Frequency Of Rainy Days Research Articles

Assessment of mean precipitation and precipitation extremes in Iran as simulated by dynamically downscaled RegCM4

This paper aims to assess the mean precipitation and precipitation extremes over Iran as simulated by the Regional Climate Model (RegCM4). A simulation spanning 20 years (1991–2010) at a horizontal resolution of 20 Km is driven by the NCEP / NCAR reanalysis. We evaluated the model by comparing simulated precipitation with observations using Bias, Root-Mean-Square Error, and Index of Agreement metrics. We examined the extreme precipitations based on a set of extreme indices recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI) in three categories of intensity (Rx1day and SDII), duration (CDD and CWD), and frequency (R10mm and R20mm). The linear trends are calculated using the Theil–Sen estimator method, and the statistical significance (95% confidence level) is determined by using a modified Mann-Kendall (MMK) trend test. The RegCM4 model satisfactory captured the spatial distribution of precipitation and precipitation extremes, although high bias remained in small parts of Iran, including the northwest and southeast. The northwest bias is due to spring convectional precipitation and the southeast bias could be caused by precipitation from the Asian summer monsoon system, which both of them may not be well simulated by the applied Grell convective scheme. Results indicate that the model reasonably captures Rx1day, SDII, CWD, R10mm, and R20mm Indices over Iran. In good agreement with precipitation observations, the southern coast of the Caspian Sea represents the second-highest extreme precipitation, except for SDII, which is probably due to the high frequency of rainy days in this region. The highest CDD of more than 200 days is found in the arid and semi-arid regions of the southeast. In general, precipitation decreased in most regions of Iran, especially the western, southern, and interior regions. In addition, the results reveal that heavy (R10mm) and very heavy (R20mm) precipitation events have also decreased in the same regions. Results also emphasize an increase in consecutive dry days (CDD) in most parts, especially in the southeast, which deserves more attention in future research. The decreasing trend of precipitation and the increasing trend of CDD show that Iran has become drier in the 2000 s compared to the 1990 s

Observed changes in the contribution of extreme precipitation over the Zagros Mountains, Iran

Due to global warming, precipitation regimes are expected to change, and heavy events are expected to occur more frequently. This study investigates the relative share of heavy daily precipitation events to total precipitation for past and current climates. In this regard, daily precipitation data with a spatial resolution of 0.25° × 0.25° from the APHRODITE and CHIRPS databases are used. We used two nonparametric tests, the Mann–Kendall test and Sen’s slope estimator, to identify the trend. The results showed that the frequency of daily heavy precipitation has been increasing in most regions of Iran. The relative share of heavy daily precipitation events to total precipitation has increased over the southwest and central areas of Iran from a case of the past to the current climate. The rise in the share of heavy precipitation of the total precipitation has led to a decrease in the frequency of rainy days (wet days) and an increase in the intensity and concentration of precipitation in Iran. The amount of increase in the share of heavy rainfall to the total precipitation is more prominent in the middle parts of the Zagros Mountains. These conditions lead to heavy floods in the southwestern plains of Iran.

Combining mathematical and statistical algorithms for objectivity in the use of ogive for determining rainfall onset, peak, and retreat dates over Nigeria

