Ahmad, I., Singh, A., Fahad, M., & Waqas, M. M. (2020). Remote sensing-based framework to predict and assess the interannual variability of maize yields in Pakistan using Landsat imagery. Computers and Electronics in Agriculture, 178.
Abstract: Predicting crop yields and their spatio-temporal variability under a changing climate is a challenging but essential undertaking for crop management and policymaking purposes. The availability of information on risks associated with effects of climatic variability on agricultural activity outcomes is critical for stakeholders ranging from individual landowners to national economists alike. This research was conducted as a pilot study to (1) develop satellite remote sensing based estimates of maize acreage in a typical Maize growing region in Pakistan, (2) to develop a statistical-empirical model for prediction of maize yields, and finally, (3) to assess the influence of temperature on inter-annual variability in maize yields across a decade. A total of eight machine learning algorithms were tested for identifying maize growing operations in the Faisalabad district of Pakistan using Landsat 8 imagery. Classification models were evaluated via 200 randomly selected ground-verified points across the study region. Results of the maize mapping exercise were used to estimate interannual maize yields using Landsat-derived multi-temporal normalized difference vegetation index (NDVI) and land surface temperature (LST) data as predictors. Predictors for the yield forecasting model were selected via principal component screening and were fed into a least absolute shrinkage and selection (LASSO) regression model. The yield model thus developed was applied to 10 years of past data (2006-2017) and validated against data recorded by government sources. Finally, predictions spanning the ten years were tested for effects of temperature variability to find evidence of influence of ambient temperature on maize yields. Results indicate that support vector machine classifiers work the best in this landscape (accuracies >90%) and reveal that maize cropping area may be underestimated in government sources by as much as 14%. The LASSO regression models also showed very good fits (validation R2 = 0.95) and were fairly accurate in tracking interannual variations in maize yields (R2 = 0.78.) Results also indicate that the maximum temperature has significant negative influence (R2 = 0.76, P < 0.0001) on maize yields in Faisalabad district. Methods presented in this study should be of use to policymakers for better formulating export-import policies and decisions governing food security issues in the larger region.
|
Arcodia, M. C., Kirtman, B. P., & Siqueira, L. S. P. (2020). How MJO Teleconnections and ENSO Interference Impacts U.S. Precipitation. J. Climate, 33(11), 4621–4640.
Abstract: A composite analysis reveals how the Madden-Julian oscillation (MJO) impacts North American rainfall through perturbations in both the upper-tropospheric flow and regional low-level moisture availability. Upper-level divergence associated with the MJO tropical convection drives a quasi-stationary Rossby wave response to the midlatitudes. This forces a midlatitude upper-level dipolar geopotential height anomaly that is accompanied by a westward retraction of the jet stream and reduced rainfall over the central-eastern North Pacific. A reverse effect is found as the MJO propagates eastward across the Maritime Continent. These large differences in the extratropical upper-level flow, combined with anomalies in the regional supply of water vapor, have a profound impact on southeastern U.S. rainfall. The low-frequency variability, including that associated with ENSO, can modify the seasonal background flow (e.g., El Nino and La Nina basic states) affecting the distribution, strength, and propagation of the intraseasonal oscillation and the extratropical teleconnection patterns. The combined effects of the ENSO and the MJO signals result in both spatial and temporal patterns of interference and modulation of North American rainfall. The results from this study show that during a particular phase of an active MJO, the extratropical response can considerably enhance or mask the interannual ENSO signal in the United States, potentially resulting in anomalies of the opposite sign than that expected during a specific ENSO phase. Analyses of specific MJO events during an El Nino or La Nina episode reveal significant contributions to extreme events via constructive and destructive interference of the MJO and ENSO signals.
|
Bunge, L., & Clarke, A. J. (2014). On the Warm Water Volume and Its Changing Relationship with ENSO. J. Phys. Oceanogr., 44(5), 1372–1385.
