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Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

The issues of climate change in Senegal have the potential of undermining sustainable development efforts if positive steps are not taken to respond to its adverse consequences. This study documents existing and available literature on impacts of climate change on Small and Medium Enterprises (SMEs) in semi-arid zones of Senegal. It is evident that there are significant negative impacts of climate on SMEs in Senegal. Loss of goods, low productivity and sales as well as loss of income are mainly observed by the small and medium enterprises due to the impacts of increased temperature, soil erosion and salinization, decrease of rainfall, frequency of extreme events on both supply and production processes. Despite this fact, there are limited adaptation and mitigation strategies to climate change at company or enterprise level in order to deal effectively with the changing climate. Ensuring Senegal's enterprises to develop more effective climate change adaptation and mitigation strategies, there is the need for the Senegalese government to support enterprises by providing the necessary resources such as credit, information, training for managers and employees on climate change adaptation strategies and technologies, and investing in climate resilient projects which will reduce significantly the adverse effects of climate change on business operations. [ABSTRACT FROM AUTHOR]

A better understanding of the effects of climate change and land use/cover change (LUCC) on streamflow promotes the long-term water planning and management in the arid regions of northwestern China. In this paper, the Soil and Water Assessment Tool (SWAT) and a separation approach were used to evaluate and separate the effects of climate change and LUCC on streamflow in the Xiying River basin. The SWAT model was calibrated by the hydro-meteorological data from 1980-1989 to obtain the optimum parameters, which were validated by the subsequent application to the period between 1990-2008. Moreover, streamflow under several scenarios with different climate change and land use conditions in 1990-2008 and 2010-2069 were further investigated. Results indicate that, in the period of 1990-2008, the streamflow was dominated by climate change (i.e., changes in precipitation and temperature), which led to a 102.8% increase in the mean annual streamflow, whereas LUCC produced a decrease of 2.8%. Furthermore, in the future period of 2010-2039, the mean annual streamflow will decrease by 5.4% and 4.5% compared with the data of 1961-1990 under scenarios A2 and B2, respectively, while it will decrease by 21.2% and 16.9% in the period of 2040-2069, respectively. [ABSTRACT FROM AUTHOR]

The area–time integral (ATI) method has previously been successfully used to estimate the area-averaged rain-rate distribution and the rainfall volume over an area from radar or from satellite infrared (IR) data. In most cases, the method was implemented over regions or test areas with an assumed homogeneous climatic character, that is, without a strong spatial variation of the rain regime throughout the test area. In the present paper, the behavior of the ATI method is discussed for a test area displaying two strong gradients of the cumulative annual rainfall: one meridional, at the transition between regions having, respectively, a desertic and an equatorial climate and the other zonal, at the transition between land and sea. The studied area is divided into four subtest areas (north, south, land, and sea) over which the ATI computation is applied separately. The linear coefficient relating the radar-observed area-averaged rain rate and the fractional area where the rain is higher than a threshold calculated over the four subtest areas is found to be almost constant, in agreement with the ergodic character of the rain-rate distribution observed in this region. Similarly, the linear coefficient relating the rain volume over the subtest areas to the IR satellite-derived ATI, a parameter analogous to the Geostationary Operational Environmental Satellite (GOES) Precipitation Index (GPI), is found to be very steady, with a mean value of 3.02 mm h-1 and a coefficient of variation of only 8%. These coefficients, as well as the underlying dynamic and microphysical processes, do not seem significantly influenced by the climatic character, even at a short space scale, in the studied area. The ratio of radar rain areas to cloud areas is, notably, almost constant. For a brightness temperature of 235 K, the ratio of the cloud area to rain area is around 1.68. [ABSTRACT FROM AUTHOR]

