Annual Cycle Of Precipitation Research Articles

Contribution of diverse monsoon precipitation over Central and Northern India during mid to Late Holocene

Abstracts The Indian summer monsoon (ISM) precipitation pattern over Indian subcontinent is looked through various high resolution speleothem oxygen (δ18O) isotope records from Mid to Late Holocene. The six cave locations distributed from central to northern India describing regional climatic conditions due to stalagmite deposition are considered. The stalagmite deposition reflects precipitation patterns by temporal variations of δ18O values. Oxygen isotope values reflect cumulative precipitation that is basically interpreted by averaged latitudinal site of inter tropical convergence zone (ITCZ). Under the Paleoclimate Modelling Intercomparison Project Phase III (PMIP3) simulation, Commonwealth Scientific and Industrial Research Organisation Mk3L version 1.0 – Part 2 (CSIRO-Mk3L-1-2) model output shows ITCZ movement from Bay of Bengal (BoB) to Arabian Sea (AS) during Mid to Late Holocene which resulted due to solar insolation changes. It reflects precipitation shift from BoB to AS as well as to core monsoon zone (CMZ) to the western Himalayas. The past millennium epoch, which consists little ice age (LIA) and middle warm period (MWP), shows large variations in 850 hPa geopotential height leading to high anomalous precipitation variability all over India during ISM. The high fluctuation in δ18O values during Mid Holocene over northern India led to drought conditions due to which Indus valley civilization vanished. The present study shows that the Himalayas received higher precipitation during late Holocene. That is basically governed by western disturbances (WD) as well as ISM. Present study summarizes that the mean annual precipitation cycle for entire epoch was roughly similar, but spatial distribution of precipitation during various epoch was quite divergent from Mid to Late Holocene. The onset of ISM was also similar but, withdrawal was comparatively unalike. Wherever, peaks of seasonal precipitation were alike over Indian subcontinent region, spatial distribution of precipitation were unlike.

Projected changes in the annual cycle of precipitation over central Asia by CMIP5 models

Future changes in the annual cycle of the precipitation in central Asia (CA) were estimated based on the historical and representative concentration pathway 8.5 (RCP8.5) experiments from 25 models of the Coupled Model Intercomparison Project phase 5. Compared with the Global Precipitation Climatology Project observations, the historical (1979–1999) experiments showed that most models can capture the migration of rainfall centres, but remarkable discrepancies exist in the location and intensity of rainfall centres between simulations and observations. Considering the skill scores of precipitation and pattern correlations of circulations, which are closely related to the precipitation for each month, for the 25 models, the four best models (e.g., CanESM2, CMCC‐CMS, MIROC5 and MPI‐ESM‐LR) with relatively good performance were selected. The four models' ensemble mean indicated that the migration and location of the precipitation centres were better reproduced, except the intensity of the centres was overestimated, compared with the result that only took the precipitation into consideration. Based on the four best models' ensemble mean under RCP8.5 scenarios, precipitation was projected to increase dramatically over most of the CA region in the boreal cold seasons (November, December, January, February, March and April) and May, with the maximum in December at the end of 21st century (2079–2099), and several positive centres were located in the Pamirs Plateau, the Tianshan Mountains and the northern Himalayas. The precipitation changes were weak in the boreal warm seasons (June, July, August, September and October), with a dry centre located in the Pamirs Plateau and a wet centre in the northern Himalayas. These projected changes can be directly attributed to the overlay of anomalous moisture convergence and evaporation, and other possible mechanisms of dynamic and thermodynamic factors need to be further elucidated.

