Climatological Differences Research Articles

Deforestation‐Driven Increases in Shallow Clouds Are Greatest in Drier, Low‐Aerosol Regions of Southeast Asia

AbstractAnthropogenic activity drives extensive tropical deforestation, particularly in Southeast Asia where 16% of total forest cover was lost between 2000 and 2020. While land surface changes significantly affect the atmosphere, their net impact on convective clouds is not well‐constrained. Here, we use satellite data to demonstrate long‐term deforestation in Southeast Asia robustly alters cloud properties and provide the first observational evidence that the magnitude of this response depends on the atmospheric environment. Deforestation drives a shift toward more widespread, shallower clouds during the daytime, with amplified effects in dry inland areas compared with moist coastal regions. Aerosols only weakly modulate the cloud fraction response, but offset the cloud top height response to deforestation, suggesting the influence of aerosol indirect effects. We conclude that the local signature of forest loss is not uniform, and regional differences in climatology must be considered when assessing deforestation impacts on clouds and the climate system.

Retrieval of cherry flowering phenology on Flickr and YouTube: a case study along the Tarumi railway, Gifu, Japan

To further develop the accuracy of monitoring cherry flowering dates, we require phenological records from multiple points in multiple years at the catchment scale, as well as conventional in situ phenological observations, phenological data published on the Internet, and analysis using statistics of Internet search engines. We tried to detect the dates of cherry flowering phenology along the Tarumi railway, Gifu Prefecture, Japan, by using Flickr, an image hosting service, and YouTube, an online video sharing and social media platform. We detected full bloom of Cerasus ×yedoensis and Cerasus jamasakura mainly at cherry blossom viewing spots (around some train stations) on Flickr and at both viewing spots and multiple points in the landscape along the railway on YouTube. Despite local climatological differences along the railway, the detected full blooming dates corresponded not only with each other, but also with the full bloom period of Neodani Usuzumi-zakura (Cerasus itosakura), a famous tree with long-term detailed records. We could not detect the date and location in many photographs on Flickr or in any videos on YouTube. However, the usefulness of both platforms is supported by the facts that we can evaluate the year-to-year variability of full bloom dates, especially at cherry blossom viewing spots, and detect flowering phenology even in a non-photogenic landscape. By applying our method to other railways, we expect to collect multi-year records of plant phenology dates at multiple points that cannot be collected by older methods.

Development and application of a bioenergetics growth model for multiple early life stages of an ecologically important marine fish

Spatial and temporal variability in temperature and food availability are key drivers of growth of marine fishes. Growth during the early life stages (ELS's) is tightly coupled to survival, and in turn, can set year-class strength (i.e. annual recruitment) and overall stock productivity of populations and fished stocks. Ontogenetic changes in physiology, dietary preferences, and growth across ELS's can be accounted for within bioenergetics models, but existing models lack resolution within larval and early juvenile stages. We leveraged daily output from a coupled physical-biogeochemical model to force a highly resolved ontogenetic bioenergetics model parametrized for an ecologically important rockfish in the California Current System. Size-at-age predictions closely track empirical growth trajectories of the ELS's. Scenario testing revealed that growth performance is disproportionately driven by changes in temperature compared to food availability. We then expanded the model to incorporate spatial climatological differences in temperature and prey concentration and found that preflexion growth potential is maximized in areas of historical spawning, suggesting the timing and location of reproduction is an adaptive strategy that places larvae in habitat favorable for survival. Growth potential for late-stage larvae (postflexion) is greatest over a broad areal extent, implying that if a particle tracking algorithm was coupled to the bioenergetics model, a wide range of larval dispersal pathways would place postflexion larvae in habitat suitable for rapid growth. Finally, growth potential of pelagic juveniles is maximized over the continental shelf and shelf-break, aligning with high juvenile catch rates from a fisheries-independent survey. In summary, this study (i) serves as a proof of concept that a bioenergetics model with high ontogenetic resolution can reproduce life stage-specific growth trajectories even though the underlying physiology data for model parameterization is imperfect and (ii) can aid future studies aimed at understanding how ecosystem processes interact with ontogenetic growth and changes in year class strength of early life stages of marine fishes.

