCs become more intense is only moderately consistent, with snapshots having increased hazards ranging from 50% to 80% depending on warming level. The fractions of TCs undergoing rapid intensification and weakening both increase across all warming simulations, suggesting elevated short‐term intensity variability. Plain Language Summary: We examined how tropical cyclones (TCs) near the United States might change due to warmer climates. First, we recreated past weather conditions from 1980 to 2019 using a specialized climate model. Then, we predicted future changes in the same meteorology by modifying the model to include warmer temperatures and running four additional simulations. We tracked and analyzed over 4,000 instances of TCs from the past 40 years, ensuring that these TCs were all matched between all five simulations, and evaluated their changes under future warming conditions. Our findings suggest that TCs will become stronger on average as the world warms, with the most notable increases in TC moisture. Not every TC in our study becomes more intense with warming, however, highlighting the complexity of understanding how extreme weather will change in the future. We found that the chances of a TC rapidly intensifying or suddenly weakening both rise with higher levels of warming. These trends could complicate predictions of TC intensity in the future, presenting additional challenges for forecasting and preparation. Key Points: Thermodynamic global warming simulations provide a unique large‐sample size view into paired counterfactual tropical cyclones12 km simulations indicate future near‐United States cyclones will, on average, be wetter, slightly more intense, but similarly sizedPeriods of rapid intensification and weakening indicate increased tropical cyclone intensity variability in warmer climates [ABSTRACT FROM AUTHOR]

Accurate predictions are crucial for addressing the challenges posed by climate change. Given South Korea's location within the East Asian summer monsoon domain, characterized by high spatiotemporal variability, enhancing prediction accuracy for regions experiencing heavy rainfall during the summer monsoon is essential. This study aims to derive temporal weighting functions using hybrid surface rainfall radar-observation data as the target, with input from two forecast datasets: the McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) and the KLAPS Forecast System. The results indicated that the variability in the optimized parameters closely mirrored the variability in the rainfall events, demonstrating a consistent pattern. Comparison with previous blending results, which employed event-type-based weighting functions, showed significant deviation in the average AUC (0.076) and the least deviation (0.029). The optimized temporal weighting function effectively mitigated the limitations associated with varying forecast lead times in individual datasets, with RMSE values of 0.884 for the 1 h lead time of KLFS and 2.295 for the 4–6 h lead time of MAPLE. This blending methodology, incorporating temporal weighting functions, considers the temporal patterns in various forecast datasets, markedly reducing computational cost while addressing the temporal challenges of existing forecast data. [ABSTRACT FROM AUTHOR]

The earliest Asian summer monsoon onset (SMO) occurs in the Bay of Bengal (BoB), heralding the coming of the rainy season. In late April or early May, the strong sea surface temperature (SST) diurnal variation accompanied by ocean surface warming triggers the SMO. However, this observed diurnal cycle intensity cannot be reasonably simulated by state‐of‐the‐art climate models, resulting in a spurious delayed SMO. To address this issue, the SST diurnal cycle parameterized by a diagnostic sublayer scheme was incorporated into a climate model named FIO‐ESM v2.0. The large diurnal amplitude of SST contributes to surface warming and changes atmospheric circulation. Consequently, the high‐pressure anomaly at high levels and an inverted trough at low levels promote more convective activity, triggering an earlier SMO. Our findings improve the ability of climate models in simulating the evolution of the Asian monsoon system. Plain Language Summary: Asian summer monsoon onset (SMO) accompanied by the coming of the rainy season has a significant impact on the lives and livelihoods of more than half of the world's population. However, state‐of‐the‐art climate models struggle to capture the major features of SMO accurately. The simulated diurnal amplitude of sea surface temperature (SST) is much smaller compared with observation, resulting in a cold bias in SST and a delayed SMO in the Bay of Bengal (BoB). Here, we incorporated a diagnostic sublayer parameterization into the climate model to account for the effect of a strong diurnal cycle. The SST in the BoB increases, and more convective activities are promoted in response to the warmer underlying surface. Changes in monsoon circulation create favorable environmental conditions for an advanced SMO. Considering the effect of strong diurnal variation provides a solution to reduce common biases of the climate model in simulating SMO. Key Points: The spurious delayed Asian summer monsoon onset (SMO) is improved by including the effect of large sea surface temperature (SST) diurnal amplitude in a climate modelStrong diurnal variation of SST contributes to upper ocean warming in the Bay of Bengal before the Asian SMOLarge‐scale circulation with favorable conditions for convection activity in response to ocean warming triggers an advanced monsoon onset [ABSTRACT FROM AUTHOR]