Assessing the reliability and uncertainties of projected changes in precipitation and temperature in Coupled Model Intercomparison Project phase 5 models over the Lake Chad basin

Lake Chad lost more than 80% of its surface area over the past decades as a result of environmental change and climate variability. It is not yet known how climate change will affect water resources availability in the basin over the coming decades. In this study, the reliability ensemble averaging (REA) technique was used to evaluate the performance of Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating present‐day precipitation and temperature (1980–2005), and to quantify the uncertainties in future projections (2050–2075) under two representative concentration pathways (RCPs) in the Lake Chad basin (LCB). Analyses were carried out at both annual and seasonal timescales. Overall, the CMIP5 models simulated precipitation better than temperature in the study area. Although the models were able to simulate the annual precipitation cycle in the basin, most models overestimated precipitation during the dry season and underestimated it during the monsoon season. Future annual basin precipitation is projected to increase by 2.5 and 5%, respectively, under RCP4.5 and RCP8.5 scenario by the middle of the century by most of the models and most of the model projections are within the REA uncertainty range. Despite the increase in projected annual precipitation in the basin, most models project a decrease in monsoon precipitation under both RCPs. Although the uncertainty range for future precipitation projections for most models lie within the range of natural climate variability, additional analysis is needed for results to be useful for any future planning in the study area.

A new region-aware bias-correction method for simulated precipitation in areas of complex orography

Abstract. Regional climate modelling is used to simulate the hydrological cycle, which is fundamental for climate impact investigations. However, the output of these models is affected by biases that hamper its direct use in impact modelling. Here, we present two high-resolution (2 km) climate simulations of precipitation in the Alpine region, evaluate their performance over Switzerland and develop a new bias-correction technique for precipitation suitable for complex topography. The latter is based on quantile mapping, which is applied separately across a number of non-overlapping regions defined through cluster analysis. This technique allows removing prominent biases while it aims at minimising the disturbances to the physical consistency inherent in all statistical corrections of simulated data. The simulations span the period 1979–2005 and are carried out with the Weather Research and Forecasting model (WRF), driven by the ERA-Interim reanalysis (hereafter WRF-ERA), and the Community Earth System Model (hereafter WRF-CESM). The simulated precipitation is in both cases validated against observations in Switzerland. In a first step, the area is classified into regions of similar temporal variability of precipitation. Similar spatial patterns emerge in all datasets, with a clear northwest–southeast separation following the main orographic features of this region. The daily evolution and the annual cycle of precipitation in WRF-ERA closely reproduces the observations. Conversely, WRF-CESM shows a different seasonality with peak precipitation in winter and not in summer as in the observations or in WRF-ERA. The application of the new bias-correction technique minimises systematic biases in the WRF-CESM simulation and substantially improves the seasonality, while the temporal and physical consistency of simulated precipitation is greatly preserved.

Harmonic Analysis of Precipitation Time Series in Lake Tana Basin, Ethiopia

This study presents harmonic analysis of precipitation observations within the Lake Tana Basin for the periods of 1985–2015. The livelihood of several millions of people within the basin and outside the basin is governed by the precipitation conditions within this basin. Large spatial and temporal variabilities of precipitation can increase the incidence of extreme events such as floods and droughts. It is important to identify the characteristics of these variations, and this study aims at investigating the characteristics of the seasonal and annual cycles of precipitation within the Lake Tana Basin using harmonic analysis. Precipitation data of 31 years from four weather stations were used in the analysis. We then applied harmonic analysis to calculate the amplitude, phase shift, and variance of observation. Detailed characteristics of the first five harmonics are presented and discussed. We found the amplitude of the first harmonic to be 173.42, 177.93, 127.77, and 188.78 mm for Debre Tabor, Bahir Dar, Gondar, and Dangila, respectively. This shows that Dangila areas got more rainfall during this fundamental period than others increasing from Gondar to Dangila direction. Also, the variance in the first harmonic is smaller than the variances of other harmonics, and this means that the large variations of the precipitation originate from higher harmonics (short time periods). This shows that precipitation variations are governed mainly by monthly, seasonal, and semiannual variations. The analysis has shown that maximum precipitation for all stations occurred in July and August.

