Late-season Rainfall Research Articles

Interdecadal change in the relationship between the South China late rainy season rainfall and equatorial Pacific SSTs

Abstract The South China (SC) late rainy season rainfall (SCLR) is important to people’s livelihoods and properties of this densely populated and economically developed region. Based on observation and reanalysis datasets, this study identifies that the relationship between the SCLR and equatorial Pacific SSTs (EPSSTs) experiences an interdecadal change around the late 1970s. The SCLR is negatively correlated with the eastern EPSSTs during 1948–1977 (the previous epoch) but positively correlated with the central EPSSTs during 1978–2022, especially during the last three decades 1993–2022 (the post epoch). This is due to the interdecadal change in El Niño flavors and EPSSTs-tropical Atlantic SSTs (TASSTs) relationship. With the increasing frequency of central Pacific El Niños in the post epoch, the El Niño-related warm SST anomaly center shifts from the eastern equatorial Pacific (EEP) to the central equatorial Pacific (CEP). Correspondingly, the anomalous cyclone exerted by the CEP warming reaches SC and causes rainfall surplus there (westward propagation pathway). In contrast, the EEP warming in the previous epoch can’t influence the SCLR through the westward propagation pathway, but through shifting the westerly jet southward via heating the tropical troposphere. The southward shifted westerly jet crashes the Qinghai-Tibet Plateau, triggering cyclonic circulations across the northern East Asia and North Pacific, which in turn cause anticyclonic circulations over the western SC and reduce SC rainfall (eastward propagation pathway). On the other hand, the CEP warming in the post epoch barely influence the SCLR through the eastward propagation pathway because of the enhanced negative relationship between EPSSTs and TASSTs.

Impact of climate change on food security of smallholder farmers in Shashogo district, central Ethiopia

Climate variability/climate change has become the biggest challenge to food security. Objective of this study is to determine the impact of climate change/variability on food security. The study utilized primary and secondary data sources obtained through household surveys. The result shows that rainfall in Belg varies greatly, suggesting that seasonal harvests in Belg are failing, leading to a decline in production levels in certain quantities and limited food availability. Rainfall in Kiremt fluctuates moderately, while annual rainfall has the lowest fluctuations. Crop prices increase every year in recently. This change in agricultural crop yields was due to climate change manifested in price volatility. Consumers have been adversely affected by an increase in crop prices. As reported FGD group that crop yields have been declining from year to year consequences of this are fluctuations in upcoming and late season rainfall, an unusual rise in temperature, flooding and the spread of the American warm, which the community to shift their livelihood to non-agricultural activities. Next to crop farming, raising livestock is one of the main sources of income for rural communities; nevertheless, the productivity and stocks of livestock may be impacted by climate change. Food stability is impacted not only by climate variability but also by increasingly frequent and intense extreme climate events that affect availability, access, and use. Stakeholders who would take steps to combat a loss of agricultural production in the Belg season were presented with the study’s results.

Environment, Grain Development, and Harvesting Strategy Effects on Zearalenone Contamination of Grain from Fusarium Head Blight-Affected Wheat Spikes.

Fusarium head blight (FHB), caused by the fungus Fusarium graminearum, is associated with grain contamination with mycotoxins such as deoxynivalenol (DON) and zearalenone (ZEA). Unlike DON, less is known about factors affecting ZEA production during FHB epidemics. The objective of this study was to quantify ZEA contamination of wheat grain as influenced by temperature, relative humidity, FHB index (IND), grain maturation, simulated late-season rainfall, and harvest timing. Mean ZEA concentrations were low (<1.1 ppm) during the early stages of grain development (25 to 31 days after anthesis [DAA]) but rapidly increased 35 to 51 DAA in field experiments, particularly under rainy conditions. Five or ten consecutive days with simulated rainfall shortly before harvest greatly increased ZEA contamination. Similarly, extremely high levels of ZEA (51.8 to 468.6 ppm) were observed in grain from spikes exposed to 100% relative humidity (RH) at all tested temperatures and mean IND levels under controlled conditions. Interestingly, at RH ≤ 90%, ZEA concentrations were very low (0.1 to 3.6 ppm) at all tested temperatures, even at IND above 90%. At 100% RH, mean ZEA contamination was significantly higher at 20 and 25°C (235.1 and 278.2 ppm) than at 30°C (104.7 ppm). Grain harvested early and not exposed to rainfall had lower mean ZEA than grain harvested late and/or subjected to preharvest rainfall. This study was the first to associate ZEA contamination of grain from FHB-affected wheat spikes with temperature and moisture and show through designed experiments that early harvest could be a useful strategy for reducing ZEA contamination.