Abstract: The interannual, equatorial Pacific, 20 degrees C isotherm depth variability since 1980 is dominated by two empirical orthogonal function (EOF) modes: the "tilt" mode, having opposite signs in the eastern and western equatorial Pacific and in phase with zonal wind forcing and El Nino-Southern Oscillation (ENSO) indices, and a second EOF mode of one sign across the Pacific. Because the tilt mode is of opposite sign in the eastern and western equatorial Pacific while the second EOF mode is of one sign, the second mode has been associated with the warm water volume (WWV), defined as the volume of water above the 20 degrees C isotherm from 5 degrees S to 5 degrees N, 120 degrees E to 80 degrees W. Past work suggested that the WWV led the tilt mode by about 2-3 seasons, making it an ENSO predictor. But after 1998 the lead has decreased and WWV-based predictions of ENSO have failed. The authors constructed a sea level-based WWV proxy back to 1955, and before 1973 it also exhibited a smaller lead. Analysis of data since 1980 showed that the decreased WWV lead is related to a marked increase in the tilt mode contribution to the WWV and a marked decrease in second-mode EOF amplitude and its contribution. Both pre-1973 and post-1998 periods of reduced lead were characterized by "mean" La Nina-like conditions, including a westward displacement of the anomalous wind forcing. According to recent theory, and consistent with observations, such westward displacement increases the tilt mode contribution to the WWV and decreases the second-mode amplitude and its WWV contribution.
|
Bunting, E., Southworth, J., Herrero, H., Ryan, S., & Waylen, P. (2018). Understanding Long-Term Savanna Vegetation Persistence across Three Drainage Basins in Southern Africa. Remote Sensing, 10(7), 1013.
Abstract: Across savanna landscapes of southern Africa, people are strongly tied to the environment, meaning alterations to the landscape would impact livelihoods and socioecological development. Given the human-environment connection, it is essential to further our understanding of the drivers of savanna vegetation dynamics, and under increasing climate variability, to better understand the vegetation-climate relationship. Monthly time series of Advanced Very High-Resolution Radiometer (AVHRR)- and Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation indices, available from as early as the 1980s, holds promise for the large-scale quantification of complex vegetation�climate dynamics and regional analyses of landscape change as related to global environmental changes. In this work, we employ time series based analyses to examine landscape-level vegetation greening patterns over time and across a significant precipitation gradient. In this study, we show that climate induced reductions in Normalized Difference Vegetation Index (NDVI; i.e., degradation or biomass decline) have had large spatial and temporal impacts across the Kwando, Okavango, and Zambezi catchments of southern Africa. We conclude that over time there have been alterations in the available soil moisture resulting from increases in temperature in every season. Such changes in the ecosystem dynamics of all three basins has led to system-wide changes in landscape greening patterns.
|
Cammarano, D., Stefanova, L., Ortiz, B. V., Ramirez-Rodrigues, M., Asseng, S., Misra, V., et al. (2013). Evaluating the fidelity of downscaled climate data on simulated wheat and maize production in the southeastern US. Reg. Environ. Change, 13(1), 101–110.
Abstract: Crop models are one of the most commonly used tools to assess the impact of climate variability and change on crop production. However, before the impact of projected climate changes on crop production can be addressed, a necessary first step is the assessment of the inherent uncertainty and limitations of the forcing data used in these crop models. In this paper, we evaluate the simulated crop production using separate crop models for maize (summer crop) and wheat (winter crop) over six different locations in the Southeastern United States forced with multiple sources of actual and simulated weather data. The paper compares the crop production simulated by a crop model for maize and wheat during a historical period, using daily weather data from three sources: station observations, dynamically downscaled global reanalysis, and dynamically downscaled historical climate model simulations from two global circulation models (GCMs). The same regional climate model is used to downscale the global reanalysis and both global circulation models� historical simulation. The average simulated yield derived from bias-corrected downscaled reanalysis or bias-corrected downscaled GCMs were, in most cases, not statistically different from observations. Statistical differences of the average yields, generated from observed or downscaled GCM weather, were found in some locations under rainfed and irrigated scenarios, and more frequently in winter (wheat) than in summer (maize). The inter-annual variance of simulated crop yield using GCM downscaled data was frequently overestimated, especially in summer. An analysis of the bias-corrected climate data showed that despite the agreement between the modeled and the observed means of temperatures, solar radiation, and precipitation, their intra-seasonal variances were often significantly different from observations. Therefore, due to this high intra-seasonal variability, a cautious approach is required when using climate model data for historical yield analysis and future climate change impact assessments.
|
Canfield Jr., D. E., Hoyer, M. V., Bachmann, R. W., Bigham Stephens, D., & Ruiz-Bernard, I. (2016). Water quality changes at an Outstanding Florida Water: influence of stochastic events and climate variability. Lake and Reservoir Management, 32(3), 297–313.