High-resolution ensemble projections and uncertainty assessment of regional climate change over China in CORDEX East Asia

Abstract. An ensemble simulation of five regional climate models (RCMs) from the coordinated regional downscaling experiment in East Asia is evaluated and used to project future regional climate change in China. The influences of model uncertainty and internal variability on projections are also identified. The RCMs simulate the historical (1980–2005) climate and future (2006–2049) climate projections under the Representative Concentration Pathway (RCP) RCP4.5 scenario. The simulations for five subregions in China, including northeastern China, northern China, southern China, northwestern China, and the Tibetan Plateau, are highlighted in this study. Results show that (1) RCMs can capture the climatology, annual cycle, and interannual variability of temperature and precipitation and that a multi-model ensemble (MME) outperforms that of an individual RCM. The added values for RCMs are confirmed by comparing the performance of RCMs and global climate models (GCMs) in reproducing annual and seasonal mean precipitation and temperature during the historical period. (2) For future (2030–2049) climate, the MME indicates consistent warming trends at around 1 ∘C in the entire domain and projects pronounced warming in northern and western China. The annual precipitation is likely to increase in most of the simulation region, except for the Tibetan Plateau. (3) Generally, the future projected change in annual and seasonal mean temperature by RCMs is nearly consistent with the results from the driving GCM. However, changes in annual and seasonal mean precipitation exhibit significant inter-RCM differences and possess a larger magnitude and variability than the driving GCM. Even opposite signals for projected changes in average precipitation between the MME and the driving GCM are shown over southern China, northeastern China, and the Tibetan Plateau. (4) The uncertainty in projected mean temperature mainly arises from the internal variability over northern and southern China and the model uncertainty over the other three subregions. For the projected mean precipitation, the dominant uncertainty source is the internal variability over most regions, except for the Tibetan Plateau, where the model uncertainty reaches up to 60 %. Moreover, the model uncertainty increases with prediction lead time across all subregions.

Analysis of NVDI variability in response to precipitation and air temperature in different regions of Iraq, using MODIS vegetation indices

Iraq, the land of two rivers, has a history that extends back millennia and is the subject of much archaeological research. However, little environmental research has been carried out, and as such relatively little is known about the interaction between Iraq’s vegetation and climate. This research serves to fill this knowledge gap by investigating the relationship between the Normalized Difference Vegetation Index (NDVI) and two climatic factors (precipitation and air temperature) over the last decade. The precipitation and air temperature datasets are from the Water and Global Change Forcing Data ERA-Interim (WFDEI), and the NDVI dataset was extracted from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m spatial resolution and 16 day temporal resolution. Three different climatic regions in Iraq, Sulaymaniyah, Wasit, and Basrah, were selected for the period of 2001–2015. This is the first study to compare these regions in Iraq, and one of only a few investigating vegetation’s relationship with multiple climatic factors, including precipitation and air temperature, particularly in a semi-arid region. The interannual, intra-annual and seasonal variability for each region is analysed to compare the different responses of vegetation growth to climatic factors. Correlations between NDVI and climatic factors are also included. Plotting annual cycles of NDVI and precipitation reveals a coherent onset, fluctuation (peak and decline), with a time lag of 4 months for Sulaymaniyah and Wasit (while for the Basrah region, high temperatures and a short rainy season was observed). The correlation coefficients between NDVI and precipitation are relatively high, especially in Sulaymaniyah, and the largest positive correlation was (0.8635) with a time lag of 4 months. The phenological transition points range between 3 and 4 month time lag; this corresponds to the duration of maturity of the vegetation. However, when correlated with air temperature, NDVI experiences an inverse relationship, although not as strong as that of NDVI and precipitation; the highest negative correlation was observed in Wasit with a time lag of 2 months (− 0.7562). The results showed that there is a similarity between temporal patterns of NDVI and precipitation. This similarity is stronger than that of NDVI and air temperature, so it can be concluded that NDVI is a sensitive indicator of the inter-annual variability of precipitation and that precipitation constitutes the primary factor in germination while the air temperature acts with a lesser effect.

Evaluation of CMIP5 retrospective simulations of temperature and precipitation in northeastern Argentina