<p><span lang="EN-GB">The study combined the second-order polynomial and some elements of algebra and trigonometry with the ogive to objectively (mathematically) locate the rainfall onset, peak, and retreat on the ogive, which was visually done. The data used for the investigation are the daily rainfalls of 16 synoptic stations (Ikeja, Calabar, Port-Harcourt, Benin, Ondo, Enugu, Ilorin, Lokoja, Jos, Kaduna, Yola, Kano, Sokoto, Maiduguri, Potiskum, and Nguru) across all the ecological zones of Nigeria. The datasets spanning 50 years (1971–2020) were collected from the Archives of the Nigerian Meteorological Services, Abuja, Nigeria. The ogives were derived from the frequency of rainy days. The peak periods were best detected from the pentad graphs of the rainy-day frequency. The results showed that rainy-day frequency is better than rainfall amount in determining the various rainfall parameters over Nigeria. The second-order polynomial modeled the two curvatures of the rainfall perfectly. The rainy-day frequency in the southern part of the country exhibited double rainfall maxima, while those in the northern part showed a single rainfall maximum. The double rainfall maxima are not peculiar to the southwestern region of Nigeria, as previously widely asserted; they cut across the whole southern region, although the number of days and the depth of the trough between the peaks dimmish from the largest values in the extreme southwest to the least in the extreme southeast. The first rainfall peaks were attained in southern Nigeria in July, except at Ikeja, which was in June. The second rainfall peak was reached in September in all the southern stations. The single peaks were attained in all the extreme northern stations in August and in the other stations south of them in early September. The rainfall onset begins at Ikeja in the extreme southwestern corner of Nigeria around March ending. It spreads eastwards and northwards to cover the entire country by mid-June, reaching Nguru in the northeastern corner. It is generally earlier on the western flank than the eastern flank. Rainfall begins to retreat from the northernmost stations by the third week in September to reach the extreme southern stations between October and early November.</span></p>

Changes in atmospheric circulation and evapotranspiration are reducing rainfall in the Brazilian Cerrado

Here we analyze the trends of rainfall and the frequency of rainy days over the Brazilian Cerrado between 1960 and 2021 in four distinct periods according to the seasonal patterns over the region. We also evaluated trends in evapotranspiration, atmospheric pressure, winds, and atmospheric humidity over the Cerrado to elucidate the possible reasons for the detected trends. We recorded a significant reduction in rainfall and frequency of rainy days in the northern and central Cerrado regions for all periods except at the beginning of the dry season. The most pronounced negative trends were recorded during the dry season and the beginning of the wet season, where we recorded reductions of up to 50% in total rainfall and the number of rainy days. These findings are associated with the intensification of the South Atlantic Subtropical Anticyclone, which has been shifting atmospheric circulation and raising regional subsidence. Moreover, during the dry season and the beginning of the wet season, there was a reduction in regional evapotranspiration, which also potentially contributed to the rainfall reduction. Our results suggest an expansion and intensification of the dry season in the region, potentially bringing broad environmental and social impacts that transcend the Cerrado boundaries.

Cardamom agro-environmental interrelationships analysis in Indian cardamom hills

The rainfall pattern seen in the Indian Cardamom Hills (ICH) has been extremely variable and complicated, with El Niño-Southern Oscillation (ENSO) playing a crucial role in shaping this pattern. In light of this, more investigation is required through improved statistical analysis. During the study period, there was greater variability in rainfall and the frequency of rainy days. About 2,730 mm of rainfall was reported in 2018, while the lowest amount (1168.3 mm) was registered for 2016. The largest decrease in decadal rainfall (>65 mm) was given by the decade 1960–1969, followed by 1980–1989 (>40 mm) and 2010–2019 (>10 mm). In the last 60 years of study, there has been a reduction of rainy days by 5 days in the last decade (2000–2009), but in the following decade (2010–2019), it registered an increasing trend, which is only slightly <2 days. The highest increase in decadal rainy days was observed for the 1970–1979 period. The smallest decadal increase was reported for the last decade (2010–2019). Total sunshine hours were the highest (1527.47) for the lowest rainfall year of 2016, while the lowest value (1,279) was recorded for the highest rainfall year (2021). The rainfall characteristics of ICH are highly influenced by the global ENSO phenomenon, both positively and negatively, depending on the global El Nino and La Nina conditions. Correspondingly, below and above-average rainfall was recorded consecutively for 1963–1973, 2003–2016, and 1970–2002. Higher bright forenoon sun hours occurred only during SWM months, which also reported maximum disease intensity on cardamom. The year 2016 was regarded as a poorly distributed year, with the lowest rainfall and the highest bright afternoon sun hours during the winter and summer months (January-May). Over the last three decades, the production and productivity of cardamom have shown a steady increase along with the ongoing local climatic change. Many of our statistical tests resulted in important information in support of temporal climatic change and variability. Maintaining shade levels is essential to address the adverse effects of increasing surface air temperature coupled with the downward trend of the number of rainy days and elevated soil temperature levels.