Abstract: The Santa Fe Lake System (SFS) is an Outstanding Florida Water system in northern peninsular Florida and receives special protection from governmental agencies to prevent impairment of water quality from anthropogenic activities. Since 1986, periods of sudden nutrient increases and declines have occurred along with changes in water clarity documented within a 28-year monthly database. Changes were linked to stochastic events such as an influx of gulls in 1986, the adjacent 5100-ha Dairy Road forest fire in 2007, 3 Category 3 hurricanes that struck Florida in 2004, and droughts. However, increasing trends at SFS were also observed for the yearly measured minimum water chemistry values, as were synchronous changes in these baseline conditions at other nearby lakes, suggesting the lakes were being impacted by a regional environmental factor. These changes corresponded to a period of decreasing precipitation and were related to climate variability, perhaps reflecting phase changes in the Atlantic Multidecadal Oscillation. The possible mechanism for the observed changes most likely relates to alterations in regional precipitation/evaporation rates and resulting changes in groundwater chemistry and hydrology. Long-term trends in water quality at SFS may reverse if Florida enters a long-term period of increasing precipitation.
|
|
Cavaleri, M. A., Coble, A. P., Ryan, M. G., Bauerle, W. L., Loescher, H. W., & Oberbauer, S. F. (2017). Tropical rainforest carbon sink declines during El Niño as a result of reduced photosynthesis and increased respiration rates. New Phytol, 216(1), 136–149.
|
Collins, J. M., Paxton, C. H., Wahl, T., & Emrich, C. T. (2017). Climate and weather extremes. In E. P. Chassignet, J. W. Jones, V. Misra, & J. Obeysekera (Eds.), Florida's climate: Changes, variations, & impacts (pp. 579–615). Gainesville, FL: Florida Climate Institute.
Abstract: This chapter examines Florida’s extreme weather hazards: 1) why they happen, 2) their relation to interannual to multidecadal climate variability, and 3) the potential of each hazard and spatial variability across the state. The weather hazards indicated are under these broad categories: precipitation (rainfall, flooding, droughts), thunderstorms (lightning, hail, convective wind, tornadoes), tropical weather (tropical storms and hurricanes), and temperatures (extreme highs and lows). The conclusions section mainly addresses the challenge of attributing extreme events to human-induced climate change.
|
|
García, P. E., Menénendez, A. N., Podestá, G., Bert, F., Arora, P., & Jobbágy, E. (2018). Land use as possible strategy for managing water table depth in flat basins with shallow groundwater. International Journal of River Basin Management, 16(1), 79–92.
|
Gilford, D. M., Smith, S. R., Griffin, M. L., & Arguez, A. (2013). Southeastern U.S. Daily Temperature Ranges Associated with the El Nino-Southern Oscillation. J. Appl. Meteor. Climatol., 52(11), 2434–2449.
Abstract: The daily temperature range (DTR; daily maximum temperature minus daily minimum temperature) at 290 southeastern U.S. stations is examined with respect to the warm and cold phases of the El Niño�Southern Oscillation (ENSO) for the period of 1948�2009. A comparison of El Niño and La Niña DTR distributions during 3-month seasons is conducted using various metrics. Histograms show each station�s particular distribution. To compare directly the normalized distributions of El Niño and La Niña, a new metric (herein called conditional ratio) is produced and results are evaluated for significance at 95% confidence with a bootstrapping technique. Results show that during 3-month winter, spring, and autumn seasons DTRs above 29°F (16.1°C) are significantly more frequent during La Niña events and that DTRs below 15°F (8.3°C) are significantly more frequent during El Niño events. It is hypothesized that these results are associated spatially with cloud cover and storm tracks during each season and ENSO phase. Relationships between DTRs and ENSO-related relative humidity are examined. These results are pertinent to the cattle industry in the Southeast, allowing ranchers to plan for and mitigate threats posed by periods of low DTRs associated with the predicted phase of ENSO.
|
|
Guo, L., Cheng, J., Luedeling, E., Koerner, S. E., He, J. - S., Xu, J., et al. (2017). Critical climate periods for grassland productivity on China's Loess Plateau. Agricultural and Forest Meteorology, 233, 101–109.
|
Havens, K. E., & Ji, G. (2018). Multiyear oscillations in depth affect water quality in Lake Apopka. Inland Waters, 8(1).