Statistical and hydrodynamic numerical modeling to quantify storm surge hazard: Comparison of approaches applied to U.S. North Atlantic coast

Estimating the storm surge magnitude and annual exceedance probability is a key element in the siting and design of coastal nuclear power plants in both the U.S. and France. However, differences in storm climatology, specifically the relative importance of tropical cyclones (TCs) versus extratropical storms (XTCs), have driven differences in estimation method development. This work compares purely statistical modeling with combined statistical and numerical simulation modeling approaches for extreme storm surge applied to the U.S. North Atlantic coast which is subject to both tropical and extratropical storms. Two frequency analysis methods are applied to observed water levels and compared to a copula-based joint probability analysis of TCs and automated frequency analysis of XTCs that is enriched with numerically simulated storms. One frequency analysis method is applied using (1) hourly at-site data and (2) hourly at-site data enriched with additional data from a homogeneous region. The other frequency analysis method is applied using (1) hourly at-site data and (2) hourly at-site data enriched with monthly water level maxima. Variables of interest used in the comparison are skew storm surge, maximum instantaneous storm surge, non-tidal residual and maximum seal level. The performance of the methods (mean surge and water level estimates and confidence intervals) depend on the variable of interest and, to some extent, on return period. Inclusion of additional information (e.g., regional water levels, and monthly maxima) in the frequency analysis methods does not have a large impact on estimated mean surge and water levels, but significantly reduces resulting confidence intervals (over 40% reduction in some cases). However, the confidence intervals still grow with increasing return period. Inclusion of simulated storms in the joint probability analysis results in significantly different mean surge and water level estimates (up to 25% higher than the frequency analysis in some cases). The joint probability analysis confidence intervals are wider than those for the frequency analysis methods lower return periods (e.g., 60%–80% wider at 100 years), but they grow much more slowly and are significantly narrower for higher return periods (e.g., 40%–60% narrower at 1 000 years). Although there are appreciable differences between the results documented in this paper, these are reasonable due to differences in the data and methods used in this comparison.

Wharton, Writing, and Nature

Abstract Although past critics of Wharton’s work have focused on the social world she depicts, Wharton also presents the natural world in her work, from poems she wrote as a teenager through her late writings. Using Thomas Lyon’s “Taxonomy of Nature Writing” (1989), this article looks at a range of Wharton’s work to argue that she is indeed a “nature writer.” Wharton’s work in Italian Villas and Their Gardens and A Motor-Flight Through France meditate on the relationship between landscape and human habitation, and her lifelong experiences of gardening in various climates deepened her ecological understanding of climatological differences. Wharton’s first published story “Mrs. Manstey’s View” argues for the importance of nature even in an urban setting, while also creating a character who is a phenologist (someone who studies seasonal cycles); much later in her career, her paired novels Hudson River Bracketed and The Gods Arrive not only demonstrate Wharton’s own skill as a nature writer, but also convey the importance of nature, both cosmic and local, as inspiration to the writer. Finally, the article suggests that Wharton’s attentiveness to nature may have made her a better writer; moreover, it asks readers to consider Wharton’s depictions of nature as they consider today’s ecological crisis.

Evaluating the Influence of CAM5 Aerosol Configuration on Simulated Tropical Cyclones in the North Atlantic

This study examines the influence of prescribed and prognostic aerosol model configurations on the formation of tropical cyclones (TCs) in the North Atlantic Ocean in Community Atmosphere Model version 5 (CAM5). The impact of aerosol parameterization is examined by investigating storm track density, genesis density, potential intensity, and genesis potential index. This work shows that both CAM5 configurations simulate reduced storm frequency when compared to observations and that differences in TC climatology between the model configurations can be explained by differences in the large-scale environment. The analysis shows that simulation with the prognostic aerosol parameterization scheme reasonably captures the observed interannual variability in tropical cyclones and aerosols (i.e., dust) in the North Atlantic, while simulation with the prescribed configuration (climatology) is less favorable. The correlation between dust and TCs in observations (i.e., reanalysis and satellite datasets) is shown to be negative, and this relationship was also found for the prognostic aerosol configuration despite an overall decrease in the frequency of TCs. This indicates that, to accurately replicate certain aspects of TC interannual variability, the aerosol configuration within CAM5 needs to account for the appropriate dust variability.