Evaluations of satellite/reanalysis rainfall and temperature products in the Bale Eco-Region (Southern Ethiopia) to enhance the quality of input data for hydro-climate studies

The sparse distribution and lack of meteorological stations due to deficit infrastructure in developing countries is one of the limiting factors for hydro-climate studies, and dependency on globally available data is often prone to various level of errors. Thus, this study aimed to evaluate the performance of satellite/reanalysis rainfall and temperature products in the Bale Eco-Region (BER) in Southern Ethiopia. This study evaluated performances of three rainfall products such as the Climate Hazards Group Infrared Precipitation with Stations, version 2.0 (CHIRPS v2.0), Tropical Applications of Meteorology using SATellite and ground-based observations, version 3.1 (TAMSAT v3.1) and Multi-Source Weighted-Ensemble Precipitation, version 2.8 (MSWEP v2.8). The two temperature products evaluated in this study are ERA5 and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA v2). Evaluations of these satellite/reanalysis rainfall and temperature products were undertaken against observed data (1995–2014) in temperate, sub-tropical and tropical agro-ecological zones (AEZs) across multiple temporal scales ranging from the daily to annual. For assessing the performances of satellite/reanalysis rainfall and temperature products, a point-pixel evaluation approach was undertaken using five continuous evaluation scores such as correlation coefficient (R), mean absolute error (MAE), root mean square error (RMSE), percent bias (PBIAS) and Kling–Gupta efficiency (KGE). Categorical sores such as Probability of Detection (POD), False Alarm Ratio (FAR) and Frequency Bias Index (FBI) were also used for assessing the rainfall products. The findings revealed that MSWEP v2.8 has better performance than CHIRPS v2.0 and TAMSAT v3.1 in temperate and tropical AEZs at the daily, dry season and annual time steps as well as in sub-tropical AEZ in dry season and annual temporal periods, but MSWEP v2.8 displayed comparable performance with TAMSAT v3.1 in the daily time step. CHIRPS v2.0 exhibit superior performance in the monthly time scale in the three AEZs as well as in the wet season in temperate and tropical AEZs, but TAMSAT v3.1 has outperformed than CHIRPS v2.0 in the wet season in sub-tropical AEZ. The finding also indicated that the capability of MSWEP v2.8 to detect the rainy days (79–86%) and frequency of rainy days (0.99–1.79) is better than CHIRPS v2.0 and TAMSAT v3.1, but TAMSAT v3.1 has shown the best performance for identifying the non-rainy days (14–38%) than MSWEP v2.8 and CHIRPS v2.0. With regard to temperature, MERRA v2 outperformed over ERA5 in temperate and tropical AEZs for estimating both maximum and minimum temperatures from the daily to annual time scales, but ERA5 has shown superior performance than MERRA v2 in the sub-tropical AEZ. In view of the finding, we concluded that the best performing rainfall and temperature products for each AEZ can be used for data scarce regions such as the BER. The findings of this study provide important insights about the need to identify best performing rainfall and temperature products for different AEZs to enhance the quality of hydro-climate study outputs in the decision-making process.