Abstract: We evaluated the effects of multiyear oscillations in depth on water quality in Lake Apopka, a shallow hypereutrophic lake on the Florida peninsula. A 17-year record of monthly data on rainfall, mean depth, total phosphorus (TP), total nitrogen (TN), chlorophyll a (Chl-a), and Secchi disk (SD) transparency was used to quantify relationships. We also looked for long-term trends because the lake has been the subject of major watershed and in-lake programs to reduce concentrations of TP and Chl-a. The dataset (1999 to 2016) included 4 high-water events and 3 drought events. We found no long-term trends in TP or SD and only minor long-term increases in Chl-a and TN. By contrast, all of the water quality attributes were significantly related to mean depth (p < 0.001). Water quality deteriorated with each drought and improved with each high-water period. The results illustrate how variation in climate can control water quality in shallow lakes with legacy nutrients in the sediments. When depth and volume are reduced during droughts in Lake Apopka, the likely scenario is a concentration of nutrients and solutes in the water column as well as greater net effects of benthivorous fish in mobilizing nutrients from the sediments and in creating turbidity. Because shallow lakes are more sensitive to changes in depth than deeper lakes, they can serve as early warning sites for effects of climate change on lake ecosystems.
|
Havens, K. E., Fulton III, R. S., Beaver, J. R., Samples, E. E., & Colee, J. (2016). Effects of climate variability on cladoceran zooplankton and cyanobacteria in a shallow subtropical lake. J. Plankton Res., 38(3), 418–430.
Abstract: In peninsular Florida, USA, rainfall is coupled with the Pacific Sea Surface Temperature Anomaly (SSTA), and rainfall affects mean depth and residence time of shallow lakes. We examined effects of two cycles of variation in rainfall using a 15-year data set from a shallow eutrophic lake dominated by small zooplankton, cyanobacteria and omnivorous fish. In high rainfall periods, the lake was deeper and cladoceran biomass was significantly higher than in dry periods. One factor was correlated with reduced biomass of cladocerans: a 3-fold higher biovolume of cyanobacteria. This led us to examine how variation in rainfall affects cyanobacteria. When cyanobacteria biovolume was high, the movement of water through the lake was low and invariant. Cyanobacteria grew unchecked. When cyanobacteria was reduced and cladocerans attained high biomass, there were intermittent flushing events that may have disrupted algal growth. Water color was elevated similar to 6-fold during the same time periods. Greater color may have made conditions less favorable for cyanobacteria by increasing light attenuation, and also more favorable for cladocerans, by reducing risk from fish. This study provides insight into how future variability in rainfall and drought, which may be exacerbated by global warming, could affect plankton in shallow subtropical lakes.
|
Havens, K. E., Ji, G., Beaver, J. R., Fulton, R. S., & Teacher, C. E. (2019). Dynamics of cyanobacteria blooms are linked to the hydrology of shallow Florida lakes and provide insight into possible impacts of climate change. Hydrobiologia, 828(1), 43–59.
Abstract: Analysis of an 18-year dataset from seven shallow lakes in Florida provides evidence of hydrologic factors controlling dynamics of cyanobacteria blooms. Depth was the most important variable, and there was a synergistic effect with flushing. When the lakes were deep, rainfall led to water discharges and disruption of stagnant conditions that maintained blooms. Factors commonly associated with bloom formation (temperature) or suppression (high organic color, which can be a light-limiting factor) did not play a significant role. A conceptual model illustrates how blooms are regulated. First, the presence of bloom-forming species, high concentrations of nutrients, and lack of large zooplankton create a potential for blooms. Second, climate cycles influence yearly rainfall, resulting in wet years and droughts that affect lake water level and volume. This either stimulates blooms (drought, shallow) or suppresses them (wet, deep). Finally, proximal drivers such as a rain events and a flush of water suppress blooms. The results illustrate how climate variability and weather can control cyanobacteria blooms by affecting several processes long known to influence bloom formation, and provide insight into how climate change might affect occurrence of blooms in nutrient-enriched shallow lakes.
|
|
Hernandez-Ochoa, I. M., & Asseng, S. (2018). Cropping Systems and Climate Change in Humid Subtropical Environments. Agronomy, 8(2), 19.
|
Heve, W. K., Olesen, J. E., Chirinda, N., & Adiku, S. G. K. (2016). Targeted management of organic resources for sustainably increasing soil organic carbon: Observations and perspectives for resource use and climate adaptations in northern Ghana. Acta Agriculturae Scandinavica, Section B -- Soil & Plant Science, 66(2), 178–190.