Recent cover crop adoption is associated with small maize and soybean yield losses in the United States.

Cover crops are gaining traction in many agricultural regions, partly driven by increased public subsidies and by private markets for ecosystem services. These payments are motivated by environmental benefits, including improved soil health, reduced erosion, and increased soil organic carbon. However, previous work based on experimental plots or crop modeling indicates cover crops may reduce crop yields. It remains unclear, though, how recent cover crop adoption has affected productivity in commercial agricultural systems. Here we perform the first large-scale, field-level analysis of observed yield impacts from cover cropping as implemented across the US Corn Belt. We use validated satellite data products at sub-field scales to analyze maize and soybean yield outcomes for over 90,000 fields in 2019-2020. Because we lack data on cover crop species or timing, we seek to quantify the yield impacts of cover cropping as currently practiced in aggregate. Using causal forests analysis, we estimate an average maize yield loss of 5.5% on fields where cover crops were used for 3 or more years, compared with fields that did not adopt cover cropping. Maize yield losses were larger on fields with better soil ratings, cooler mid-season temperatures, and lower spring rainfall. For soybeans, average yield losses were 3.5%, with larger impacts on fields with warmer June temperatures, lower spring and late-season rainfall, and, to a lesser extent, better soils. Estimated impacts are consistent with multiple mechanisms indicated by experimental and simulation-based studies, including the effects of cover crops on nitrogen dynamics, water consumption, and soil oxygen depletion. Our results suggest a need to improve cover crop management to reduce yield penalties, and a potential need to target subsidies based on likely yield impacts. Ultimately, avoiding substantial yield penalties is important for realizing widespread adoption and associated benefits for water quality, erosion, soil carbon, and greenhouse gas emissions.

Future Land Precipitation Changes Over the North American Monsoon Region Using CMIP5 and CMIP6 Simulations

AbstractChanges in the North American Monsoon (NAM), a circulation system that transports moisture into western Mexico and the southwest U.S., can have substantial impacts on water resources and agriculture. Here, we utilize future projections from Phase 6 and 5 of the Coupled Model Intercomparison Project (CMIP) to assess monthly changes in land precipitation and the leading mechanisms resulting from anthropogenic climate change. Historical CMIP6 simulations of seasonal precipitation demonstrate skill in reproducing NAM rainfall, but mimic precipitation biases observed in previous CMIP generations. Future climate projections from the SSP5‐8.5 pathway produce reductions in precipitation that persist throughout the monsoon season (June–August) but are balanced by precipitation increases during the late monsoon season (September–October) but are not shown in CMIP5 projections. Atmospheric moisture budget analysis reveals that early monsoon rainfall deficits are associated with a combination of greater evaporative demand, a negative dynamic response of vertical moisture advection, and anomalous subsidence. Increases in late monsoon season rainfall are attributed to a positive change in the dynamical term of vertical moisture advection and increases in upward motion. Although minimal changes in total land NAM rainfall are observed, seasonal shifts and the persistence of drier conditions can have significant ecological and societal consequences.

Response of nitrous oxide emissions to individual rain events and future changes in precipitation.

Changing precipitation has the potential to alter nitrous oxide (N2 O) emissions from agricultural regions. In this study, we applied the Coupled Model Intercomparison Project Phase 5 end-of-century RCP 8.5 (business as usual) precipitation projections for the U.S. Upper Midwest and examined the effects of mean precipitation changes, characterized by increased early-season rainfall and decreased mid- to late-season rainfall, on N2 O emissions from a conventionally managed corn (Zea mays L.) cropping system grown in an indoor mesocosm facility over four growing seasons. We also assessed the response of N2 O emissions to over 1,000 individual rain events. Nitrous oxide emissions were most strongly correlated with water-filled pore space (WFPS) and soil nitrogen (N) status. After rain events, the change in N2 O emissions, relative to pre-rain emissions, was more likely to be positive when soil NO3 - was>40mg N kg-1 soil and soil NH4 + was>10mg N kg-1 soil and was more likely to be negative when soil NO3 - was>40mg N kg-1 soil and soil NH4 + was<10mg N kg-1 soil. Similarly, hourly N2 O emissions remained <5nmol m- 2 s-1 when combined NH4 + + NO3 - was<20mg N kg-1 soil or NH4 + and NO3 - were<5 and 20mg N kg-1 soil, respectively. Rain event magnitude did not substantially affect the change in N2 O flux. Finally, growing-season N2 O emissions, soil moisture, and inorganic N content were not affected by the future precipitation pattern. Near-optimal soil WFPS combined with soil N concentrations above the identified thresholds favor higher N2 O emissions.