The General Circulation Models experience a significant challenge in realistically simulating rainfall over the tropical Maritime Continent (hereafter, MC). Here, we investigate the mechanisms of an improvement in monthly rainfall simulation over the MC region in the UK Met Office Unified Model (version Global Atmosphere 6.0), which occurs when the horizontal resolution is increased from N96 (grid spacing ~135 km) to N216 (~60 km). The increased resolution enhances the area-averaged rainfall rate over the MC, thereby reducing the dry rainfall bias seen in the model at the N96 resolution. We find that the enhanced area-averaged rainfall is mostly due to an increase in the medium rainfall rates that occurs over the MC islands in the N216 experiment. The rainfall change is predominantly associated with changes in the atmospheric convective circulation and the related horizontal moisture flux convergence. The vertical profiles of convective circulation show a strong sensitivity to the increased horizontal resolution over the MC islands, but not over the surrounding oceans. It is shown that a significant underestimation of the deep convection (as opposed to the shallow convection) in the N96 experiment is primarily responsible for the stronger dry bias in this experiment. We present evidence that the dry bias, and the associated weaker deep convection, are in part caused by the strongly smoothed orography used in the N96 experiment, which provides a weaker orographic lifting of the moist surface air (in a conditionally unstable atmosphere) than that in the N216 experiment. [ABSTRACT FROM AUTHOR]

Desertification is one of the most critical environmental challenges facing Iraq, significantly impacting agricultural productivity. This paper explores the phenomenon of desertification in Iraq, its causes, and its detrimental effects on agricultural land. The study highlights that about 90% of Iraq's land falls within arid andsemi-arid climates, exacerbating desertification. High temperatures, reduced rainfall, and improper land management are major factors contributing to soil degradation. The research focuses on the causes of desertification, such as human activities, climate change, and poor agricultural practices, and assesses the resulting decline in Iraq's food production capacity. The paper also discusses strategies for combating desertification, including land management, technological interventions, and policy recommendations to protect Iraq's remaining arable land. [ABSTRACT FROM AUTHOR]

Introduction: Groundwater in the Middle East and North Africa region is a critical component of the water supply budget due to a (semi-)arid climate and hence limited surface water resources. Despite the significance, factors affecting the groundwater balance and overall sustainability of the resource are often poorly understood. This often includes recharge and discharge characteristics, groundwater extraction and impacts of climate change. The present study investigates the groundwater balance in the Dead Sea Basin aquifer in Jordan using a groundwater flow model developed using the MODFLOW. Methods: The study aimed to simulate groundwater balance components and their effect on estimation of the aquifer's safe yield, and to also undertake a preliminary analysis of the impact of climate change on groundwater levels in the aquifer. Model calibration and predictive analysis was undertaken using a probabilisticmodeling workflow. Spatially heterogeneous groundwater recharge for the historical period was estimated as a function of rainfall by simultaneously calibrating the recharge and aquifer hydraulic property parameters. Results and discussion: The model indicated that annual average recharge constituted 5.1% of the precipitation over a simulation period of 6 years. The effect of groundwater recharge and discharge components were evaluated in the context of estimation of safe yield of the aquifer. The average annual safe yield is estimated as ~8.0mm corresponding to the 80% of the calibrated recharge value. Simulated groundwater levels matched well with the declining trends in observed water levels which are indicative of unsustainable use. Long-term simulation of groundwater levels indicated that current conditions would result in large drawdown in groundwater levels by the end of the century. Simulation of climate change scenarios using projected estimates of rainfall and evaporation indicates that climate change scenarios would further exacerbate groundwater levels by relatively small amounts. These findings highlight the need to simulate the groundwater balance to better understand the water availability and future sustainability. [ABSTRACT FROM AUTHOR]