Changes in extreme precipitation events in the Zambezi River basins based on CORDEX‐CORE models: Part I—Evaluation of historical simulation

AbstractThis study evaluates the ability of the Coordinated Output for Regional Evaluations (CORE) initiated under the Coordinated Regional Climate Downscaling Experiment (CORDEX) to reproduce austral summer extreme precipitation indices over the Zambezi River basin (ZRB) from 1983 to 2005. The ability of the RCMs to simulate the spatial distributions of observed extreme precipitation was assessed using multiple datasets. The spatially averaged performance of the CORDEX‐CORE ensemble mean (CORE‐ENS) and RCM ensembles (RCM‐ENSEMBLES developed from different combinations of CORE‐ENS ensemble members) was evaluated using statistical metrics. The results showed similarities in the spatial distribution of extreme precipitation among the observations. However, there were considerable differences in the magnitude of extreme precipitation among the observations. The frequency of days with very heavy precipitation (R20) showed the largest differences in magnitude among the observations. Although there are differences in magnitude, CORE‐ENS, its ensemble members, and RCM‐ENSEMBLES can capture the spatial distribution of extreme precipitation. Specifically, CORE‐ENS, its ensemble members, and RCM‐ENSEMBLES overestimated (underestimated) the frequency of rainy days (RR1) and maximum consecutive wet days (CWD) (maximum consecutive dry days [CDD]). In contrast, some members of CORE‐ENS overestimate, while others underestimate, the simple daily intensity index (SDII), the frequency of days with heavy precipitation (R10), and R20, depending on the choice of reference data. The Consortium for Small‐scale MOdelling in CLimate Mode (CCLM) and Regional MOdel (REMO) performed better than the Regional Climate Model (RegCM4.7) in simulating the spatial distributions of extreme precipitation. The regionally averaged uncertainties (biases) of the CORE‐ENS, its ensemble members, and RCMENSEMBLES were within the range of those in the observational datasets, except for CWD (CWD and RR1). Overall, CORE‐ENS performed better than its ensemble members in simulating extreme precipitation.

Design of Portable Coffee Dryer in Kabawetan District, Kepahiang Regency

The statistical data of the Kepahiang Regency in 2018 shows that more than 90% of Kabawetan people worked in the agricultural sector as vegetable and coffee farmers. Due to the hilly morphology of the settlements, the settlement configurations should conform with the land contours. As the majority of the coffee farmers have limited land for drying the harvested coffee, portable architectural technology can then help overcome the problems with the limited house yard. This tool is used as a space for drying their coffee, especially during the rainy season. The method to transfer the portable coffee dryer design to the communities is by training them how to use the technology and introducing it with the help of props (prototypes). This introductory training was conducted for the Permata Sari farmer group in the farmer's house yard in Bukit Sari Village, Kabawetan District. The training activities included coordinating with the involved farmers, making coffee dryer designs, testing simple tools, and introducing the mobile coffee dryer technology to Permata Sari farmer group members in Bukit Sari Village, Kabawetan District Kepahiang Regency. Portable coffee dryers are urgently needed considering the contoured lands, limited space, and the frequency of rainy days in Kabawetan exceeds that of sunny days. However, this tool still requires further development, where it can be used as a sorting tool, particularly for sorting out the red pickled coffee that is dried using this tool.

Impact of Climate Variability on Water Resources: The Case of Marc Delorme-Cnra Station, Southeast of Ivory Coast

This study aims to characterize the climatic variability in the South-East of Ivory Coast and to show its impact on the supply of water resources. To do this, statistical and hydrological methods were applied to climatic data collected at the Marc DELORME Research Station of the CNRA. The statistical trend tests on this data revealed a significant decrease in precipitation and an increase in temperature, insolation and evaporation. Statistical break methods indicate a rainfall break in 1982 which marks a modification of the rainfall regime thus translating a drop in rainfall of 15%, a recession in the frequency of rainy days in general and in particular in rainfall heights between 10 and 30 mm and greater than 50 mm. This break is accompanied by a shortening of the rainy seasons, with average rainfall durations ranging from 54 days (short rainy season) to 104 days (great rainy season). Despite the disturbances in the different seasons of the year, the monthly rainfall regimes in the area have not changed. The assessment of the effects of drought on water resources using the Standardized Precipitation and Evapotranspiration Index (SPEI) for three-time scales (1 month, 3 months and 12 months) indicates a severe drought ranging from 3% to 7% over the period 1961 to 2018. However, despite the presence of this severe drought, the intensity of the drought was found to be moderate on all time scales. The Thorrnthwaite method was used to highlight the impacts of this climatic variability on the region’s water resources. The average annual recharge estimated at 402 mm, has been reduced to 153 mm during a deficit period, a decrease of about 62%. The average annual runoff, which was 294 mm, fells to 257 mm, a decrease of about 13%. This recorded decrease in the water infiltrated after the rainfall break (1983-2018), explains the heterogeneous decrease in the depth of the water table.