ABSTRACTIt is generally agreed that models that better simulate historical and current features of climate should also be the ones that more reliably simulate future climate. This article describes the ability of a selection of global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to represent the historical and current mean climate and its variability over northeastern Argentina, a region that exhibits frequent extreme events. Two types of simulations are considered: Long‐term simulations for 1901–2005 in which the models respond to climate forcing (e.g. changes in atmospheric composition and land use) and decadal simulations for 1961–2010 that are initialized from observed climate states. Monthly simulations of precipitation and temperature are statistically evaluated for individual models and their ensembles.Subsets of models that best represent the region's climate are further examined. First, models that have a Nash–Sutcliffe efficiency of at least 0.8 are taken as a subset that best represents the observed temperature fields and the mean annual cycle. Their temperature time series are in phase with observations (r > 0.92), despite systematic errors that if desired can be corrected by statistical methods. Likewise, models that have a precipitation Pearson correlation coefficient of at least 0.6 are considered that best represent regional precipitation features. GCMs are able to reproduce the annual precipitation cycle, although they underestimate precipitation amounts during the austral warm season (September through April) and slightly overestimate the cold season rainfall amounts. The ensembles for the subsets of models achieve the best evaluation metrics, exceeding the performance of the overall ensembles as well as those of the individual models.

Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

Decadal Shift in West China Autumn Precipitation and its Association With Sea Surface Temperature

AbstractWest China autumn precipitation (WCAP) is the final stage of the rainy season in mainland China and is characterized as the secondary peak in annual cycle of precipitation in West China. This study reveals that WCAP experienced a significant interdecadal shift around the mid‐1980s, with greatly reduced precipitation after this shift. Features related to the decrease in WCAP include the weakening of warm, wet southerlies prevailing from the oceans to inland China, the weakened Eurasian pattern, and the southward displacement of the East Asian jet stream (EAJS). Further analysis indicates that the interdecadal changes in WCAP may be attributed to the interdecadal increasing of sea surface temperature (SST) in the Indo‐Pacific warm pool (SSTIOP), North Pacific (SSTNP), and central equatorial Pacific (SSTCEP) after the 1980s. The warmer SSTIOP contributes to a weaker meridional land‐sea thermal contrast, which inducts an anomalous local meridional circulation and northerly. The warmer SSTNP stimulates a Rossby wave train that leads to weakened West Pacific subtropical high and accompanying cyclonic circulation anomaly, hindering the transport of water vapor inland from the oceans. The increased SSTCEP leads to the southward displacement of the EAJS and its secondary circulation, generating an anomalous descending branch and reduced WCAP. Numerical simulations further support the conclusions derived from the diagnostic analysis that the decadal warming of the SSTIOP, SSTNP, and SSTCEP synergistically contributes to the reduction of WCAP after the 1980s.

Regional climate model simulation for temperature and precipitation over South Asia using different physical parameterisation schemes

The ability of ICTP regional climate model version 4 (RegCM4.3) is investigated by using two land surface schemes: the biosphere-atmosphere transfer scheme (BATS) and the community land model version 3.5 (CLM3.5). To attain the best model configuration over the South Asia region, six sensitivity experiments are conducted with three different cumulus convection schemes. RegCM4.3 coupled with CLM3.5 and mixed convection scheme option (MIX-CLM), produced better simulation than BATS. The cold winter bias and the intensities of wet-dry biases over the foothills of Hindukush-Karakorum-Himalaya (HKH) and Central India are substantially reduced with MIX-CLM. In terms of seasonal variability, results suggest that different convection schemes behaved differently over sub-regions of the domain. The annual cycles of precipitation and temperature are better captured over the Bay of Bengal and Western Ghats by MIX-CLM. In spite of some deficiencies, the MIX-CLM scheme improves the model performance over the various parts of the domain.

Regional climate model simulation for temperature and precipitation over South Asia using different physical parameterisation schemes

The ability of ICTP regional climate model version 4 (RegCM4.3) is investigated by using two land surface schemes: the biosphere-atmosphere transfer scheme (BATS) and the community land model version 3.5 (CLM3.5). To attain the best model configuration over the South Asia region, six sensitivity experiments are conducted with three different cumulus convection schemes. RegCM4.3 coupled with CLM3.5 and mixed convection scheme option (MIX-CLM), produced better simulation than BATS. The cold winter bias and the intensities of wet-dry biases over the foothills of Hindukush-Karakorum-Himalaya (HKH) and Central India are substantially reduced with MIX-CLM. In terms of seasonal variability, results suggest that different convection schemes behaved differently over sub-regions of the domain. The annual cycles of precipitation and temperature are better captured over the Bay of Bengal and Western Ghats by MIX-CLM. In spite of some deficiencies, the MIX-CLM scheme improves the model performance over the various parts of the domain.