Dynamics of Diurnal Precipitation Differences and Their Spatial Variations in China

Abstract Systematic analyses of the daytime and nocturnal precipitation changes provide a better understand of the impact of global warming on the environment. In this study, the daytime and nocturnal precipitation across China from 1990 to 2019 was analyzed using observational data from 698 meteorological stations. Both daytime and nocturnal precipitation have increased in the western parts of China (including the Continental basin, headwaters of the Yangtze River basin, and Yellow River basin), whereas the trends in the eastern part are more complex. Climatological differences between daytime and nocturnal precipitation in summer were more significant than in other seasons. We developed a Z index to quantify the diurnal differences of precipitation. The annual mean Z index of China is about −2%, and its long-term change on an annual basis increased at a rate of 0.06% yr−1 (p < 0.1). The mean Z-index values during the year and seasons (except for summer) are negative and show an increasing trend. The intensity of the diurnal differences of precipitation has been decreasing in China since 1990. Topographic exposure and distance from the coast also influence the daytime and nocturnal precipitation changes. The Z index of the first-category stations (distance from the coast ≤ 100 km) was positively correlated with the distance from the coast (r = 0.39; p < 0.001) in summer, which may result from the superposition of the summer monsoon and sea-breeze effects. Significance Statement The diurnal cycle of precipitation is an important indicator for diagnosing the impact of global warming on the environment. There is a slight annual difference between daytime and nocturnal precipitation in China. The nocturnal precipitation maximum is in winter, spring, and autumn and the opposite occurs in summer. We define a precipitation index to quantifying the intensity of the diurnal differences of precipitation. The mean precipitation index is negative annually and seasonally (except for summer), with an increasing trend indicating that the intensity of the diurnal differences of precipitation has decreased in China from 1990 to 2019. These results are valuable for understanding the impact of recent warming on the diurnal differences of precipitation in China.

Resolution Dependence of Atmosphere–Ocean Interactions and Water Mass Transformation in the North Atlantic

AbstractWater mass transformation (WMT) in the North Atlantic plays a key role in driving the Atlantic Meridional Overturning Circulation (AMOC) and its variability. Here, we analyze subpolar North Atlantic WMT in high‐ and low‐resolution versions of the Community Earth System Model version 1 (CESM1) and investigate whether differences in resolution and climatological WMT impact low‐frequency AMOC variability and the atmospheric response to this variability. We find that high‐resolution simulations reproduce the WMT found in a reanalysis‐forced high‐resolution ocean simulation more accurately than low‐resolution simulations. We also find that the low‐resolution simulations, including one forced with the same atmospheric reanalysis data, have larger biases in surface heat fluxes, sea‐surface temperatures, and salinities compared to the high‐resolution simulations. Despite these major climatological differences, the mechanisms of low‐frequency AMOC variability are similar in the high‐ and low‐resolution versions of CESM1. The Labrador Sea WMT plays a major role in driving AMOC variability, and a similar North Atlantic Oscillation‐like sea‐level pressure pattern leads AMOC changes. However, the high‐resolution simulation shows a pronounced atmospheric response to the AMOC variability not found in the low‐resolution version. The consistent role of Labrador Sea WMT in low‐frequency AMOC variability across high‐ and low‐resolution coupled simulations, including a simulation which accurately reproduces the WMT found in an atmospheric‐reanalysis‐forced high‐resolution ocean simulation, suggests that the mechanisms may be similar in nature.