West African monsoon precipitation impacted by the South Eastern Atlantic biomass burning aerosol outflow

The West African Monsoon (WAM) is a complex system depending on global climate influences and multiple regional environmental factors. Central and Southern African biomass-burning (SABB) aerosols have been shown to perturb WAM during episodic northward inter-hemispheric transport events, but a possible dynamical connection between the core of the SABB aerosol outflow and the WAM system remains unexplored. Through regional climate modeling experiments, we show that SABB aerosols can indeed impact WAM dynamics via two competitive regional scale and inter-hemispheric dynamical feedbacks originating from (i) enhanced diabatic heating occurring in the Southeastern Atlantic low-cloud deck region, and (ii) aerosol and cloud-induced sea surface temperature cooling. These mechanisms, related to aerosol direct, semi-direct, and indirect effects, are shown to have different seasonal timings, resulting in a reduction of June to September WAM precipitation, while possibly enhancing late-season rainfall in WAM coastal areas.

Coupling landscape-scale diagnostics surveys, on-farm experiments, and simulation to identify entry points for sustainably closing rice yield gaps in Nepal

CONTEXTRice is the primary staple food crop in Nepal, contributing 20% of the agricultural gross domestic product and more than 50% of the total calories in the national diet. Nevertheless, the productivity of rice (3.36 t ha−1) is the lowest in South Asia region. OBJECTIVEThe objective of this study was to employ a mixed-methods approach to characterize and decompose yield gaps (YGs) in the context of identifying sustainable intensification pathways for rice production in Nepal. METHODSMethodologies include: a) landscape-scale crop diagnostic survey on crop management, field attributes, and productivity outcomes combined with gridded soil and daily weather data to decompose rice yield gaps into constituent factors with machine learning diagnostics; b) with survey data, computation of key performance indicators to identify factors associated with productivity, profitability, and resource use efficiencies; c) complementary multi-location on-farm experiments (2011–2017) evaluating new agronomic management practices; and d) dynamic simulation (ORYZA3) to derive estimates of rice yield potential. RESULTS AND CONCLUSIONSAnalysis of survey data suggests an exploitable YG of 2.57 t ha−1 (40%) and the total YG of 4.85 t ha−1 (55%) indicating substantial scope for increasing rice yields in Nepal. Frequency of irrigation, amount of late-season rainfall, soil type, amount of early-season rainfall, presence of water stress, soil pH, and nitrogen (N) and phosphorus (P) fertilizer rates are the principal determinants of productivity outcomes in descending ranked order. Efficiency metrics suggest rice farmers in the study region make good use of fertilizer inputs, but since application rates are very low (e.g. most farmers apply <20 kg P ha−1) unsustainable mining of soil nutrients is likely common. Farmers in the top 10% of the yield distribution had lower greenhouse gas emission intensities (−43%), increased water productivity (+66%), and higher use efficiencies of N and P fertilizers (+28% and + 20%, respectively), suggesting that yield intensification can be achieved without tradeoffs with key environmental performance indicators. On-farm experiments conducted over several seasons support insights from surveys by demonstrating that major gains in rice yield (1.86 t ha−1) and profitability (US$ 243 ha−1) are achievable through the adoption of good agronomic practices. SIGNIFICANCEThrough a mixed methods approach, our results suggest that adoption of integrated 'good agronomic practices' can close YGs and improve food security outcomes associated with the rice-based agricultural systems of Nepal while simultaneously preserving or enhancing key sustainability and livelihood objectives.

Season of the drought

Indian Monsoon The Indian monsoon is a critical source of water for hundreds of millions of people, and when it fails to deliver its normal quantity of rain, enormous human, economic, and ecological costs can be incurred. Monsoon droughts are not always seasonal, however. Borah et al. found that nearly half of all monsoonal droughts were subseasonal and characterized by a steep decline in late-season rainfall. Moreover, this type of subseasonal drought appears to be related to a distinct cold anomaly in the North Atlantic Ocean, raising the possibility that monsoon droughts may be more predictable. Science , this issue p. [1335][1] [1]: /lookup/doi/10.1126/science.aay6043

Indian monsoon derailed by a North Atlantic wavetrain.