In recent years, climate extreme events have caused increasing direct economic and social losses in the arid region of northwestern China. Based on daily temperature and precipitation data from 1960 to 2010, this paper discussed the linear trend and abrupt changes of climate indices. The general evolution was obtained by the empirical orthogonal function (EOF), the Mann-Kendall test, and the distribution-free cumulative sum chart (CUSUM) test. The results are as follows: (1) climate showed a warming trend at annual and seasonal scale, with all temperature indices exhibiting statistically significant changes. The warm indices have increased, with 1.37%days/decade of warm days (TX90p), 0.17 °C/decade of warmest days (TXx) and 1.97 days/decade of warm spell duration indicator (WSDI), respectively. The cold indices have decreased, with − 1.89%days/decade, 0.65 °C/decade and − 0.66 days/decade for cold nights (TN10p), coldest nights (TNn) and cold spell duration indicator (CSDI), respectively. The precipitation indices have also increased significantly, coupled with the changes of magnitude (max 1-day precipitation amount (RX1day)), frequency (rain day (R0.1)), and duration (consecutive dry days (CDD)). (2) Abrupt changes of the annual regional precipitation indices and the minimum temperature indices were observed around 1986, and that of the maximum temperature indices were observed in 1996. (3) The EOF1 indicated the overall coherent distribution for the whole study area, and its principal component (PC1) was also observed, showing a significant linear trend with an abrupt change, which were in accordance with the regional observation results. EOF2 and EOF3 show contrasts between the southern and northern study areas, and between the eastern and western study areas, respectively, whereas no significant tendency was observed for their PCs. Hence, the climate indices have changed significantly, with linear trends and abrupt changes noted for all climate indices, which will have serious impacts on water resources and ecological environment in the arid region of China. [ABSTRACT FROM AUTHOR]

Changes in vegetation dynamics play a critical role in terrestrial ecosystems and environments. Remote sensing products and dynamic global vegetation models (DGVMs) are useful for studying vegetation dynamics. In this study, we revised the Community Land Surface Biogeochemical Dynamic Vegetation Model (referred to as the BGCDV_CTL experiment) and validated it for the Tibetan Plateau (TP) by comparing vegetation distribution and carbon flux simulations against observations. Then, seasonal–deciduous phenology parameterization was adopted according to the observed parameters (referred to as the BGCDV_NEW experiment). Compared to the observed parameters, monthly variations in gross primary productivity (GPP) showed that the BGCDV_NEW experiment had the best performance against the in situ observations on the TP. The climatology from the remote sensing and simulated GPPs showed similar patterns, with GPP increasing from northwest to southeast, although the BGCDV_NEW experiment overestimated GPP in the semi-arid and arid regions of the TP. The results show that temperature warming was the dominant factor resulting in the increase in GPP based on the remote sensing products, while precipitation enhancement was the reason for the GPP increase in the model simulation. [ABSTRACT FROM AUTHOR]

Climate change is expected to have important implications for human mobility. This article discusses and contextualizes key insights from a recently published study by Thalheimer, Williams, van der Geest, and Otto in Earth's Future (2021), https://doi.org/10.1029/2020EF001958. The authors synthesize findings from the climate science and impact literature, among others from the IPCC Special Report on Global Warming of 1.5 °C, to explore the role of climatic drivers for human mobility in African drylands. Facing a number of economic, social, and political challenges, these areas are highly vulnerable to global warming and related risks. Climate mobility in this region is the outcome of complex interactions between individual and contextual factors shaping peoples' needs and incentives to move as well as their constraints. As the authors highlight, climate change can influence mobility outcomes through a number of channels, including impacts on food and water security, poverty and livelihood risks, and conflicts. These impacts are relevant for both rural areas and cities, with the latter representing a primary destination for climate‐induced migration in Africa. The complexity and diversity of the climate mobility nexus call for integrative approaches in science and policy that bridge different disciplines and policy sectors. These approaches should be based on fair, equal, and inclusive processes of knowledge production, transfer, and implementation that involve a number of stakeholders. Inclusive deliberations and partnerships across fields and sectors are key elements to comprehensively studying and addressing the realities and manifold challenges faced by both mobile and immobile populations. Key Points: Drylands in Africa are highly exposed and vulnerable to climate change impacts with important implications for human mobilityClimate mobility is the outcome of complex interactions between individual and contextual factors shaping mobility decisions, outcomes, and risksIntegrative approaches in science and policy are needed to address the complex nexus between climate change and human mobility [ABSTRACT FROM AUTHOR]