Multiscale precipitation variability and extremes over South America: analysis of future changes from a set of CORDEX regional climate model simulations

The precipitation behaviour at different timescales (interannual, intraseasonal and synoptic) and extreme events in a warmer scenario over South America is analysed. This study is based on a set of Regional Climate Models (RCM) from the CORDEX database and their driving Global Climate Models (GCM) from the CMIP5 Project. Historical simulations for 1979–2005 and from the RCP4.5 scenario for 2071–2100 are used. The projected changes in the precipitation behaviour are evaluated in terms of the consistency between the pairs RCM-GCM aiming to explore the added value of RCMs. The agreement between projected changes from RCMs is also evaluated as a measure of confidence of the regional climate change signal. The analysis is carried out for two extended seasons (April to September and October to March). The projected change in the mean precipitation over subtropical latitudes is associated with both changes in the frequency of rainy days and in the intensity of extreme events, while for the tropics the changes are mainly associated with changes in the wet day frequency. The increase of extreme precipitation events over the subtropics arises as a robust signal among models, while for tropical latitudes the dispersion among models is high, which reduces the confidence of the projections. In general, the consistency of the projections in the pairs RCM-GCM and the agreement among models are higher for the low frequency variability patterns during winter, while for summertime a better agreement in the projected changes of the precipitation behaviour at different timescales among RCMs is found.

Analysis of climate extremes indices over northeast Brazil from 1961 to 2014

An analysis of climate extremes indices was conducted for maximum temperatures (TMax), minimum temperatures (TMin), and daily rainfall data (PRCP) over the northeast region of Brazil for the period of 1961–2014. The indices were calculated for 96 weather stations using RClimDex software in a sub-regional study based on cluster analysis, as well as for each individual weather station, after a rigorous process of quality control, gap filling of missing values, and homogenization. The Mann-Kendall non-parametric trend test was employed to assess the statistical significance of the series. The results indicate unequivocal signs of heating. In the past decades, there were predominant trends of decrease in the percentage of cold nights (−8.4% days/decade), increase in the percentage of the number of warm nights (10.6% days/decade), increase in the number of days per decade in which the minimum temperature exceeded the threshold of 20 °C, and a trend showing an increase in heat waves. This was corroborated by the declining trend in the number of consecutive days in which TMin did not exceed the 10th percentile, and the increase in the number of consecutive days in which TMax exceeded the 90th percentile in the data distribution. With regard to PRCP, in most weather stations where there is a significant increase in consecutive dry days, there is also a trend of significant increase in consecutive wet days, thereby intensifying the seasonality, with the dry seasons becoming drier and the rainy seasons wetter. In most weather stations, a reduction was found in the total annual precipitation and in the frequency of rainy days. Moreover, in many stations, an increase in rainfall events that surpasses the threshold of 95% and 99% in the distribution was discovered. These factors highlight concerns of a region of Brazil marked by the scarcity of perennial water resources and the threat of desertification.