Performances of BATS and CLM land‐surface schemes in RegCM4 in simulating precipitation over CORDEX Southeast Asia domain

ABSTRACTThis study evaluates the sensitivity of precipitation in Southeast Asia (SEA) to the choice of land‐surface schemes available in RegCM4, that is BATS1e (BATS) and CLM4.5 (CLM), over the CORDEX SEA domain. Two similar simulations using different land‐surface schemes were conducted for the period 1989 to 2007, with a horizontal resolution of 25 × 25 km. Four different types of observational data were used to evaluate the performance of these simulations. It was found that both of these simulations reproduced the SEA precipitation climatology spatial patterns reasonably well. However, the BATS simulation systematically produced higher frequency and more intense precipitation over land. The CLM simulation, although overestimating the precipitation frequency, produced a lower amount of on‐land precipitation. The precipitation annual cycle and interannual variability were both insensitive to the choice of land‐surface scheme. The errors in the precipitation simulation were found to originate from the simulated convective precipitation (CPr). Large‐scale precipitation was found to be less sensitive to the choice of land‐surface scheme. The influence of the land‐surface scheme on SEA precipitation simulation took place through the interaction between soil moisture content and CPr. The soil moisture content was consistently higher in the BATS simulation, as was the CPr simulated. During December to February (DJF), the difference in the precipitation amount simulated by BATS and CLM simulations was lower over the SEA mainland, even though the soil moisture content in both simulations was very different. This difference was due to the inactivity of the convective activities over the SEA mainland during DJF. This study concludes that the simulation of SEA precipitation amount was sensitive to the choice of land‐surface scheme, and recommend the use of CLM4.5 land‐surface scheme for simulation of SEA precipitation.

Observed and Projected Changes to the Precipitation Annual Cycle

Anthropogenic climate change is predicted to cause spatial and temporal shifts in precipitation patterns. These may be apparent in changes to the annual cycle of zonal mean precipitation P. Trends in the amplitude and phase of the P annual cycle in two long-term, global satellite datasets are broadly similar. Model-derived fingerprints of externally forced changes to the amplitude and phase of the P seasonal cycle, combined with these observations, enable a formal detection and attribution analysis. Observed amplitude changes are inconsistent with model estimates of internal variability but not attributable to the model-predicted response to external forcing. This mismatch between observed and predicted amplitude changes is consistent with the sustained La Niña–like conditions that characterize the recent slowdown in the rise of the global mean temperature. However, observed changes to the annual cycle phase do not seem to be driven by this recent hiatus. These changes are consistent with model estimates of forced changes, are inconsistent (in one observational dataset) with estimates of internal variability, and may suggest the emergence of an externally forced signal.

Temperature and precipitation in the context of the annual cycle over Asia: Model evaluation and future change

Since the early or late arrival of monsoon rainfall can be devastating to agriculture and economy, the prediction of the onset of monsoon is a very important issue. The Asian monsoon is characterized by a strong annual cycle with rainy summer and dry winter. Nevertheless, most of monsoon studies have focused on the seasonal-mean of temperature and precipitation. The present study aims to evaluate a total of 27 coupled models that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) for projection of the time evolution and the intensity of Asian monsoon on the basis of the annual cycle of temperature and precipitation. And future changes of onset, retreat, and intensity of monsoon are analyzed. Four models for good seasonal-mean (GSM) and good harmonic (GH) groups, respectively, are selected. GSM is based on the seasonal-mean of temperature and precipitation in summer and winter, and GH is based on the annual cycle of temperature and precipitation which represents a characteristic of the monsoon. To compare how well the time evolution of the monsoon is simulated in each group, the onset, retreat, and duration of Asian monsoon are examined. The highest pattern correlation coefficient (PCC) of onset, retreat, and duration between the reanalysis data and model outputs demonstrates that GH models’ MME predicts time evolution of monsoon most precisely, with PCC values of 0.80, 0.52, and 0.63, respectively. To predict future changes of the monsoon, the representative concentration pathway 4.5 (RCP 4.5) experiments for the period of 2073-2099 are compared with historical simulations for the period of 1979-2005 from CMIP5 using GH models’ MME. The Asian monsoon domain is expanded by 22.6% in the future projection. The onset date in the future is advanced over most parts of Asian monsoon region. The duration of summer Asian monsoon in the future projection will be lengthened by up to 2 pentads over the Asian monsoon region, as a result of advanced onset. The Asian monsoon intensity becomes stronger with the passage of time. This study has important implication for assessment of CMIP5 models in terms of the prediction of time evolution and intensity of Asian monsoon based on the annual cycle of temperature and precipitation.

