Rainfall characteristics such as onset and cessation dates, seasonal rainfall amount, and distribution significantly impact agricultural production in rainfed systems. Studies have found that timely crop planning is necessary to maximize crop production and increase the resilience and sustainability of the rain-fed system. Thus, timely and accurate prediction of seasonal rainfall characteristics is crucial to enhance effective crop planning and minimize climate-induced crop production risks. The present study used seasonal rainfall onset dates computed using a long-term dataset, i.e., 1935–2020, acquired from the Tanzania Meteorological Authority (TMA) using Liebmann’s method to characterize the growing period in the semi-arid region of Tanzania—Kongwa district. Liebmann’s method was used due to its proven suitability in both hydrological and agronomical applications. We further used the well-known climate indices, i.e., the SOI (Southern Oscillation Index), the IOD (Indian Ocean Dipole), and NINO 3.4 averaged over the July–September period in the decision tree model, to predict the onset dates and characterize the growing period. We found the late-onset seasons—two weeks after the 7th of December—had lower rainfall (17% less than the climatological mean) and were at least 15 days shorter than the climatologically normal growing period. Moreover, the variability in seasonal rainfall in the late-onset season (CV = 28%) was found to be at least 5% higher than in the early-onset season. Late-onset seasons had a 40% chance of receiving the minimum amount of rainfall required for high-water-demand cereals like maize (450 mm). We also found SOI to be a good predictor of onset dates compared to NINO 3.4 and IOD. The SOI predicted well both normal and late-onset infections—50% and 68% precision (hit rate), respectively—compared to the IOD and NINO 3.4, whose precision was less than 10% in predicting the late onset and about 63% in predicting the normal onset. Although our results are useful to guide crop planning before the season, we recommend further studies to examine the agronomical and economic impacts the onset dates would have on crop productivity.

How to cite: Joseph, J., Whitbread, A., Roetter, R., and Surovyatkina, E.: Characterizing the growing period using seasonal rainfall onset dates in the semi-arid region of Tanzania, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12235, https://doi.org/10.5194/egusphere-egu23-12235, 2023.

Western Equatorial Africa (WEA) is characterized by a long and cloudy dry season extending from June to September. So far, no study has investigated the intra-seasonal characteristics of this dry season especially its onset and cessation dates. In our study, the onset and cessation dates are determined over the 38-year period 1983–2020, using daily surface solar radiation (SSR) data from CMSAF SARAH-2. The maximum and minimum values of the cumulative anomalies of a regional index, for each year, are used to extract the onset and cessation dates. The mean onset date of the dry season in the region is May 17, the mean cessation date is October 3. We obtain very distinct anomaly patterns of SSR but also of low-level clouds and precipitation before/after the onset/cessation dates. The onset and cessation dates show strong year-to-year variability but no significant trend is detected over the 4 decades studied. Lastly, the cumulative anomalies for each year are also used to classify the dry seasons according to the SSR intra-seasonal evolution. Three types of years are obtained which are associated to different patterns of SST anomalies in the tropics.

How to cite: Ouhechou, A., Philippon, N., and Morel, B.: Detection and characterization of the onset and cessation dates of the dry season in Western Equatorial Africa based on solar radiation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4418, https://doi.org/10.5194/egusphere-egu23-4418, 2023.

The  onset  of  the  southwest  monsoon  over  Kerala  (Southern tip of India) is  very  crucial  as  it  marks  the  beginning  of  the rainy  season  for  Indian  land  mass.  The  onset  of  the  broad  scale  Asian  monsoon  occur  in  many  stages  associated with the significant  transitions  in  the  large-scale  atmospheric  and  ocean  circulations  over  the  region.  Along with this, the changes in sea surface temperature (SST) and convective activity over the north Indian Ocean also play crucial roles during the onset and advance of monsoon over India. Recent analysis (based on data from 1971 to 2019) by India Meteorological Department (IMD) on the onset & withdrawal of southwest monsoon over India compared to the earlier onset and withdrawal dates (based on the rainfall data from 1901 to 1940) has found variations in onset and withdrawal dates over different parts of India.