The forecast of Indian monsoon droughts has been predicated on the notion of a season-long rainfall deficit linked to a warm equatorial Pacific. Here we show that nearly half of all droughts over the past century differ from this paradigm in that they (i) occur when Pacific temperatures are near-neutral and (ii) are subseasonal phenomena, characterized by an abrupt decline in late-season rainfall. This severe subseasonal rainfall deficit can be associated with a Rossby wave from mid-latitudes. Specifically, we find that the interaction of upper-level winds with an episodic North Atlantic vorticity anomaly results in a wavetrain that curves toward East Asia, disrupting the monsoon. This atmospheric teleconnection offers an avenue for improved predictability of droughts, especially in the absence of telltale signatures in the Pacific.

Climate drivers provide valuable insights into late season prediction of Australian wheat yield

Foresight of grain yields prior to harvest would be empowering for many stakeholders along the supply chain from farmers through to bulk handlers, banks and insurance companies. Estimating Australian grain production ahead of harvest is difficult for many reasons including the highly variable year to year rainfall. The rainfall in the final months prior to harvest, can be crucial to final harvest totals. Here we explore the importance of rainfall from September 1, which broadly corresponds to the close of the top-dressing fertilizer application window, for the remaining cropping season in determining final yield. This is assessed via sensitivity analysis of water-limited wheat potential yield totals from historical climate in the APSIM crop model. At locations where the rainfall influences wheat yield, we compare three methods to forecast wheat yields that differ based on the climate data input: 1) climatology approach, which uses 30 years of observed climate data, 2) analogue climatology, which uses information from climate drivers (El-Niño Southern Oscillation and Indian Ocean Dipole) to create analogue years; and 3) dynamical climate forecasts from a general circulation model (ACCESS-S). We find that potential yields strongly depend on in-season plant available water (PAW) where years with high PAW are unaffected by the late season rainfall. Predicting the potential yield from analogue climatology (climate drivers) had the greatest skill, with smallest Root Mean Squared Error of 0.45 t/ha. This approach ranked first for 42% of the study locations compared to the climatology and ACCESS-S forecasting methods. This knowledge can help inform decision makers about the need to incorporate seasonal climate forecasts and the most appropriate climate forecasting method.

Rainfall variability and its effects on growing period and grain yield for rainfed lowland rice under transplanting system in Northeast Thailand

ABSTRACTRainfall variability in Northeast Thailand during 2000–2015 was examined with objectives to determine any changes in rainfall pattern with time, and to determine its effects on duration of rice growing period and grain yield using a simulation model. Variation in mean annual rainfall over 16 years in 93 locations in the region ranged from over 1,600 to less than 1,200 mm, and the locations were grouped into 4 based on the annual rainfall. The change in annual rainfall, and early, mid and late season rainfall was analysed for the rainfall groups. There was a significant reduction in the amount of early season rainfall during the 16-year period in all groups. However, there was no significant change for annual, and mid and late season rainfall. Simulation study showed that the start of rice growing period (SGP) was delayed with reduced early rainfall during the 16 year period and the end of rice growing period (EGP) was also delayed while there was no significant change for the length of rice growing period (LGP). Simulation results showed that grain yield of KDML105, leading variety in Thailand, tended to increase during the 16 year period, as delayed planting time was optimum for achieving maximum yield in all rainfall groups. With general delay in rainfall season, occurrence of late season drought was predicted to be reduced and this helped to increase simulated grain yield. However, adaptation to changing rainfall pattern needs to be planned in advance to maximize its effect.

Microclimate–forage growth linkages across two strongly contrasting precipitation years in a Mediterranean catchment

AbstractGiven the complex topography of California rangelands, contrasting microclimates affect forage growth at catchment scales. However, documentation of microclimate–forage growth associations is limited, especially in Mediterranean regions experiencing pronounced climate change impacts. To better understand microclimate–forage growth linkages, we monitored forage productivity and root‐zone soil temperature and moisture (0–15 and 15–30 cm) in 16 topographic positions in a 10‐ha annual grassland catchment in California's Central Coast Range. Data were collected through two strongly contrasting growing seasons, a wet year (2016–17) with 287‐mm precipitation and a dry year (2017–18) with 123‐mm precipitation. Plant‐available soil water storage (0–30 cm) was more than half full for most of the wet year; mean peak standing forage was 2790 kg ha−1 (range: 1597–4570 kg ha−1). The dry year had restricted plant‐available water and mean peak standing forage was reduced to 970 kg ha−1 (range: 462–1496 kg ha−1). In the wet year, forage growth appeared energy limited (light and temperature): warmer sites produced more forage across a 3–4°C soil temperature gradient but late season growth was associated with moister sites spanning this energy gradient. In the dry year, the warmest topographic positions produced limited forage across a 10°C soil temperature gradient until late season rainfall in March. Linear models accounting for interactions between soil moisture and temperature explained about half of rapid, springtime forage growth variance. These findings reveal dynamic but clear microclimate–forage growth linkages in complex terrain, and thus, have implications for rangeland drought monitoring and dryland ecosystems modeling under climate change.

