ITS2.8/AS1.23
Posters on site: Wed, 26 Apr, 14:00–15:45 | Hall X5
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., and Roetter, R.: Characterizing the growing period using seasonal rainfall onset dates in the semi-arid region of Tanzania, EGU General Assembly 2023, Vienna, Austria, 24–28 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, 24–28 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, 24–28 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, 24–28 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, 24–28 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, 24–28 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, 24–28 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, 24–28 Apr 2023, EGU23-12834, https://doi.org/10.5194/egusphere-egu23-12834, 2023.
The mechanisms involved in the onset of the Bay of Bengal summer monsoon (BOBSM) were studied using reanalysis data and numerical model experiments. Results revealed that the weak meridional land–sea thermal contrast (LSTC) over the northern BOB in early spring enhances the lower-tropospheric easterly belt along 10°–15°N, which is unfavorable for the BOBSM onset. The BOBSM onset is driven by the cumulative impact of this LSTC along with the LSTC in the meridional direction across the equator and in the zonal direction across the tropics, together with air–sea interactions. While the LSTC intensifies over the northern BOB, a near-surface northward cross-equatorial flow develops south of India, inducing springtime zonal flow and surface sensible heating over the southern BOB and a pair of cyclones straddling the equator over the central Indian Ocean at 700 hPa. The zonal LSTC in the tropics generates near-surface cyclones over land and anticyclones over the sea. This induces a zonal SST warm pool around 10°N, which produces vertical westerly wind shear to the north and weakens the wintertime easterly aloft and the anticyclone to its north. As the cyclone over southern India develops eastward, the cyclone below 700 hPa develops northward over the eastern BOB in response to the enhancing tropical westerly and surface sensible heating. The wintertime anticyclonic belt and easterly belt split, and the southerly carries water vapor northward over the eastern BOB, heralding the onset of the BOBSM and presenting a delayed response to the springtime LSTC changes.
How to cite: Weihao, S., Yimin, L., and Guoxiong, W.: Delayed response of the onset of the summer monsoon over the Bay of Bengal to land–sea thermal contrast, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10749, https://doi.org/10.5194/egusphere-egu23-10749, 2023.
As cities around the world are growing at a rapid pace, the need to understand their impact on the regional to local climate has become more crucial. Urban settlements are more affected by extreme weather than rural areas. Localised circulation patterns, the topography of the region and micro-scale systems induced by Land-Use Land-Cover (LULC) can modify regional flows to produce unique patterns in the urban region. National Capital Region (NCR) - Delhi, the second biggest urban settlement globally, reported an almost ~20 fold increase in urban and built-up areas in past decades. NCR urbanisation during the past few decades caused a corresponding increase up to 3–5 and 2–4 K in values of LST and T2m, respectively, while a decrease in the magnitude of surface winds up to 2 m s−1 was noted. The LULC plays a crucial role in meteorological models because they determine the crustal properties that interfere with the exchange of energy, moisture, and momentum between the land surface and the atmosphere. This study attempts to assess the impact of legitimate present-state LULC based on AWiFS in the mesoscale model for simulating monsoon weather over NCR Delhi. The newly implemented AWiFS LULC precisely distinguishes the default MODIS classification used in the model framework. Overall, the AWiFS-based simulations showed an improved performance in predicting the study period during the monsoon.
How to cite: Chalakkal, J. B. and Mohan, M.: Impact of accurate representation of Land Use/Land Cover over the National Capital Region (NCR) Delhi in simulating Monsoon Weather , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-605, https://doi.org/10.5194/egusphere-egu23-605, 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, 24–28 Apr 2023, EGU23-16914, https://doi.org/10.5194/egusphere-egu23-16914, 2023.
Posters virtual: Wed, 26 Apr, 14:00–15:45 | vHall AS
Monsoon rain and its year-to-year variability have a profound influence on Africa’s socio-economic structure by heavily impacting agricultural and energy sectors. The current study focuses on major drivers of the east African Monsoon during October-November-December (OND) which is a common onset window for various rainfall patterns, unimodal or bimodal. Major drivers of monsoon rain in the East African sector, covering Tanzania, Malawi, Kenya and Somalia could be different in early or extended boreal winter, due to the relative positioning of the Intertropical convergence zone and its seasonal migration -hence the location and season is the focus here.
Two drivers viz. Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO) both separately indicate very strong positive connections with monsoon(OND) rain. Not only is a strong significant correlation present in OND season with zero seasonal lag, but the signal is also present even a season ahead (before four months too). This is also confirmed using various data sources, detrending the data, using regression technique and covering even earlier as well as later periods. To further strengthen results, a compositing technique is applied that can additionally identify strong signals when different combinations of ENSO and IOD phases act as confounding factors. Results of precipitation anomaly suggest that when IOD and ENSO are both on the same phase in July-August-September (JAS), a significant OND rainfall anomaly is noticed around the east African sector: a deficit (excess) of monsoon rain when both drivers are in the negative (positive) phase. Walker circulation seems to play a major part in transporting signals, via reversing its ascending or descending branch over the regions, when IOD and ENSO are in the same phase. These results can be used for prediction purposes and interestingly, that criterion of IOD and ENSO being of same phase in JAS was again matched in 2022 (both negative) and hence it was possible to deliver early warnings for a deficit in the rain, a season ahead.
Methods to compute the Monsoon Onset as determined by meteorological services such as the Tanzania Meteorological Authority rely on various thresholds (these can vary according to the country). To overcome some of the biases with such methods, other definitions of ‘Onset’ take into account cumulative rainfall amount: these have also been tested. Late (early) Onsets dominate years when ENSO and IOD are both in their negative (positive) phases during the JAS season. The cumulative rainfall and Onset days are correlated such that early Onsets are usually associated with more seasonal rainfall and vice versa. Uncertainty in cumulative rain as well as the Onset date of the OND Monsoon is reduced to a large degree when years are categorised based on ENSO and IOD phases of the previous season. Such results have implications for future planning in optimizing agricultural and energy outputs, mitigating severe consequences and losses, alongside taking advantage of favourable weather scenarios. It will impact the livelihoods of millions of Africans.
How to cite: Roy, I., Troccoli, A., and Mliwa, M.: Major drivers of East African Monsoon variability and improved prediction for Onset dates , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-17545, https://doi.org/10.5194/egusphere-egu23-17545, 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, 24–28 Apr 2023, EGU23-5395, https://doi.org/10.5194/egusphere-egu23-5395, 2023.