        The variability of SST and convective activity over the north Indian Ocean (Bay of Bengal and Arabian Sea) on inter-annual time scales and their association with the onset and withdrawal of southwest monsoon over India has been analysed by using 42-year (1980-2021) monthly mean outgoing longwave radiation (OLR) data. The 42-year period is categorised into two groups of 21 years each (Former: 1980-2000 & Later: 2021-2021). The inter-annual variability of SST shows significant increasing trends over the Arabian Sea and the Bay of Bengal with a comparatively higher rate of increase of SST over the Arabian Sea. Associated with this increasing SST, the degree of moist static convective instability and associated convective rainfall is also increasing during later period compared to the former period with a magnitude of difference is higher over the Arabian Sea compared to the Bay of Bengal.

         The analysis also indicated that there is a rapid progress of monsoon to the north after its onset over the southern tip of India leading to early onset over parts of northern India.  Similarly, there is a delayed withdrawal of monsoon from northwest India in later period compared to the former period, which is basically, due to the increasing convective activity over the north Arabian Sea and neighbourhood during the onset and withdrawal phase of monsoon.

How to cite: Pattanaik, D. R.: Recent Changes in Onset and Withdrawal Characteristics of Monsoon over India in Relation to Variability of SST and Convection over the Indian Ocean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17236, https://doi.org/10.5194/egusphere-egu23-17236, 2023.

Monsoon onset is the most awaited event for more than a billion people in India because monsoon rainfall is a source of life for the population. The abruptness of the transition to monsoon and its spatial and temporal variability from year to year are key features of the phenomenon that makes predicting the monsoon's onset a scientific challenge. According to Ananthakrishnan and Soman, 1988, [1], the onset of a monsoon is a transition from a regime of sporadic rainfall to spatially organized and temporally sustained rainfall. Our recent study [2] added a single word to this definition by discovering that a transition to monsoon is a 'critical' transition. We defined two states in the transition: pre-monsoon and monsoon. Between two states must be a critical point - a threshold in the atmospheric variables (near-surface air temperature, relative humidity). We found that the monsoon begins when the variables overcome a critical threshold. This funding allowed us to develop and successfully implement [3] the methodology of the long-term forecast of monsoon onset and withdrawal in Central India, Northern Telangana, and Delhi: 40 days before the onset date and 70 days before the withdrawal date. Building on these findings, I move forward to understand how to describe the critical conditions for a local onset and withdrawal of monsoon in every state in India, where the monsoon forecast desperately needs.

Here, I present a definition of monsoon onset for every location based on critical values of three atmospheric variables: temperature (Tc), relative humidity (RHc), and outgoing longwave radiation (OLRc). The OLR is included in the critical points set because it is a crucial indicator for the upcoming monsoon characterizing convective activity, implying scarcity or deep convective clouds. The critical values (Tc, RHc, OLRc) for every location can be revealed from the historical observations: near-surface temperature and relative humidity at 1000 hPa from NCEP/NCAR reanalysis and OLR data from NOAA. The three critical points do not always appear simultaneously; the dates might differ from one to three days. Hence, monsoon onset occurs when all three variables pass a critical threshold. I anticipate the definition to be a starting point for other monsoon-related applications, such as planning agriculture season, the water and energy recourses management.

Importantly, a vulnerable period could appear between monsoon onset and sustainable rainfall - a dry spell after initial rainfall strongly affecting the agriculture sector. I work towards a deeper understanding of the precursors of a dry spell and its extremes and uncover how to avoid false alarms that are disastrous for farming.

ES acknowledges the financial support of the B-EPICC project (18_II_149_Global_A_Risikovorhersage) funded by FFO.

[1] Ananthakrishnan R., and M. K. Soman, 1988: The onset of southwest monsoon over Kerala: 1901-1980. J. Climatol., 8, 283–296.

[2] Stolbova, V., E. Surovyatkina, B. Bookhagen, and J. Kurths (2016): Tipping elements of the Indian monsoon: Prediction of onset and withdrawal. GRL 43, 1–9 [doi:10.1002/2016GL068392]

[3] https://www.pik-potsdam.de/members/elenasur/forecasting-indian-monsoon/welcome-to-the-pik-monsoon-page-1

How to cite: Surovyatkina, E.: Local onset of monsoon defined by critical values of atmospheric variables: Indian summer monsoon case, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8441, https://doi.org/10.5194/egusphere-egu23-8441, 2023.