It is a matter of current study to determine potential climate changes in different parts of the world, especially in regions like a basin which has the potential to affect socioeconomic and environmental issues in a defined area. This study provides a comparison between several climate change indices trends of two very different basins in Mexico, one located in the northern arid region (the Conchos River basin) and the other in the southern humid area (the Usumacinta River basin). First, quality control, homogenization, and completion of the missing data were applied before calculating the climate change indices and their respective trends for the combined period 1961–1994. A clear warming signal was found for the two basins in addition to an increment in the DTR, in agreement with other studies in Mexico. Also, the Conchos River basin was found to be more humid and the Usumacinta River basin drier, in accordance to a supposed seesaw behavior indicated in previous analysis. [ABSTRACT FROM AUTHOR]

Water-use efficiency (WUE), defined as the ratio of net primary productivity (NPP) to evapotranspiration (ET), is an important indicator to represent the trade-off pattern between vegetation productivity and water consumption. Its dynamics under climate change are important to ecohydrology and ecosystem management, especially in the drylands. In this study, we modified and used a late version of Boreal Ecosystem Productivity Simulator (BEPS), to quantify the WUE in the typical dryland ecosystems, Temperate Eurasian Steppe (TES). The Aridity Index (AI) was used to specify the terrestrial water availability condition. The regional results showed that during the period of 1999–2008, the WUE has a clear decreasing trend in the spatial distribution from arid to humid areas. The highest annual average WUE was in dry and semi-humid sub-region (DSH) with 0.88 gC mm-1 and the lowest was in arid sub-region (AR) with 0.22 gC mm-1. A two-stage pattern of WUE was found in TES. That is, WUE would enhance with lower aridity stress, but decline under the humid environment. Over 65% of the region exhibited increasing WUE. This enhancement, however, could not indicate that the grasslands were getting better because the NPP even slightly decreased. It was mainly attributed to the reduction of ET over 70% of the region, which is closely related to the rainfall decrease. The results also suggested a similar negative spatial correlation between the WUE and the mean annual precipitation (MAP) at the driest and the most humid ends. This regional pattern reflected the different roles of water in regulating the terrestrial ecosystems under different aridity levels. This study could facilitate the understanding of the interactions between terrestrial carbon and water cycles, and thus contribute to a sustainable management of nature resources in the dryland ecosystems. [ABSTRACT FROM AUTHOR]

Here we conduct research to understand the evolutionary history of a shrubby species known as Agarito (Berberis trifoliolata), an endemic species to the Chihuahuan Desert. We identify genetic signatures based on plastid DNA and AFLP markers and perform niche modelling and spatial connectivity analyses as well as niche modelling based on records in packrats to elucidate whether orogenic events such as mountain range uplift in the Miocene or the contraction/expansion dynamics of vegetation in response to climate oscillations in the Pliocene/Pleistocene had an effect on evolutionary processes in Agarito. Our results of current niche modelling and palaeomodelling showed that the area currently occupied by Berberis trifoliolata is substantially larger than it was during the Last Interglacial period and the Last Glacial Maximum. Agarito was probably confined to small areas in the Northeastern and gradually expanded its distribution just after the Last Glacial Maximum when the weather in the Chihuahuan Desert and adjacent regions became progressively warmer and drier. The most contracted range was predicted for the Interglacial period. Populations remained in stable areas during the Last Glacial Maximum and expanded at the beginning of the Holocene. Most genetic variation occured in populations from the Sierra Madre Oriental. Two groups of haplotypes were identified: the Mexican Plateau populations and certain Northeastern populations. Haplogroups were spatially connected during the Last Glacial Maximum and separated during interglacial periods. The most important prediction of packrat middens palaeomodelling lies in the Mexican Plateau, a finding congruent with current and past niche modelling predictions for agarito and genetic results. Our results corroborate that these climate changes in the Pliocene/Pleistocene affected the evolutionary history of agarito. The journey of agarito in the Chihuahuan Desert has been dynamic, expanding and contracting its distribution range and currently occupying the largest area in its history. [ABSTRACT FROM AUTHOR]