Over the past two decades, rapid climate change has severely impacted people's lives globally, affecting their safety and sustainability. Water, a vital human resource, has been severely affected, with drought and high temperatures leading to desertification, the drying up of rivers and lakes, spontaneous fires in forests, and massive floods and torrents due to melting ice and rising sea and ocean surface water levels. The expected impacts of climate change on the Nile, Egypt's primary water source, are significant. These impacts can vary across regions, depending on factors like local climate, socio-economic dynamics, topography, and environmental nature. Upper Egypt, characterized by arid and semi-arid regions, faces water scarcity and socio-economic development challenges. Climate change exacerbates these issues, posing significant threats to the region's ecological sustainability and socio-economic development. Therefore, it is crucial to address these impacts to ensure the Nile's continued vitality and sustainability. The study aims to analyze the climate change data over the past few decades, analyze its characteristics, and model its effects on Upper Egypt's water sources. The study expected a big decrease in the water resources of the Nile. While what is currently occurring in terms of fluctuating rainfall rates between scarcity and severity contradicts the results of those studies, that is the best evidence of the need for further research and studies to obtain more reliable and consistent results with the reality that it may help decision-makers to develop scenarios to manage climate change effectively, preventing or reducing negative effects, and finding suitable alternatives. Studies predict a 10% decrease in Nile revenue at Aswan High Dam Lake by 2095, with some predicting a 30% increase. This lack of credibility underscores the need for more comprehensive studies. [ABSTRACT FROM AUTHOR]

Projected changes of warm season (May-September) rainfall events in an ensemble of 30 regional climate model (RCM) simulations are assessed for the Czech Republic. Individual rainfall events are identified using the concept of minimum inter-event time and only heavy events are considered. The changes of rainfall event characteristics are evaluated between the control (1981-2000) and two scenario (2020-2049 and 2070-2099) periods. Despite a consistent decrease in the number of heavy rainfall events, there is a large uncertainty in projected changes in seasonal precipitation total due to heavy events. Most considered characteristics (rainfall event depth, mean rainfall rate, maximum 60-min rainfall intensity and indicators of rainfall event erosivity) are projected to increase and larger increases appear for more extreme values. Only rainfall event duration slightly decreases in the more distant scenario period according to the RCM simulations. As a consequence, the number of less extreme heavy rainfall events as well as the number of long events decreases in majority of the RCM simulations. Changes in most event characteristics (and especially in characteristics related to the rainfall intensity) depend on changes in radiative forcing and temperature for the future periods. Only changes in the number of events and seasonal total due to heavy events depend significantly on altitude. [ABSTRACT FROM AUTHOR]

This study evaluates several important statistics of daily rainfall based on frequency and amount distributions as simulated by a global climate model whose precipitation does not depend on convective parameterization-Super-Parameterized Community Atmosphere Model (SPCAM). Three superparameterized and conventional versions of CAM, coupled within the Community Earth System Model (CESM1 and CCSM4), are compared against two modern rainfall products (GPCP 1DD and TRMM 3B42) to discriminate robust effects of superparameterization that emerge across multiple versions. The geographic pattern of annual-mean rainfall is mostly insensitive to superparameterization, with only slight improvements in the double-ITCZ bias. However, unfolding intensity distributions reveal several improvements in the character of rainfall simulated by SPCAM. The rainfall rate that delivers the most accumulated rain (i.e., amount mode) is systematically too weak in all versions of CAM relative to TRMM 3B42 and does not improve with horizontal resolution. It is improved by superparameterization though, with higher modes in regions of tropical wave, Madden-Julian Oscillation, and monsoon activity. Superparameterization produces better representations of extreme rates compared to TRMM 3B42, without sensitivity to horizontal resolution seen in CAM. SPCAM produces more dry days over land and fewer over the ocean. Updates to CAM's low cloud parameterizations have narrowed the frequency peak of light rain, converging toward SPCAM. Poleward of 50°, where more rainfall is produced by resolved-scale processes in CAM, few differences discriminate the rainfall properties of the two models. These results are discussed in light of their implication for future rainfall changes in response to climate forcing. [ABSTRACT FROM AUTHOR]