Abstract: Since soil organic matter (SOM) buffers against impacts of climatic variability, the objective of this study was to assess on-farm distribution of SOM and propose realistic options for increasing SOM and thus the adaptation of smallholder farmers to climate change and variability in the interior northern savannah of Ghana. Data and information on spatial distribution of soil organic carbon (SOC), current practices that could enhance climate adaptation including management of organic resources were collected through biophysical assessments and snap community surveys. Even though homestead fields were more frequently cultivated, higher amounts of SOC (15 +/- 2gkg(-1)) were observed in homesteads when compared to the periphery cropped sections in bushes (SOC=9 +/- 1gkg(-1)). Possibly, a combination of household wastes, droppings of domestic animals that are mostly reared in a free-range system, manures applied to crops and cultural norms of chieftaincy, which cause short-term fallowing of homestead fields could account for the differences in SOC. Use of organic resources for soil amendment among farmers was low (31% of interviewed farmers) due largely to ignorance of fertilizer values of manures and residues, traditions for bush-burning and competing use of organic resources for fuels. Our findings suggest a need for effective management practices, training and awareness aimed at improving management of organic resources and, consequently, increasing SOC and resilience to climate-change-induced risks.
|
|
Ji, G., Havens, K., Beaver, J., & Fulton III, R. (2017). Response of Zooplankton to Climate Variability: Droughts Create a Perfect Storm for Cladocerans in Shallow Eutrophic Lakes. Water, 9(10), 764.
|
Johnson, N. T., Martinez, C. J., Kiker, G. A., & Leitman, S. (2013). Pacific and Atlantic sea surface temperature influences on streamflow in the Apalachicola-Chattahoochee-Flint river basin. Journal of Hydrology, 489, 160–179.
Abstract: Large scale climate phenomena can provide valuable information for regional climate and streamflow in many parts of the world. Several climate phenomena may impact a given area and their value for providing information on streamflow is dependent on first establishing the local relationship. This study was conducted to establish the individual and coupled impacts of the El Nino-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Oscillation (AMO) on streamflow in the Apalachicola-Chattahoochee-Flint (ACF) river basin. Differences in annual and seasonal streamflow using two unimpaired streamflow datasets based on the phase(s) of ENSO, the PDO, and the AMO were evaluated using the nonparametric rank-sum test. Few statistical differences were found for the individual impacts of ENSO and the PDO on annual and seasonal streamflow; differences based on ENSO were largely confined to the southern portion of the basin. Significant differences in annual streamflow based on the AMO were largely confined to the northern half of the basin. Differences in seasonal streamflow based on the AMO were found for much of the year in the northern portion of the basin but were confined to the winter season in the southern portion. Significant differences in annual and seasonal streamflow were found between the La Nina/positive AMO phase and the El Nino/negative AMO phase, between the positive AMO/negative PDO phase and the negative AMO/negative PDO phase, and there appears to be a modulation of the impacts of La Nina by the phase of the AMO. A greater number of stations and a greater magnitude of significant differences were found for the coupled impacts than for the individual impacts of ENSO, the PDO, and the AMO; indicating the importance of the coupled impacts on regional streamflow when establishing the role of annual, decadal, and multidecadal climate variability.
|
Kirtman, B. P., Schneider, E. K., Straus, D. M., Min, D., & Burgman, R. (2011). How weather impacts the forced climate response. Clim Dyn, 37(11-12), 2389–2416.
Abstract: The new interactive ensemble modeling strategy is used to diagnose how noise due to internal atmospheric dynamics impacts the forced climate response during the twentieth century (i.e., 1870–1999). The interactive ensemble uses multiple realizations of the atmospheric component model coupled to a single realization of the land, ocean and ice component models in order to reduce the noise due to internal atmospheric dynamics in the flux exchange at the interface of the component models. A control ensemble of so-called climate of the twentieth century simulations of the Community Climate Simulation Model version 3 (CCSM3) are compared with a similar simulation with the interactive ensemble version of CCSM3. Despite substantial differences in the overall mean climate, the global mean trends in surface temperature, 500 mb geopotential and precipitation are largely indistinguishable between the control ensemble and the interactive ensemble. Large differences in the forced response; however, are detected particularly in the surface temperature of the North Atlantic. Associated with the forced North Atlantic surface temperature differences are local differences in the forced precipitation and a substantial remote rainfall response in the deep tropical Pacific. We also introduce a simple variance analysis to separately compare the variance due to noise and the forced response. We find that the noise variance is decreased when external forcing is included. In terms of the forced variance, we find that the interactive ensemble increases this variance relative to the control.
|
|
Klavans, J. M., Poppick, A., Sun, S., & Moyer, E. J. (2017). The influence of model resolution on temperature variability. Clim Dyn, 48(9-10), 3035–3045.
|