The regression tree method is used to upscale evapotranspiration (ET) measurements at eddy-covariance (EC) towers to the grassland ecosystems over the Dryland East Asia (DEA). The regression tree model was driven by satellite and meteorology datasets, and explained 82% and 76% of the variations of ET observations in the calibration and validation datasets, respectively. The annual ET estimates ranged from 222.6 to 269.1 mm yr−1 over the DEA region with an average of 245.8 mm yr−1 from 1982 through 2009. Ecosystem ET showed decreased trends over 61% of the DEA region during this period, especially in most regions of Mongolia and eastern Inner Mongolia due to decreased precipitation. The increased ET occurred primarily in the western and southern DEA region. Over the entire study area, water balance (the difference between precipitation and ecosystem ET) decreased substantially during the summer and growing season. Precipitation reduction was an important cause for the severe water deficits. The drying trend occurring in the grassland ecosystems of the DEA region can exert profound impacts on a variety of terrestrial ecosystem processes and functions. [ABSTRACT FROM AUTHOR]

This study analyzed the inter- and inner-annual variations of discharge regimes in the upper and mid reaches of the Heihe River basin. These variations then correlated with temperature and precipitation variations in the area. The differences between the runoff regimes at the upper and mid reaches were compared, and the human impacts on discharge variations in the Heihe River were discussed. The results indicate that in the upper reaches, the long-term trends and periods of discharge and precipitation correlate well. In the mid reaches, the discharge and temperature trends correlate well, and the short discharge and precipitation periods correlate well. Precipitation increases would generate more runoff in both the upper and mid reaches, but the effects of temperature increases on discharge are different in the upper and mid reaches. Temperature increases would enhance the glacial ablation processes and increase runoff in the upper reaches. However, temperature increases would increase the evaporation and decrease runoff in the mid reaches. After the 1980s, higher temperature enhanced snow and glacial melt, and increasing precipitation increased the discharge in the upper reaches. Although increasing precipitation increased some discharge, great human activities caused a notable discharge decrease in the 1990s in the mid reaches, especially during the spring to autumn when large amounts of water resources were used for irrigation. In summary, both precipitation and temperature impact the availability of water resources in the study area, and active and effective adaptation strategies should be developed to improve the efficiency of water resource exploration and to prevent the desertification processes in the arid Heihe River basin. [ABSTRACT FROM AUTHOR]

An atmospheric general circulation model (AGCM) is coupled to three different land surface schemes (LSSs), both individually and in combination (i.e., the LSSs receive the same AGCM forcing each time step and the averaged upward surface fluxes are passed back to the AGCM), to study the uncertainty of simulated climatologies and variabilities caused by different LSSs. This tiling of the LSSs is done to study the uncertainty of simulated mean climate and climate variability caused by variations between LSSs. The three LSSs produce significantly different surface fluxes over most of the land, no matter whether they are coupled individually or in combination. Although the three LSSs receive the same atmospheric forcing in the combined experiment, the inter-LSS spread of latent heat flux can be larger or smaller than the individually coupled experiment, depending mostly on the evaporation regime of the schemes in different regions. Differences in precipitation are the main reason for the different latent heat fluxes over semiarid regions, but for sensible heat flux, the atmospheric differences and LSS differences have comparable contributions. The influence of LSS uncertainties on the simulation of surface temperature is strongest in dry seasons, and its influence on daily maximum temperature is stronger than on minimum temperature. Land–atmosphere interaction can dampen the impact of LSS uncertainties on surface temperature in the tropics, but can strengthen their impact in middle to high latitudes. Variations in the persistence of surface heat fluxes exist among the LSSs, which, however, have little impact on the global pattern of precipitation persistence. The results provide guidance to future diagnosis of model uncertainties related to LSSs. [ABSTRACT FROM AUTHOR]