Influence of the ripening chamber’s geographical location on dry-cured Iberian ham’s key odorants

Olfactometric and sensory analyses have been applied to study the possible influence of the ripening chamber’s geographical location on the aroma sensory profiles and key odorants of Iberian ham. Dry-cured Iberian ham was obtained from 3 acorn-fed pigs and, for the first time, both of the participating production facilities, located in two different Andalusian municipalities with different altitudes above mean sea level, processed one of the two hind legs from each pig. The descriptive sensory profile of orthonasal and retronasal odours was determined by trained panellists, while odour-active compounds were determined by gas chromatography/mass spectrometry-olfactometry (GC/MS-O). The results obtained showed that, separately, both techniques enable Iberian ham samples to be differentiated by their ripening chamber’s geographical location. For sensory analysis, retronasal sensory analysis appeared to be the most suitable for this goal, highlighting the “meat broth odour” and “roasted nuts odour” descriptors which presented significant differences between geographical locations for samples from all pigs. Moreover, ripening chamber’s geographical location characteristics and the initial composition of the raw material seemed to influence the content of some odour-active compounds. The odour-active compound identified as octane/acetone and isobutanol were conditioned by the ripening chamber’s geographical location, while decanal/2-ethyl-1-hexanol, 1-undecanol, 2-furanmethanol and cis-2-nonenal were also influenced by the individual pig itself. This study showed that slight climatological differences due to the location of the ripening chamber seem to have somewhat of an influence on the aromatic profile.

Characterizing winter season severity in the Midwest United States, Part I: Climatology and recent trends

AbstractSevere winter weather is a staple of Midwest United States (U.S.) climate and is an important natural hazard that has significant economic and environmental impacts. Winter season severity varies both spatially and temporally in the Midwest, and past studies have documented significant changes in Midwest winter characteristics, including increases in temperature and decreases in snow depth. In this study, we use the Accumulated Winter Season Severity Index (AWSSI) to characterize winter severity across the Midwest and assess its variability and change on various spatial and temporal scales during the 1951–2020 period. AWSSI is derived from daily records of snowfall (SF), snow depth (SD), maximum surface air temperature (TMAX), and minimum surface air temperature (TMIN) during the winter season. The daily total AWSSI index value reflects the sum of points accumulated from daily values of each of these four variables surpassing pre‐determined thresholds, and the total season sum reflects the overall winter season severity. We find AWSSI provides a unique perspective by which to describe climatological differences in winter season character in the Midwest. Namely, over three quarters of winter season days accumulate points in the northern Midwest, compared to just over half in the southern Midwest. Meanwhile, the relative contribution of extreme winter days to total winter severity is much larger in the southern Midwest than farther north. In addition, we find overall winter season severity has significantly decreased at only a quarter of stations and the frequency of extreme winter days has significantly decreased at only a fifth of stations, despite widespread increases in winter daily maximum and minimum temperature. The results suggest Midwest U.S. winter season severity as described by the AWSSI has not significantly changed over the past 70 years.

A New Framework for Identifying and Investigating Seasonal Climate Extremes

AbstractPrevious studies have recognized the societal relevance of climatic extremes on the seasonal time scale and examined physical processes leading to individual high-impact extreme seasons (e.g., extremely wet or warm seasons). However, these findings have not yet been generalized beyond case studies since at any specific location only very few seasonal events of such rarity occurred in the observational record. In this concept paper, a pragmatic approach to pool seasonal extremes across space is developed and applied to investigate hot summers and cold winters in ERA-Interim and the Community Earth System Model Large Ensemble (CESM-LENS). We identify spatial extreme season objects as contiguous regions of extreme seasonal mean temperatures based on statistical modeling. Regional pooling of extreme season objects in CESM-LENS then yields considerable samples of analogs to even the most extreme ERA-Interim events. This approach offers numerous opportunities for systematically analyzing large samples of extreme seasons, and several such analyses are illustrated. We reveal a striking co-occurrence of El Niño to La Niña transitions and the largest ERA-Interim midlatitude extreme summer events. Moreover, we perform a climate model evaluation with regard to extreme season size and intensity measures and estimate how often an extreme winter like the cold North American 2013/14 winter is expected anywhere in midlatitude regions. Furthermore, we present a large set of simulated analogs to this event, which makes it possible to study commonalities and differences of their underlying physical processes. Finally, substantial but spatially varying climatological differences in the size of extreme summer and extreme winter objects are identified.

Temperature thresholds of ecosystem respiration at a global scale.