Knowledge of the onset, cessation and length of the rainy season is important for decision-making in various climate sensitive sectors over Eastern Africa. In the agricultural sector for example the forecast information on these characteristics can be used to decide on when and what to plant.  We customize the Weather Research and Forecasting (WRF) model over the region and evaluate the skill of producing the onset and cessation over the region. The WRF regional climate model is utilised in sub-seasonal to seasonal forecasting over the region.  We utilize the threshold on accumulated rainfall method for calculating the rainfall onset and cessation as is currently done operationally over the region by the IGAD Climate Prediction and Applications Centre.   The customization experiments focus on the land surface, cumulus and microphysics schemes for the long rains (March-April- May), June to September and the short rains (October-November-December). In this study 3 land surface schemes, 5 cumulus and 6 microphysics schemes are utilized in combination with other physics schemes.  The WRF model is able to simulate the seasonal rainfall over the region. In addition it is shown that some physics combinations represent the onset and cessation  dates  better compared to others. The preliminary results  highlight the usefulness of the WRF model in reproducing the onset and cessation characteristics over the region. 

How to cite: Gudoshava, M., Bahaga, T., Barimalala, R., Sobolowski, S., Atheru, Z., Demissie, T., and Artan, G.: Evaluating the Performance of the WRF model in reproducing the Rainfall Onset and Cessation  over Eastern  Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14836, https://doi.org/10.5194/egusphere-egu23-14836, 2023.

The Climate Predictability Tool (CPT) is a well established tool for creating calibrated objective predictions of seasonal rainfall anomalies, and is used for this purpose by many institutions including  the IGAD Climate Prediction and Applications Centre (ICPAC)  to create operational forecasts for the Greater Horn of Africa wet seasons. CPT can also be used to predict other variables such as wet season onset. Such predictions require a non spatially dependent definition of onset, in our case we define onset as the number of days into the season when rainfall reaches 10% of seasonal rainfall for that location. The CPT forecasts are created by detecting relationships between predictions of precipitation and SST from global dynamical forecasting systems and observed onset patterns using Canonical Correlation Analysis (CCA).  CPT has the advantage that skill statistics are automatically produced for assessing the performance of the forecasts. CPT forecasts of Short rains (October-December) onset have been found to have useful skill.

How to cite: Colman, A.: Hybrid dynamical/statistical forecasts of wet season onset using CCA, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7802, https://doi.org/10.5194/egusphere-egu23-7802, 2023.

Most of the socioeconomic activities in the Greater Horn of Africa (GHA) region are rain dependent, and economic sectors such as agriculture, hydroelectric power generation, and health would greatly benefit from reliable information about onset, cessation, intensity, and frequency of rainfall. 
In a seasonal climate forecast at lead times on the order of weeks or months, uncertainty about these variables is significant, making a case for probabilistic forecasting where uncertainties are communicated along with the forecast.

We present results of an evaluation of the skill of probabilistic rainy season onset forecasts over GHA, which were derived from bias-corrected, long-range, multi-model ensemble precipitation forecasts. A careful analysis of the contribution of the different forecast systems to the overall multi-model skill shows that the improvement over the best performing individual model can largely be explained by the increased ensemble size. An alternative way of increasing ensemble size by blending a single model ensemble with climatology is explored and demonstrated to yield better probabilistic forecasts than the multi-model ensemble. Both reliability and skill of the probabilistic forecasts are better for OND onset than for MAM and JJAS; for the two latter, forecasts are found to be late biased and have only minimal skill relative to climatology. While the overall level of skill is limited in our setup where predictions are made at a horizontal resolution of 0.25 degrees, we find that especially OND forecast skill increases substantially under a metric that evaluates the forecasts at coarser spatial scales.

How to cite: Scheuerer, M., Bahaga, T., Segele, Z., and Thorarinsdottir, T.: Probabilistic Rainy Season Onset Prediction over the Greater Horn of Africa based on Long-Range Multi-Model Ensemble Forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2418, https://doi.org/10.5194/egusphere-egu23-2418, 2023.

The demand for more accurate forecasts in rainy season onset, length and cessation has significantly increased over the Greater Horn of Africa area. Recent failed rainy seasons, and an extended drought over much of the region, have highlighted the need for both reliable and timely forecasts so that action can be taken proactively rather than reactively. One of the major challenges in the weather and climate science community is how to appropriately define and characterize onset in such a way that is both robust and useful to the stakeholders.

As part of the EU H2020 project CONFER (Co-production of Climate Services for east Africa), we revisit the rainfall onset and cessation definitions used over the subcontinent, with a particular focus on the large discrepancies, reaching up to 50 days, in the onset and cessation dates that emerge from different definitions. The climate over the Greater Horn of Africa is highly variable with most of the region classified as arid and semi-arid and only a few areas classified as humid. A regionalization of the thresholds used in the definitions that more accurately accounts for user needs and the amount of total rainfall an area receives is suggested. These regional details are then combined with a probabilistic approach developed in CONFER, based on a widely available multi-model seasonal forecast ensemble, to predict rainy season onset over the Greater Horn of Africa area.