Aim To explore potential shifts in vegetation and fire regime in some dominant forest types in the north-eastern part of the Mediterranean basin under climate change. Location Two altitudinal gradients in the continental part of Greece. Methods We developed a forest gap dynamics simulator that provides feedback from the stand to its water balance and flammability status. The model is used to simulate vegetation dynamics in two mountainous areas, currently found under different aridity conditions. Two climatic change scenarios (Intergovernmental Panel on Climate Change A1 and B2) were applied to explore differences in the response of the established forest types. In addition we explicitly accounted for the role of fire, under both current and altered climate patterns. Results Fire was identified to play a significant role in low-altitude sites. Its significance increased with the severity of the climate change scenario. Elevational shifts of the dominant species were simulated for each site, while in some cases these changes were associated with a shorter fire cycle and a frequent resetting of processes of vegetation change. Main conclusions Our simulations suggest a greater vulnerability of mountainous Mediterranean drier areas regarding compositional alteration and flammability trends. Changes in vegetation could take place through both a discrete and synergistic realization of changes in the drought stress and fire frequency. [ABSTRACT FROM AUTHOR]

Understanding of climate influence on crop yields can help in the design of policies to reduce climate-related vulnerability in many parts of the world, including the target of this case study—the state of Ceará, Brazil. The study has examined the relationships between climate variations and corn yields and, in addition, has estimated the potential predictability of corn yields in Ceará drawing on the now well-established seasonal predictability of the region’s climate based on prevailing patterns of sea surface temperature (SST), especially in the tropical Atlantic and tropical Pacific Oceans. The relationships between corn yields and climate variables have been explored using observed data for the period of 1952–2001. A linear regression–based corn-yield model was evaluated by comparing the model-simulated yields with the observations using three goodness-of-fit measures: the coefficient of determination, the index of agreement, and the mean absolute error. A comparative performance analysis was carried out on several climate variables to determine the most appropriate climate index for simulating corn yields in Ceará. A weather index was defined to measure the severity of drought and flooding conditions in the growing season for corn. The analysis indicated that the weather index is the best climate parameter for simulating corn yields in Ceará. The observed weather index can explain 56.8% of the variance of the observed corn yields. High potential predictability of the weather index was revealed by the evaluation of an ensemble of 10 runs with the NCEP Regional Spectral Model nested into the ECHAM4.5 atmospheric general circulation model, driven with observed SSTs in each season for the period of 1971–2000. Whereas these runs are based on the actual observed SST pattern in each season, other studies have shown that persistence of SST over several months is sufficient for a true predictive capability. The aim here was to show that the SST-forced component of climate variation does translate into the weather features that are important for crop yields. Indeed, the results demonstrate the striking extent to which the year-to-year changes in SST force local climate characteristics that can specify the year-to-year variations in corn yields. The variance of corn yield explained by the SST-driven model was 49.5%. [ABSTRACT FROM AUTHOR]