Ecosystem respiration is a major component of the global terrestrial carbon cycle and is strongly influenced by temperature. The global extent of the temperature-ecosystem respiration relationship, however, has not been fully explored. Here, we test linear and threshold models of ecosystem respiration across 210 globally distributed eddy covariance sites over an extensive temperature range. We find thresholds to the global temperature-ecosystem respiration relationship at high and low air temperatures and mid soil temperatures, which represent transitions in the temperature dependence and sensitivity of ecosystem respiration. Annual ecosystem respiration rates show a markedly reduced temperature dependence and sensitivity compared to half-hourly rates, and a single mid-temperature threshold for both air and soil temperature. Our study indicates a distinction in the influence of environmental factors, including temperature, on ecosystem respiration between latitudinal and climate gradients at short (half-hourly) and long (annual) timescales. Such climatological differences in the temperature sensitivity of ecosystem respiration have important consequences for the terrestrial net carbon sink under ongoing climate change.

The summer precipitation response of latewood tree‐ring chronologies in the southwestern United States

AbstractLatewood width tree‐ring chronologies from arid‐site conifers in the southwestern United States are correlated with precipitation during portions of the summer monsoon season. The onset date and length of the monsoon season varies across the region, and these regional differences in summer rainfall climatology may impact the strength and timing of the warm season precipitation response of latewood chronologies. The optimal latewood response to summer precipitation is computed on a daily basis using 67 adjusted latewood chronologies (LWa) from the southwestern United States, adjusted to remove correlation with preceding earlywood growth. Most LWa chronologies are significantly correlated with precipitation summed over a period of approximately 4 weeks (29 days) in early summer. This early summer precipitation signal is present in most ponderosa pine chronologies across the study area. It is also evident in Douglas‐fir chronologies, but only from southern Arizona and New Mexico. The Julian date of summer precipitation onset increases from south to north in the instrumental precipitation data for the southwestern United States. The timing of the early summer season precipitation response in most LWa chronologies also tends to occur later in the summer from southeastern Arizona into northern New Mexico and eastern Colorado. Principal components analysis of the LWa chronologies reproduces two of the three most important spatial modes of early summer precipitation covariability seen in the instrumental data. The first PC of LWa is related to the same atmospheric circulation features associated with PC1 of instrumental early summer precipitation, including cyclonic circulation over the southwestern United States and moisture advection from the eastern Pacific. Correlation analyses between antecedent cool season precipitation and early summer rainfall using instrumental and tree‐ring reconstructed precipitation indicates that the tree‐ring data reproduce the multi‐decadal variability in correlation between seasons seen in the instrumental data.

Climatological influence of land and atmospheric initial conditions on North America and Eurasia surface temperature and circulation in the past 57 years (1958–2014) reforecasts

This study demonstrates the potential impact of land and atmospheric initial conditions (ICs) on the mean state of land surface temperature (SKT) and mid-troposphere circulation over Eurasia and North America (NA) using the Climate Forecast System version-2 (CFSv2) ensemble seasonal reforecasts for 1958–2014. The land ICs and atmosphere ICs have assembled from several different data sources before and after 1979 in January initialized reforecasts (JIR). Therefore, two-time periods have defined, earlier period (1958–1978) and later period (1994–2014). The climatological difference between JIR P58-78 and P94-14 depicts enhanced cold SKT and sub-surface temperature at 0–10 cm over northern Eurasia and northeast region of NA from May to June. Model overestimates snow cover fraction from May to June in JIR P58-78 than JIR P94-14, which leads to excessive upwards-shortwave radiation in the northern latitudes. Due to cold temperature from the surface to mid-troposphere, model depicts lower geopotential heights in mid-troposphere, which leads to increase westerly winds at mid-troposphere over northern latitudes from May to June. The climatological differences between earlier and later periods of JIR from May to June are similar to differences between reforecasts initialized in winter and spring as reported by some recent studies. The climatological difference between JIR P58-78 and P94-14 depicts enhanced cooling from surface to 600 hPa over northern latitudes in January. As lead months increase, the magnitude of cold temperature decreases gradually from February to March. Most prominent centers of geopotential height from surface to mid-troposphere over northern latitude in climatological differences between earlier and later periods of JIR in January vanish in February. The different sources of ICs and the nature of land conditions before and after 1979 are main causes of large differences in JIR from May to June over northern latitudes.