Contrasting lake ice responses to winter climate indicate future variability and trends on the Alaskan Arctic Coastal Plain

Strong winter warming has dominated recent patterns of climate change along the Arctic Coastal Plain (ACP) of northern Alaska. The full impact of arctic winters may be best manifest by freshwater ice growth and the extent to which abundant shallow ACP lakes freeze solid with bedfast ice by the end of winter. For example, winter conditions of 2016–17 produced record low extents of bedfast ice across the ACP. In addition to high air temperatures, the causes varied from deep snow accumulation on the Barrow Peninsula to high late season rainfall and lake levels farther east on the ACP. In contrast, the previous winter of 2015–16 was also warm, but low snowpack and high winds caused relatively thick lake ice to develop and corresponding high extents of bedfast ice on the ACP. This recent comparison of extreme variation in lake ice responses between two adjacent regions and years in the context of long-term climate and ice records highlights the complexity associated with weather conditions and climate change in the Arctic. Recent observations of maximum ice thickness (MIT) compared to simulated MIT from Weather Research and Forcing (Polar-WRF) model output show greater departure toward thinner ice than predicted by models, underscoring this uncertainty and the need for sustained observations. Lake ice thickness and the extent of bedfast ice not only indicate the impact of arctic winters, but also directly affect sublake permafrost, winter water supply for industry, and overwinter habitat availability. Therefore, tracking freshwater ice responses provides a comprehensive picture of winter, as well as summer, weather conditions and climate change with implications to broader landscape, ecosystem, and resource responses in the Arctic.

Manipulating rainfall to study symptom expression of &lt;i&gt;Botrytis cinerea&lt;/i&gt; infection in wine grapes

Manipulating rainfall to study symptom expression of &lt;i&gt;Botrytis cinerea&lt;/i&gt; infection in wine grapes

Flowers to fruit; early fruit formation and late fruit quality in cherry

Early fruit development (from bloom to stage II) was followed in the current season on variety 'Lapins'; this variety has previously been exposed as susceptible to apical-end skin blemishes such as cracking and woody scar tissue. It has been shown that skin cracking at the apical-end of the fruit in response to late season rainfall is increased by water uptake across the fruit skin, which in turn is encouraged by water droplets forming in the apical-end depression in some varieties. This condition could be further exacerbated by the presence of growth scars. Anecdotal information and industry reports support the development of apical-end skin blemishes in regions which experience a long cool spring and a protracted period of development. To explore this problem, regular flower and fruit monitoring early in the season was undertaken at two sites. The relationship between floral part retention, scarring and the development of larger cracks following late season rainfall was investigated. Style retention was found to increase both scarring and apical-end cracking. Furthermore, to determine if timely progression (rate of development) from floral through to fruit formation affected the formation of apical-end scarring, floral closure was promoted using a growth promoting spray applied at 50, 100% and 2 weeks after full bloom. Preliminary results showed that style retention is increased under a slower progression of flower to fruit.

Quantifying canopy formation processes in fodder beet (Beta vulgaris subsp. vulgaris var. alba L.) crops