In situ observations of surface air and dewpoint temperatures and air pressure from over 15 000 weather stations and from ships are used to calculate surface specific (q) and relative (RH) humidity over the globe (60°S–75°N) from December 1975 to spring 2005. Seasonal and interannual variations and linear trends are analyzed in relation to observed surface temperature (T) changes and simulated changes by a coupled climate model [namely the Parallel Climate Model (PCM)] with realistic forcing. It is found that spatial patterns of long-term mean q are largely controlled by climatological surface temperature, with the largest q of 17–19 g kg-1 in the Tropics and large seasonal variations over northern mid- and high-latitude land. Surface RH has relatively small spatial and interannual variations, with a mean value of 75%–80% over most oceans in all seasons and 70%–80% over most land areas except for deserts and high terrain, where RH is 30%–60%. Nighttime mean RH is 2%–15% higher than daytime RH over most land areas because of large diurnal temperature variations. The leading EOFs in both q and RH depict long-term trends, while the second EOF of q is related to the El Niño–Southern Oscillation (ENSO). During 1976–2004, global changes in surface RH are small (within 0.6% for absolute values), although decreasing trends of -0.11% ∼ -0.22% decade-1 for global oceans are statistically significant. Large RH increases (0.5%–2.0% decade-1) occurred over the central and eastern United States, India, and western China, resulting from large q increases coupled with moderate warming and increases in low clouds over these regions during 1976–2004. Statistically very significant increasing trends are found in global and Northern Hemispheric q and T. From 1976 to 2004, annual q (T) increased by 0.06 g kg-1 (0.16°C) decade-1 globally and 0.08 g kg-1 (0.20°C) decade-1 in the Northern Hemisphere, while the Southern Hemispheric q trend is positive but statistically insignificant. Over land, the q and T trends are larger at night than during the day. The largest percentage increases in surface q (∼1.5% to 6.0% decade-1) occurred over Eurasia where large warming (∼0.2° to 0.7°C decade-1) was observed. The q and T trends are found in all seasons over much of Eurasia (largest in boreal winter) and the Atlantic Ocean. Significant correlation between annual q and T is found over most oceans (r = 0.6–0.9) and most of Eurasia (r = 0.4–0.8), whereas it is insignificant over subtropical land areas. RH–T correlation is weak over most of the globe but is negative over many arid areas. The q–T anomaly relationship is approximately linear so that surface q over the globe, global land, and ocean increases by ∼4.9%, 4.3%, and 5.7% per 1°C warming, respectively, values that are close to those suggested by the Clausius–Clapeyron equation with a constant RH. The recent q and T trends and the q–T relationship are broadly captured by the PCM; however, the model overestimates volcanic cooling and the trends in the Southern Hemisphere. [ABSTRACT FROM AUTHOR]

In arid and semiarid regions most of the solar radiation penetrates through the canopy and reaches the ground, and hence the turbulent exchange coefficient under canopy Cs becomes important. The use of a constant Cs that is only appropriate for thick canopies is found to be primarily responsible for the excessive warm bias of around 10 K in monthly mean ground temperature over these regions in version 2 of the Community Climate System Model (CCSM2). New Cs formulations are developed for the consistent treatment of undercanopy turbulence for both thick and thin canopies in land models, and provide a preliminary solution of this problem. [ABSTRACT FROM AUTHOR]

Climate change is estimated to exacerbate existing challenges faced by smallholder farmers in Sub-Sahara Africa. However, limited studies quantify the extent of variation in climate change impact under these systems at the local scale. The Decision Support System for Agro-technological Transfer (DSSAT) was used to quantify variation in climate change impacts on maize yield under current agricultural practices in semi-arid regions of Senegal (Nioro du Rip) and Ghana (Navrongo and Tamale). Multi-benchmark climate models (Mid-Century, 2040–2069 for two Representative Concentration Pathways, RCP4.5 and RCP8.5), and multiple soil and management information from agronomic surveys were used as input for DSSAT. The average impact of climate scenarios on grain yield among farms ranged between −9% and −39% across sites. Substantial variation in climate response exists across farms in the same farming zone with relative standard deviations from 8% to 117% at Nioro du Rip, 13% to 64% in Navrongo and 9% to 37% in Tamale across climate models. Variations in fertilizer application, planting dates and soil types explained the variation in the impact among farms. This study provides insight into the complexities of the impact of climate scenarios on maize yield and the need for better representation of heterogeneous farming systems for optimized outcomes in adaptation and resilience planning in smallholder systems. [ABSTRACT FROM AUTHOR]