In order to understand the dynamics of climate change and to adopt mitigation technique against it, it is necessary to know its impact on rainfall, one of the worst affected meteorological elements. Weather radars and satellites—proven to be the most effective instruments to estimate rainfall—need to explore high frequencies, namely the millimeter wave frequency range, because of its higher rate of data transmission, and also due to overcrowding at the lower frequency region. However, with an increase in frequency, the attenuation of the signal by rainfall increases. Above 10 GHz, the attenuation can be so severe that the link transmission may be significantly interrupted. Moreover, modern satellites adopting frequency reuse technique to increase the channel capacity suffer from unwanted cross polarization, which is attributed to the oblate shape of rain drops. Knowledge of co-polar attenuation is necessary to estimate cross polarization. Thus, the study of attenuation is of immense importance for an accurate estimation of rainfall. In this paper, the authors aim to study the attenuation at the Tropical Microwave Imager (TMI) channels, viz. 10.65, 19.35, 21.3, 37, and 85.5 GHz onboard the Tropical Rainfall Measuring Mission (TRMM) satellite over Salem, India by using the International Telecommunication Union (ITU-R) model. The TMI uses four of its channels in dual polarization mode, except the 21.3 GHz. The ITU-R model to estimate rainfall attenuation needs a one-minute rainfall interval. However, rainfall values are mostly available on hourly basis. This paper aims to seek a conversion formula between the two, if any, over Salem. [ABSTRACT FROM AUTHOR]

Abstract Extreme rainfall and flooding associated with landfalling tropical cyclones (TCs) have large societal impacts, both in fatalities and economic losses. This study examines the response of TC rainfall to climate change projected under future anthropogenic greenhouse emissions, focusing on Hurricane Irene, which produced severe flooding across the Northeastern United States in August 2011. Numerical simulations are made with the Weather Research and Forecasting model, placing Irene in the present‐day climate and one projected for the end of 21st century climate represented by Phase 5 of the Coupled Model Intercomparison Project Representative Concentration Pathway 8.5 scenario. Projected future changes to surface and atmospheric temperature lead to a storm rainfall increase of 32% relative to the control run, exceeding the rate expected by the Clausius‐Clapeyron relation given a ~3‐K lower atmospheric warming. Analyses of the atmospheric water balance highlight contributions to the increase in rainfall rate from both increased circulation strength and atmospheric moisture. Storm rainfall rate shows contrasting response to global warming during TC and extratropical transition periods. During the TC phase, Irene shows a significant increase of storm rainfall rate in inner core regions. This increase shifts to outer rainbands as Irene undergoes extratropical transition, collocated with the maximum tangential wind increase and the change of secondary circulation strength. Changes of storm track from the control run to global warming projections play a role in the change of spatial rainfall pattern. Distinct roles of surface and atmospheric warming in storm rainfall and structure changes are also examined.

Investigating the temporal dynamics of rainfall in a changing climate, especially in rainfed agriculture regions, is crucial for analyzing climate-induced changes and offering adaptation options. Since Mizoram experiences unfavorable impacts of rain nearly every year, the region rainfall has been altering over the years, and vital climatic activity is becoming uncontrollable. The current study is primarily concerned with the changing trend of rainfall over Mizoram, which includes both short-term persistence (STP) and long-term persistence (LTP) of rainfall in seasonal and annual time series of rainfall overseeing for the period of 25 years of daily average rainfall from 1996 to 2020 collected collectively from the seven stations over the study area of Mizoram. Four different Mann-Kendall method iterations were used to analyze rainfall trends: the original or conventional method (without autocorrelation) (MnKn1), removing lag-1 autocorrelation (trend-free pre-whitening), considering multiple lag autocorrelation (more than lag-1 autocorrelation) (MnKn3), and Hurst coefficient or LTP (MnKn4). In the analysis, the study found that during monsoon, station Lawngtlai (LT) observed the highest rainfall having a Z value of 1.986, increased by 0.466 cm/year, while station Serchhip (SC) observed the lowest rainfall having Z value of −2.282, decreased by −0.163 cm/year. After applying modified MnKn4, we observed LTP of rainfall in winter at station Lawngtlai (LT) with an increasing trend and other stations observing STP in almost all seasons either increasing or decreasing trend. Therefore, possible climate change adaptation measures should be made to optimize rainfall use for various applications for the states of Mizoram. [ABSTRACT FROM AUTHOR]