Maritime Continent seasonal climate biases in AMIP experiments of the CMIP5 multimodel ensemble

The fidelity of 28 Coupled Model Intercomparison Project phase 5 (CMIP5) models in simulating mean climate over the Maritime Continent in the Atmospheric Model Intercomparison Project (AMIP) experiment is evaluated in this study. The performance of AMIP models varies greatly in reproducing seasonal mean climate and the seasonal cycle. The multi-model mean has better skill at reproducing the observed mean climate than the individual models. The spatial pattern of 850 hPa wind is better simulated than the precipitation in all four seasons. We found that model horizontal resolution is not a good indicator of model performance. Instead, a model’s local Maritime Continent biases are somewhat related to its biases in the local Hadley circulation and global monsoon. The comparison with coupled models in CMIP5 shows that AMIP models generally performed better than coupled models in the simulation of the global monsoon and local Hadley circulation but less well at simulating the Maritime Continent annual cycle of precipitation. To characterize model systematic biases in the AMIP runs, we performed cluster analysis on Maritime Continent annual cycle precipitation. Our analysis resulted in two distinct clusters. Cluster I models are able to capture both the winter monsoon and summer monsoon shift, but they overestimate the precipitation; especially during the JJA and SON seasons. Cluster II models simulate weaker seasonal migration than observed, and the maximum rainfall position stays closer to the equator throughout the year. The tropics-wide properties of these clusters suggest a connection between the skill of simulating global properties of the monsoon circulation and the skill of simulating the regional scale of Maritime Continent precipitation.

Lifecycle of South American Monsoon System simulated by CPTEC/INPE AGCM

ABSTRACTThe lifecycle of South American Monsoon System (SAMS) plays an important role on the duration of the rainy season over large areas of South America, affecting the economy through impacts on agriculture, water resources and energy management. Numerical model prediction of SAMS onset, demise and related atmospheric features is an important tool to be used in management decisions in these sectors. This information is still missing in seasonal predictions, and the purpose of this study is to examine results of a climate simulation using the CPTEC/INPE AGCM to verify its ability in simulating the SAMS onset and demise as well as the associated atmospheric features. The SAMS lifecycle is identified using an index of the zonal humidity flux in the monsoon core. The model captured the atmospheric changes associated with the SAMS lifecycle, although showing differences in intensity and maximum locations of some variables, such as the magnitude of humidity flux, sea level pressure and omega, compared to reanalysis. During the onset, the model simulated the humidity flux direction changes, the eastward shifting of the South Atlantic Subtropical High and the northwesterly moisture flux east of tropical Andes. During the demise, the model simulated the easterly moisture flux directed toward the Amazon region and the reduction of northerly/northwesterly flow over northern South America, as well as the increase of Sea Level Pressure over the continent. Results obtained using a previous version of CPTEC/INPE AGCM are discussed, mainly the improvements, in the new version, of atmospheric variables and annual cycle of precipitation. The model was able to represent the main observed features of the SAMS lifecycle. The method can be useful to identify the onset and demise dates and could be applied to results of seasonal prediction prior to the rainy season, adding information to planning and management actions.

The role of low-level terrain-induced jets in rainfall variability in Tigris-Euphrates Headwaters.