An Index Intercomparison for MJO Events and Termination

AbstractThe Madden‐Julian oscillation (MJO) is a significant contributor to climate variability in the tropics. While many studies have examined the MJO, few have considered its termination. Multiple indices exist to track and forecast the MJO although the influence of each index on MJO decay has not been documented. This study presents an intercomparison of several MJO indices for a 34‐year period to examine the evolution of MJO events and comprises an index‐specific climatology for MJO termination. We present an analysis of common indices including the OLR‐based MJO index (OMI) and filtered OMI (FMO) in addition to the real‐time multivariate MJO (RMM) and velocity potential MJO (VPM) index. Normalized empirical orthogonal function comparisons reveal only minor shifts in longitude and time in the corresponding convection and circulation anomalies between indices. The daily rate‐of‐change (ROC) for each index is derived, and we find that the RMM and VPM indices experience twice as large of daily amplitude changes as the univariate indices. Results from the ROC analysis are implemented in an MJO event identification algorithm to study the sensitivity of MJO termination to changes in the temporary minimum amplitude and threshold used to define events. The corresponding counts of primary, continuing, and circumnavigating events are recorded with primary events being robust to changes in the temporary minimum amplitude. Finally, an MJO climatology is created that presents MJO termination as a function of phase for each index. Physical reasons behind differences in the termination climatology are proposed in addition to applications for future work.

Quantifying uncertainties of climate signals in chemistry climate models related to the 11-year solar cycle – Part 1: Annual mean response in heating rates, temperature, and ozone

Abstract. Variations in the solar spectral irradiance (SSI) with the 11-year sunspot cycle have been shown to have a significant impact on temperatures and the mixing ratios of atmospheric constituents in the stratosphere and mesosphere. Uncertainties in modelling the effects of SSI variations arise from uncertainties in the empirical models reconstructing the prescribed SSI data set as well as from uncertainties in the chemistry–climate model (CCM) formulation. In this study CCM simulations with the ECHAM/MESSy Atmospheric Chemistry (EMAC) model and the Community Earth System Model 1 (CESM1)–Whole Atmosphere Chemistry Climate Model (WACCM) have been performed to quantify the uncertainties of the solar responses in chemistry and dynamics that are due to the usage of five different SSI data sets or the two CCMs. We apply a two-way analysis of variance (ANOVA) to separate the influence of the SSI data sets and the CCMs on the variability of the solar response in shortwave heating rates, temperature, and ozone. The solar response is derived from climatological differences of time slice simulations prescribing SSI for the solar maximum in 1989 and near the solar minimum in 1994. The SSI values for the solar maximum of each SSI data set are created by adding the SSI differences between November 1994 and November 1989 to a common SSI reference spectrum for near-solar-minimum conditions based on ATLAS-3 (Atmospheric Laboratory of Applications and Science-3). The ANOVA identifies the SSI data set with the strongest influence on the variability of the solar response in shortwave heating rates in the upper mesosphere and in the upper stratosphere–lower mesosphere. The strongest influence on the variability of the solar response in ozone and temperature is identified in the upper stratosphere–lower mesosphere. However, in the region of the largest ozone mixing ratio, in the stratosphere from 50 to 10 hPa, the SSI data sets do not contribute much to the variability of the solar response when the Spectral And Total Irradiance REconstructions-T (SATIRE-T) SSI data set is omitted. The largest influence of the CCMs on variability of the solar responses can be identified in the upper mesosphere. The solar response in the lower stratosphere also depends on the CCM used, especially in the tropics and northern hemispheric subtropics and mid-latitudes, where the model dynamics modulate the solar responses. Apart from the upper mesosphere, there are also regions where the largest fraction of the variability of the solar response is explained by randomness, especially for the solar response in temperature.