Abstract Fodder beet is a highly productive forage crop of expanding use in livestock production systems in temperate regions, notably in Europe and New Zealand. The main determinant of fodder beet productivity is the amount of light intercepted by the crop canopy, which is regulated by temperature and the availability of water and nitrogen (N) for plant development and growth. The quantitative understanding of canopy formation processes under constraining growth conditions is an essential step for the development of biophysical simulation models of new crops for research and predictive purposes. In this study, we provided the first estimates of key canopy formation parameters in fodder beet both under optimum and water- and N-limited supply, in two field experiments in Lincoln, Canterbury, New Zealand. Specifically, the base temperature for leaf appearance in fodder beet was estimated as 0 °C. The range of the critical LAI (c. 90–95% of light interception) was 3–4 m 2 /m 2 . The phyllochron was 48–53 °Cd/leaf in unstressed crops and 60 °Cd/leaf in water stressed crops, with no effect of N supply. Leaf senescence rates varied widely (from 42 to 260 °Cd/leaf) depending on water availability and canopy cover. Leaf expansion, appearance and senescence rates fully recovered following a period of water stress to values similar to those observed in unstressed crops in response to late season rainfall events. Leaf area expansion rates (LAER) ranged from 0.0012 to 0.0034 m 2 /m 2 /°Cd and was reduced both by limited water and N supply. Leaf area senescence rates (LASR) ranged from 0.0005 to 0.0019 m 2 /m 2 /°Cd, with low values recorded during drought periods when crop growth was negligible. Canopy architecture, characterised by the extinction coefficient ( k ), was less sensitive to water stress than canopy expansion or senescence with a conservative value of 0.74. This first quantitative description of fodder beet canopy forming processes can assist the development of predictive approaches, such as biophysical simulation models, for application in research, extension and teaching.

Combining regional moist static energy and ENSO for forecasting of early and late season Indian monsoon rainfall and its extremes

AbstractWe exploit El Niño–Southern Oscillation (ENSO) indices and moist static energy of surface air over the Indian subcontinent and surroundings as predictors of monsoon rainfall over India during early and late seasons, defined here as 20 May to 15 June and 20 September to 15 October, respectively. Although these seasons contribute only ~22% of the entire seasonal rainfall, they clearly affect planning of agriculture and water resources. A simple, nonlinear, statistical model applied to these predictors accounts for ~40% and 45% of the observed variance of early and late season rainfall, respectively, and similar fractions for 3 day maximum rainfall intensity. Forecasted average and 3 day maximum rainfall at grid points covering India show greatest success over central India during the early season and over west central, northwestern, and northern India during the late season, regions where agriculture dominates land use. These predictors, however, offer virtually no predictability of peak season rainfall.

Exotic plant invasions under enhanced rainfall are constrained by soil nutrients and competition.

To predict the net impact of climate change on invasions, it is critical to understand how its effects interact with environmental and biotic context. In a factorial field experiment, we examined how increased late-season rainfall influences the growth and reproductive success of two widespread invasive species (Centaurea solstitialis and Aegilops triuncialis) in heterogeneous Californian grasslands, and, in particular, how its impact depends on habitat type, nutrient addition, and competition with resident species. Rainfall enhancement alone exhibited only weak effects, especially in naturally infertile and relatively uninvaded grasslands. In contrast, watering and fertilization together exhibited highly synergistic effects on both invasive species. However, the benefits of the combined treatment were greatly reduced or offset by the presence of surrounding competitors. Our results highlight the roles of nutrient limitation and biotic resistance by resident competitors in constraining the responses of invasive species to changes in rainfall. In systems with strong environmental control by precipitation, enhanced rainfall may promote invasions mainly under nutrient-rich and disturbed conditions, while having lesser effects on nutrient-poor, native "refuges".

Principal components of sea surface temperatures as predictors of seasonal rainfall in rainfed wheat growing areas ofPakistan

Time-lagged relationships were explored between VARIMAX rotated principal components (RCs) of sea surface temperatures (SSTs) and rainfall periods that are important for rainfed wheat production in Pakistan. Seasonal forecasts were developed using Generalized Additive Models. The first 10 RCs explained 54% of the variance in the SST data. Individual RCs were strongly (r2 ≥ |0.5|) to moderately (r2 ≥ |0.3|) correlated with climatic indices of SST anomalies associated with the El-Nino Southern Oscillation, Pacific Decadal Oscillation, Indian Ocean Dipole, and the tropical Atlantic Ocean. Forecasts of monsoon (July to September), total growing season (November to April), early (November to January) and late season (February to April) rainfall (1961–2010) were developed for Chakwal, Talagang and Islamabad. Important, linear or non-linear, time-lagged relationships were found between the RCs of SSTs and rainfall. Cross-validated forecasts were compared with real-time forecasts to evaluate the ‘true’ forecasting ability of the models. Continuous and categorical probabilistic forecasts were tested with an array of skill scores. Skilful forecasts of pre-season, monsoon and late-season rainfall were produced for the drier sites Chakwal and Talagang and to a lesser extent for the wetter site Islamabad. These simple, statistical forecasts can be developed with minimal financial investment. However, consideration of the potential uses of such forecasts will require a reflective decision framework that engages stakeholders and addresses socio-economic and agro-ecological constraints not included here.