Rainfall variability in the Tigris-Euphrates Headwaters is a result of interaction between topography and meteorological features at a range of spatial scales. Here, we have implemented the Weather Research and Forecasting (WRF) model, driven by NCEP/DOE R2, to better understand these interactions. Simulations were performed over a domain covering most of the Middle-East. The extended simulation period (1983-2013) enables us to study seasonality, interannual variability, spatial variability and extreme events of rainfall. Results showed that the annual cycle of precipitation produced by WRF agrees much more closely with observations than does R2. This was particularly evident during the transition months of April and October, which were further examined to study the underlying physical mechanisms. In both months, WRF improves representation of interannual variability relative to R2, with a substantially larger benefit in April. This improvement results primarily from WRF's ability to resolve two low-level terrain-induced flows in the region that are either absent or weak in NCEP/DOE: one parallel to western edge of the Zagros Mountains, and one along the East Turkish Highlands. The first shows a complete reversal in its direction during wet and dry days: when flowing southeasterly it transports moisture from the Persian Gulf to the region, and when flowing northwesterly it blocks moisture and transports it away from the region. The second is more directly related to synoptic-scale systems and carries moist, warm air from the Mediterranean and Red Seas toward the region. The combined contribution of these flows explains about 50% of interannual variability in both WRF and observations for April and October precipitation.

Role of moisture transport for Central American precipitation

Abstract. A climatology of moisture sources linked with Central American precipitation was computed based upon Lagrangian trajectories for the analysis period 1980–2013. The response of the annual cycle of precipitation in terms of moisture supply from the sources was analysed. Regional precipitation patterns are mostly driven by moisture transport from the Caribbean Sea (CS). Moisture supply from the eastern tropical Pacific (ETPac) and northern South America (NSA) exhibits a strong seasonal pattern but weaker compared to CS. The regional distribution of rainfall is largely influenced by a local signal associated with surface fluxes during the first part of the rainy season, whereas large-scale dynamics forces rainfall during the second part of the rainy season. The Caribbean Low Level Jet (CLLJ) and the Chocó Jet (CJ) are the main conveyors of regional moisture, being key to define the seasonality of large-scale forced rainfall. Therefore, interannual variability of rainfall is highly dependent of the regional LLJs to the atmospheric variability modes. The El Niño–Southern Oscillation (ENSO) was found to be the dominant mode affecting moisture supply for Central American precipitation via the modulation of regional phenomena. Evaporative sources show opposite anomaly patterns during warm and cold ENSO phases, as a result of the strengthening and weakening, respectively, of the CLLJ during the summer months. Trends in both moisture supply and precipitation over the last three decades were computed, results suggest that precipitation trends are not homogeneous for Central America. Trends in moisture supply from the sources identified show a marked north–south seesaw, with an increasing supply from the CS Sea to northern Central America. Long-term trends in moisture supply are larger for the transition months (March and October). This might have important implications given that any changes in the conditions seen during the transition to the rainy season may induce stronger precipitation trends.

Evaluating global reanalysis precipitation datasets with rain gauge measurements in the Sudano‐Sahel region: case study of the Logone catchment, Lake Chad Basin

ABSTRACTAfrica has a paucity of long term reliable meteorological ground station data and reanalysis products are used to provide the climate estimations that are important for climate change projections. In this paper monthly observed precipitation records in the Logone catchment of the Lake Chad Basin are used to evaluate the performance of two global reanalysis products: the Climate Forecasting System Reanalysis (CFSR) and ERA Interim datasets.The two reanalysis products reproduced the monthly, annual and decadal cycle of precipitation and variability relatively accurately albeit with some discrepancies. The catchment rainfall gradient was also well captured by the two products. There are good correlations between the reanalysis and rain gauge datasets although significant deviations exist, especially for CFSR. Both reanalysis products overestimated rainfall in 68% of the rain gauge stations. ERA Interim produced the lowest bias and mean absolute error with average values of 2% and 6.5 mm month−1 respectively compared to 15% and 34 mm month−1 for the CFSR. However, both reanalysis products systematically underestimated annual rainfall in the catchment during the period 1997–2002 for ERA Interim and 1998–2000 for CFSR. This research demonstrates that evaluating reanalysis products in remote areas like the Logone catchment enables users to identify artefacts inherent in reanalysis datasets. This will facilitate improvements in certain aspects of the reanalysis forecast model physics and parameterization to improve reanalysis dataset quality.This study concludes that the application of each reanalysis product in the catchment will depend on the purpose for which it is to be used and the spatial scale required.