Daily characteristics of Central African rainfall in the REMO model

In this paper, daily characteristics of the Central Africa rainfall are assessed using the regional model REMO in the framework of contributions to the CORDEX-Africa project. The model is used to dynamically downscale two global climate models (MPI-ESM-LR and EC-EARTH) for the present (1981–2005) and future (2041–2065, 2071–2095) climate under the Representative Concentration Pathway (RCP) 2.6, 4.5, and 8.5 emission scenarios. A substantial spatio-temporal variability of the daily precipitation characteristics is obtained, as well as varying inferences for individual indices. For the present days, both REMO’s runs capture reasonably well the mean seasonal rainfall, the frequency of wet days, the threshold of extreme rainfall, and the cumulative frequency of daily rainfall. The model better simulates the frequency of rainy days than their intensity. It is found that origins of model biases differ as a function of regions. Over the continent, boundary conditions tend to influence the spatial distribution of rainfall whereas over oceanic and coastal regions, REMO’s physics seems to dominate over the boundary forcing. The projected frequency of wet days shows a decrease along the twenty-first century over most part of the continent. Throughout the century, all scenarios of REMO decrease the rate of rainfall with increasing intensity, and which will be noticeable in the Sahelian region at late twenty-first century. Furthermore, the extreme event thresholds decrease over Sahelian regions and increase along the coastal regions.

Rainfall variability and the impact on maize and rice yields in north – central Nigeria

Rainfall variability in terms of amount, distribution (spatial, seasonal and diurnal), intensity and frequency of rainy days influence crop production and yield. This paper examined rainfall temporal trend inter-annual and spatial distribution and the implication of mean annual rainfall on maize and rice yield in North – Central Geopolitical Region of Nigeria. Daily rainfall records of thirty years period (1987 – 2016) at six stations in the region, namely; Abuja, Ilorin, Jos, Lokoja, Makurdi and Minna were obtained from the archive of the Nigerian Meteorological Agency (NiMet), Abuja and maize and rice yield for the period 1994 – 2016 obtained from the Bureau of Statistics of Nigeria were used for the study. The rainfall data were subjected to statistical analysis using descriptive analysis. Mann-Kendal test and Kriging method were used for the spatio–temporal rainfall distribution while the impact of rainfall amount on maize and rice yields was investigated using regression analysis. The annual rainfall amount experienced in study area was between 1100 mm and 1700 mm. Out of the six stations studied; only Abuja indicated statistically significant increased trend while the other five stations in the region showed no significant trend. Rainfall distribution in the region is largely influence by the Jos Plateau rather than Latitudes or Longitude. Generally, rainfall influences maize and rice yield positively but at varying degree from station to stationKeywords: Rainfall variability, Trend, Distribution, Impact

Changes in the Intensity and Variability of Precipitation in the Central Region of Argentina between 1960 and 2012

This study analyzes the temporal variation of different rainfall features in the central region of Argentina between 1960 and 2012, and evaluates the dynamics of temporal trends by using the Mann–Kendall–Sneyers (MKS) and Tomé–Miranda (TM) procedures. Under different criteria and levels of significance, rainfall time series show homogeneous behavior in more than 80% of cases. Only 18 of the 42 annual cases analyzed reached a significant long-term trend (p < 0.10). Total annual rainfall (AR) showed a significant increase only in Laboulaye Aero (LB) and Villa Dolores Aero (VD), but this does not currently persist. A decrease in the annual frequency of rainy days (DPF) is more widespread in the region. Thus, the increase in mean annual rainfall intensity (INT) seems to be particularly associated with the decrease in annual frequency of events (DPF) in the central region of Argentina. However, the increase in INT currently persists only at the Córdoba Observatorio (BO), as INT stopped growing for LB, Río Cuarto Aero (RC), and VD in the mid-1990s. The variation coefficients of total annual rainfall (ARCV) and DPF (DPFCV) have increased in the region, but with the former restricted locally to the Pilar Observatorio (PI), RC, and VM, and the latter to BO and RC. Long-term changes of the pluvial regime in the central region of Argentina appear to be not only local and restricted to some properties of rainfall during the period, but also reveal a particular dynamic where the long-term trends of the evaluated properties have now changed sign or maintain a certain constancy at present.