Climate change represents an overwhelming challenge that demands urgent intervention for effective resolution. Among the devastating consequences of climate change, flash floods stand out as one of the most catastrophic repercussions. This research focuses on two primary objectives. Firstly, it aims to evaluate the existing state of flash flood intensity (FFI) in a specific area of Hamamatsu city, Japan, which frequently experiences flash flood incidents. Secondly, it seeks to develop a mitigation plan to alleviate the adverse impacts of flooding on buildings within the area. To accomplish these objectives, four parameters related to FFI (namely, runoff depth, runoff velocity, runoff duration, and affected portion) were selected and estimated through the implementation of hydrological and hydrodynamic models. Additionally, a hydrological model was employed, utilizing a storm event with a return period of 100 years as input. During this simulated storm event, FFI values were calculated and categorized into four distinct levels. The results revealed that more than one-tenth of the examined buildings encountered the highest scale of FFI (category 4), while categories 3 and 4 combined accounted for nearly three-quarters of all buildings in the study area. Moreover, two mitigation strategies were adopted to prevent flooding within the buildings' vicinity. Finally, this study provides a valuable framework and guidance for decision-makers and insurance companies, enabling them to assess the flood hazard status of buildings and make informed decisions accordingly. [ABSTRACT FROM AUTHOR]

Model studies suggest that semiarid ecosystems with patterned vegetation can respond in a nonlinear way to climate change. This means that gradual changes can result in a rapid transition to a desertified state. Previous model studies focused on the response of patterned semiarid ecosystems to changes in mean annual rainfall. The intensity of rain events, however, is projected to change as well in the coming decades. In this paper, we study the effect of changes in rainfall intensity on the functioning of patterned semiarid ecosystems with a spatially explicit model that captures rainwater partitioning and runoff-runon processes with simple event-based process descriptions. Analytical and numerical analyses of the model revealed that rainfall intensity is a key parameter in explaining patterning of vegetation in semiarid ecosystems as low mean rainfall intensities do not allow for vegetation patterning to occur. Surprisingly, we found that, for a constant annual rainfall rate, both an increase and a decrease in mean rainfall intensity can trigger desertification. An increase negatively affects productivity as a greater fraction of the rainwater is lost as runoff. This can result in a shift to a bare desert state only if the mean rainfall intensity exceeds the infiltration capacity of bare soil. On the other hand, a decrease in mean rainfall intensity leads to an increased fraction of rainwater infiltrating in bare soils, remaining unavailable to plants. Our findings suggest that considering rainfall intensity as a variable may help in assessing the proximity to regime shifts in patterned semiarid ecosystems and that monitoring losses of resource through runoff and bare soil infiltration could be used to determine ecosystem resilience. [ABSTRACT FROM AUTHOR]

As a dynamical system approaches its critical threshold, the probability density distribution of the system will change significantly. Therefore, it is possible to present an early warning signal based on the changing skewness before reaching the critical threshold. Based on a zero‐dimensional climate model and several typical fold models, this paper systematically studies the influence of noise and missing data on the performance of the skewness coefficient as an early warning signal of an abrupt climate change. The results in three types of fold models show that the skewness coefficient has anti‐noise ability to some extent, but strong noise will significantly reduce the magnitude of the skewness coefficient and the time for early warning will also be shortened. In some cases, strong noise even will lead to the result that the skewness does not work in warning an impending abrupt change. However, the influence of strong noise on skewness is insignificant in the zero‐dimensional climate model. Therefore, the influence of strong noise needs to be considered in the practical application of the skewness coefficient as an early warning signal of an abrupt change. In addition, the results of all the models also indicate that different degrees of the missing data have no statistically significant effect on the warning performance of the skewness coefficient, even when the length of the missing data is up to 20% of the total sample size used in the present paper. [ABSTRACT FROM AUTHOR]