Large-scale environmental controls on the seasonal statistics of rapidly intensifying North Atlantic tropical cyclones

This study is concerned with the connections between the large-scale environment and the seasonal occurrence of rapid intensification (RI) of North Atlantic tropical cyclones. Physically-motivated statistical analysis using observations and reanalysis products suggests that for tropical cyclones over the open tropical North Atlantic, the interannual variability of the probability of storms undergoing RI is influenced by seasonal large-scale atmospheric and oceanic variables, but not so for storms over the Gulf of Mexico and western Caribbean Sea. We suggest that this differentiated response is due to the former region exhibiting a strong negative correlation between the seasonal anomalies of vertical wind shear and potential intensity. Differences in the mean climatology and subseasonal variations of the large-scale environment in these regions appear to play an insignificant role in the distinctive seasonal environmental controls on RI. We suggest that the interannual correlation of vertical wind shear and potential intensity is an indicator of seasonal predictability of tropical cyclone activity (including RI) across the tropics .

Climatology Explains Intermodel Spread in Tropical Upper Tropospheric Cloud and Relative Humidity Response to Greenhouse Warming

AbstractThe response of upper tropospheric clouds and relative humidity (RH) to warming is important to the overall sensitivity of the Earth to increasing greenhouse gas concentrations. Previous research has shown that changes in hydrologic fields should closely track rising isotherms in a warming climate. Here we show that the distribution of tropical clouds and RH in general circulation models is approximately constant under greenhouse warming when using temperature as a vertical coordinate. By assuming that these fields are an invariant function of atmospheric temperature and that temperature change follows a dilute moist adiabat, we are able to accurately predict cloud fraction and RH changes in the tropical upper troposphere (150–400 hPa) in 27 general circulation models. Our results indicate that intermodel spread in changes of tropical upper tropospheric clouds and RH is closely related to differences in model climatology and could be substantially reduced if model ensembles reliably reproduced observed climatologies.

Regional growth curves and extreme precipitation events estimation in the steppe area of northwestern Algeria

A regional statistical analysis has been established for an improved estimate of extreme frequency precipitation in the steppe area of northwestern Algeria. This analysis made it possible to determine three homogeneous regions by using methods based on statistical procedures, such as the analysis of the ascendant hierarchical classification and the L-moments method. The regions thus defined accurately reflect the climatological differences and specific characters influencing precipitation patterns in the study area. The generalized extreme value (GEV) distribution has been identified as the most appropriate distribution for modeling annual maximum daily rainfall quantiles according to the L-moments ratio plot and fit-quality tests. Rainfall indices combined with the regional growth curves can evaluate in a reasonable way the maximum rainfall quantiles at the stations by using the mean maximum precipitations of the observation series. The regional approach has considerably reduced the differences caused by the disparity of the values taken by the shape parameter of the GEV distribution as a function of the observation sites, and the estimation of high quantiles becomes more spatially consistent in a region. Different forms of growth curves are characteristic for the three regions. The error reflected by the bias and root mean square error (RMSE) are below 16 and 25%, respectively, for a 100-year return period. The study provides an assessment of the maximum daily rainfalls that can be useful in the study of floods and the design of hydrotechnical works.

An Intercomparison of Noah Model Skills With Benefits of Assimilating SMOPS Blended and Individual Soil Moisture Retrievals

AbstractSoil moisture (SM) data from Soil Moisture Operational Product System (SMOPS) have been available and used by users since 2013, and the latest version (3.0) has been operationally released since 2017. The version 3.0 provides a combination of currently all available daily global microwave SM retrievals including observations of ASCATA, ASCATB, SMAP, SMOS, and AMSR2 from 1 April 2015 to present. This study intercompares Noah model skills with benefits of assimilating the SMOPS blended (hereafter, SMOPS) and the five individual satellite SM retrievals. Results show that SMOPS SM product presents a significant advantage in data availability in comparison with the individual SM retrievals. Significant differences in data availability, climatology, and dynamic range of SM values between the bias‐corrected SMOPS and individual SM data lead to remarkable distinctions in Noah model SM simulations. Significant improvements of assimilating individual and blended satellite SM retrievals on model SM simulations versus the open loop in both surface and root zone soil layers are evident with reducing the Soil Climate Analysis Network measurements‐based root mean square errors and raising the correlations with respect to the enhanced vegetation index. Compared to the individual SM assimilations, model SM estimations with benefits of assimilating the SMOPS data provide the more remarkable improvements in surface soil layer.