Improved seasonal prediction skill of rainfall for the Primera season in Central America

ABSTRACTThis study explores the predictive skill of seasonal rainfall characteristics for the first rainy (and planting) season, May–June, in Central America. Statistical predictive models were built using a Model Output Statistics (MOS) technique based on canonical correlation analysis, in which variables that forecast with the Climate Forecast System version 2 (CFSv2) were used as candidate predictors for the observed total precipitation, frequency of rainy days and mean number of extremely dry and wet events in the season. CFSv2 initializations from February to April were explored. The CFSv2 variables used in the study consist of rainfall, as in a typical MOS technique, and a combination of low‐level winds and convective available potential energy (CAPE), a blend that has been previously shown to be a good predictor for convective activity. The highest predictive skill was found for the seasonal frequency of rainy days, followed by the mean frequency of dry events. In terms of candidate predictors, the zonal transport of CAPE (uCAPE) at 925 hPa offers higher skill across Central America than rainfall, which is attributed in part to the high model uncertainties associated with precipitation in the region. As expected, dynamical model predictors initialized in February provide lower skill than those initialized later. Nonetheless, the skill is comparable for March and April initializations. These results suggest that the National Meteorological and Hydrological Services in Central America, and the Central American Regional Climate Outlook Forum, can produce earlier more skilful forecasts for May–June rainfall characteristics than previously stated.

Partitioning evapotranspiration using long‐term carbon dioxide and water vapor fluxes

AbstractThe separate components of evapotranspiration (ET) elucidate the pathways and time scales over which water is returned to the atmosphere, but ecosystem‐scale measurements of transpiration (T) and evaporation (E) remain elusive. We propose a novel determination of E and T using multiyear eddy covariance estimates of ET and gross ecosystem photosynthesis (GEP). The method is applicable at water‐limited sites over time periods during which a linear regression between GEP (abscissa) and ET (ordinate) yields a positive ET axis intercept, an estimate of E. At four summer‐rainfall semiarid sites, T/ET increases to a peak coincident with maximum GEP and remains elevated as the growing season progresses, consistent with previous, direct measurements. The seasonal course of T/ET is related to increasing leaf area index and declining frequency of rainy days—an index of the wet surface conditions that promote E—suggesting both surface and climatic controls on ET partitioning.

Assessment of ski condition reliability in the Spanish and Andorran Pyrenees for the second half of the 20th century

In this study temporal trends of 14 climate and snow parameters related to ski conditions were analyzed for 11 ski stations located in the central Pyrenees (Spain and Andorra). We also investigated whether there was a temporal association for the analyzed parameters, such that the occurrence in a particular year of good (or bad) climate or snow conditions as represented by one parameter was similarly reflected by the other parameters. The lack of reliable climate and snow measurements was overcome by the use of simulated climate data retrieved from a high resolution hindcast simulation available for the period 1960–2006. These data were also used as inputs for an energy and mass snow energy model to obtain snow series. The results showed trends in ski reliability parameters for the 1960–2006 period. The number of days having a snowpack deeper than 30 cm and 100 cm showed declines at low and mid altitudes. The start of the ski season appears progressively delayed for all stations, and the ski season shortened. The frequency of rainy days increased at 3 stations and decreased at 8, while the frequency of days having heavy snowfall increased at 8 stations and declined at 3. Days having potential for snowmaking declined at all stations. The number of days having a wind-chill < −20 °C also decreased markedly, as overall did the number of days having a wind speed greater than 80th percentile. The main findings from the assessment of temporal associations between climate and snow parameters were positive correlations between snow depth and windy conditions. Seasons having a higher frequency of very cold days had a lower frequency of heavy snowfall and rainy days. Thus, the adverse effects on the ski industry of lesser snow availability may have been partially negated by the occurrence of fewer days of closure because of high winds, or other adverse meteorological factors.

Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

The early rainy season in Central America: the role of the tropical North Atlantic SSTs

ABSTRACTWe explored the relationship between the precipitation anomalies during May to June as the first peak of the rainy season in the Pacific slope of Central America, and sea surface temperature (SST) fluctuations in the surrounding oceans, using canonical correlation analysis (CCA). With this approach, we studied variations in total precipitation, frequency of rainy days and the monthly occurrence of days with rainfall above (below) the 80th (20th) percentile, due to changes in the nearby SST. Composites of the sea‐level pressure (SLP), geopotential heights (200 hPa), relative humidity (700 hPa), horizontal moisture flux and wind at 850 hPa were estimated to provide a dynamical analysis. The composites are calculated using the information obtained with CCA. In addition, we used a general circulation model forced with fixed SST to explore the sensitivity of the model to the SST patterns found using CCA. The results show that the SST over the tropical North Atlantic controls the precipitation fluctuations at interannual scales, due to its connection with the tropical upper tropospheric trough. Warmer (colder) temperatures result in SLP below normal in the Caribbean region, associated with an increase in the heights at 200 hPa. This vertical configuration reduces the wind shear between 850 and 200 hPa and increases the input of humidity to mid‐levels, creating favourable conditions for deep convection, and favouring the generation of tropical cyclone activity. In the Pacific, a positive anomalous low‐level moisture flux is observed from the ocean to the continental parts of the region and may enhance the formation of mesoscale systems. The classic prediction schemes show a lead time of 1 or 2 months; this is an advantage for climate services operative work. The atmospheric model outcomes replicate the main results found in the composite analysis, reflecting its potential use for model output statistics predictive schemes.

Changes in precipitation over the La Plata Basin, projected by CLARIS-LPB regional models

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 68:169-182 (2016) - DOI: https://doi.org/10.3354/cr01388 Contribution to the CR Special: 'CLARIS-La Plata Basin: climate variability and uncertainties' Changes in precipitation over the La Plata Basin, projected by CLARIS-LPB regional models Iracema Fonseca de Albuquerque Cavalcanti*, Virginia Piccinini Silveira Center of Weather Forecasting and Climate Studies/National Institute for Space Research (CPTEC/INPE), Rodovia Presidente Dutra, Km 40, CEP: 12630-000, Cachoeira Paulista, SP, Brazil *Corresponding author: iracema.cavalcanti@cptec.inpe.br ABSTRACT: The La Plata Basin (LPB) is an important region for social and economic sectors of South America, mainly as a source of water and for agriculture. Regional models are used to analyze changes in precipitation over South America in order to provide more details of the projected changes in specific regions. Results of regional models from the CLARIS-LPB project are analyzed to assess changes and uncertainties in future projections for the LPB compared to the base period. Results from several models are taken into account in order to assess uncertainties. The models agree in projecting more precipitation in the whole basin and in an increased frequency of extreme wet austral summers. The majority of models agree in projections of drier conditions in the upper LPB and an increase in the frequency of extreme dry austral winters and springs. However, in the lower LPB the projections indicate an increase in the frequency of extreme wet winters and springs. In austral autumn the uncertainties are high in the upper LPB. The uncertainties are low regarding increases in the frequency of rainy days in the middle and lower LPB and in the maximum number of consecutive dry days in the upper LPB. The projected patterns of austral summer anomaly precipitation variability obtained from empirical orthogonal function analysis display the same dipole between southern LPB and the South Atlantic Convergence Zone as in the base period, but increased anomalies in the northern center. In the austral winter the only anomaly signal simulated in the base period remains in the future projections, but the maximum variability is displaced southwards. KEY WORDS: Precipitation extremes · Regional models · La Plata Basin · Climate change · Frequency of extremes · Precipitation variability · Precipitation indices Full text in pdf format PreviousNextCite this article as: Cavalcanti IFA, Silveira VP (2016) Changes in precipitation over the La Plata Basin, projected by CLARIS-LPB regional models. Clim Res 68:169-182. https://doi.org/10.3354/cr01388 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 68, No. 2-3. Online publication date: May 04, 2016 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2016 Inter-Research.