The accurate representation of rainfall in models of global climate has been a challenging task for climate modelers owing to its small space and time scales. Quantifying this variability is important for comparing simulations of atmospheric behavior with real time observations. In this regard, this paper compares both the statistical and dynamically forced aspects of precipitation variability simulated by the high-resolution (36 km) Nested Regional Climate Model (NRCM), with satellite observations from the Tropical Rainfall Measuring Mission (TRMM) 3B42 dataset and simulations from the Community Atmosphere Model (CAM) at T85 spatial resolution. Six years of rainfall rate data (2000-2005) from within the Tropics (30°S-30°N) have been used in the analysis and results are presented in terms of long-term mean rain rates, amplitude and phase of the annual cycle and seasonal mean maps of precipitation. Our primary focus is on characterizing the annual cycle of rainfall over four land regions of the Tropics namely, the Indian Monsoon, the Amazon, Tropical Africa and the North American monsoon. The lower tropospheric circulation patterns are analyzed in both the observations and the models to identify possible causes for biases in the simulated precipitation. The 6-year mean precipitation simulated by both models show substantial biases throughout the global Tropics with NRCM/CAM systematically underestimating/overestimating rainfall almost everywhere. The seasonal march of rainfall across the equator, following the motion of the sun, is clearly seen in the harmonic vector maps. The timing of peak rainfall (phase) produced by NRCM is in closer agreement with the observations compared to CAM. However like the long-time mean, the magnitude of seasonal mean rainfall is greatly underestimated by NRCM throughout the Tropical land mass. Some of these regional biases can be attributed to erroneous circulation and moisture surpluses/deficits in the lower troposphere in both models. Overall, the results seem to indicate that employing a higher spatial resolution (36 km) does not significantly improve simulation of precipitation. We speculate that a combination of several physics parameterizations and lack of model tuning gives rise to the observed differences between NRCM and the observations. [ABSTRACT FROM AUTHOR]

The impact of vegetation-atmosphere and ocean-atmosphere interactions on the mid- to late Holocene climate change as well as their synergy is studied for different parts of the Asian monsoon region, giving consideration to the large climatic and topographical heterogeneity in that area. We concentrate on temperature and precipitation changes as the main parameters describing monsoonal influenced climates. For our purpose, we analyse a set of coupled numerical experiments, performed with the comprehensive Earth system model ECHAM5/JSBACH-MPIOM under present-day and mid-Holocene (6 k) orbital configurations (Otto et al., 2009b). The temperature change caused by the insolation forcing reveals an enhanced seasonal cycle, with a pronounced warming in summer (0.58 K) and autumn (1.29 K) and a cooling in the other seasons (spring: -1.32 K; winter: -0.97 K). Most of this change can be attributed to the direct response of the atmosphere, but the ocean, whose reaction has a lagged seasonal cycle (warming in autumn and winter, cooling in the other seasons), strongly modifies the signal. The simulated contribution of dynamic vegetation is small and most effective in winter, where it slightly warms the near-surface atmosphere (approx. 0.03 K). The temperature difference attributed to the synergy is on average positive, but also small. Concerning the precipitation, the most remarkable change is the postponement and enhancement of the Asian monsoon (0.46 mm/day in summer, 0.53 mm/day in autumn), mainly related to the direct atmospheric response. On regional average, the interactive ocean (ca. 0.18 mm/day) amplifies the direct effect, but tends to weaken the East Asian summer monsoon and strongly increases the Indian summer monsoon rainfall rate (0.68 mm/day). The influence of dynamic vegetation on precipitation is comparatively small (<0.04 mm/day). The synergy effect has no influence, on average. [ABSTRACT FROM AUTHOR]