How to cite: Barimalala, R., Gudoshava, M., Demissie, T., Sobolowski, S., Kolstad, E., and Scheuerer, M.: Rainy season onset and cessation over the Greater Horn of Africa area: definitions and forecasts., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12834, https://doi.org/10.5194/egusphere-egu23-12834, 2023.

While it is well known that the interannual variability of Kiremt (boreal summer) Rains in Ethiopia is forced by Sea Surface Temperature (SST) in the Pacific Ocean, the mechanisms for ENSO-Kiremt Rains teleconnections and the role of other oceans are not fully understood. In this study, the Ethiopian Kiremt Rains interannual variability was analyzed using observational data and higher-resolution SST-forced ICON experiments for the period 1981–2017. Such fine-grid global and two-way nests over the Greater Horn of Africa (GHA) were carried out here for the first time. The physical mechanisms that link ENSO influence on the Kiremt Rains in the model and ERA5 reanalysis are also investigated. It is found that the model reasonably simulates the main features of the JJAS rainfall climatology over GHA and also reproduces horizontal wind intensity and patterns at (150, 600, 850, and 925- hPa) levels over Africa. It is shown that there is a substantial skill in reproducing the leading modes of Kiremt Rains interannual variability (r = 0.64), given the SSTs are known. The results suggest that the majority (> 50%) of Kiremt Rains anomalies are driven by Equatorial Pacific SST variability, while the SST effects from other regions counteracted ENSO impact in the model. Consistent with previous studies, it is found that the El Niño phase of the ENSO drives a corresponding large-scale circulation anomaly, which weakens the monsoon trough over the Arabian Peninsula, and descending motion and upper-level convergence right over Ethiopia. The subsidence over the GHA region induces upper (lower) level westerly (easterly) wind anomalies over North Africa, weakening Tropical Easterly Jet, Somali Low-Level Jet, and reducing the moist westerly from Atlantic and Congo basin, and thus a reduction of Kiremt Rains over Ethiopia. The opposite pattern is considered under La Niña events and enhanced surface westerlies leading to wetter Kiremt Rains. This mechanism represents an anomalous Walker-type circulation for the ENSO-Kiremt Rains teleconnection. The results will have ramifications for climate model improvement and seasonal forecast improvement in Ethiopia and GHA.

How to cite: Bahaga, T.: Representation of the Mean Climate and Interannual Variability of Kiremt Rains over the Ethiopian Highlands within ICON AMIP Simulation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16914, https://doi.org/10.5194/egusphere-egu23-16914, 2023.

Information on the onset and cessation of rainy seasons is an important prerequisite for planning the sowing of crops in West Africa. A late onset, but also too early cessation of a rainy season, has a direct impact on plant growth and thus on the crop yield in the region. However, onset and cessation dates of rainy seasons can change under future climatic conditions. Therefore, this information is key for stakeholders and decision-makers to mainstream climate change into agricultural activities and policies for better adaptation in the region.

To obtain information on the onset and cessation of rainy seasons on a regional scale under future climate change, Regional Climate Models (RCMs) are applied to dynamically downscale global climate projections generated by Earth System Models (ESMs). Therefore, regional climate projections provide more detailed information due to the higher spatial resolution compared to the climate projections generated by ESMs.

The study will show initial results on the onset and cessation of rainy seasons in West Africa under two emission scenarios using the Representative Concentration Pathways (RCPs) 2.6 and 8.5 for the end of the century (2071-2100 vs. 1981-2010). The regional climate projections are taken from the Coordinated Output for Regional Evaluations (CORE) embedded in the WCRP Coordinated Regional Climate Downscaling Experiment (CORDEX) for Africa with a spatial resolution of about 25 km. In this initiative, three different RCMs (REMO2015, RegCM4-7, and CCLM5-0-15) were applied to perform the downscaling process.

How to cite: Weber, T., Gbode, I. E., Coulibaly, A., Abel, D., Ziegler, K., Zoungrana, J.-B. B., Traore, S. B., and Paeth, H.: Potential shift of rainy seasons’ onset and cessation under climate change scenarios in West Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5395, https://doi.org/10.5194/egusphere-egu23-5395, 2023.