Predictability of weather and climate

Abstract:

Despite the growing demand for long-range ENSO predictions beyond one year, quantifying the skill at these lead-times remains limited. This is partly due to inadequate long-records of seasonal reforecasts that make skill estimates of irregular ENSO events quite challenging. Here, we investigate ENSO predictability and the dependency of prediction skill on the ENSO cycle using 110-years of 24-month-long 10-member ensemble reforecasts from ECMWF’s coupled model (SEAS5-20C) initialised on 1st Nov/1st May during 1901-2010. Results show that Nino3.4 SST can be skilfully predicted up to ~18 lead months when initialised on 1st Nov, but skill drops at ~12 lead months for May starts that encounter boreal spring predictive barrier in year 2. The skill beyond the first year is highly conditioned to the phase of ENSO: Forecasts initialised at peak El Niño are more skilful in year 2 than those initialised at peak La Niña, with the transition to La Niña being more predictable than to El Niño. This asymmetry is related to the subsurface initial conditions in the western equatorial Pacific: peak El Niño states evolving into La Niña are associated with strong upper ocean heat discharge of the western Pacific, the memory of which stays beyond one year. In contrast, the western Pacific recharged state associated with La Niña is usually weaker and shorter-lived, being a weaker pre-conditioner for subsequent El Niño, the year after. High prediction skill of ENSO events beyond one year provides motivation for extending the lead-time of operational seasonal forecasts up to 2 years.

Abstract:

Agricultural and environmental policies are being fundamentally reviewed and redesigned in the UK following its exit from the European Union. The UK government and the Devolved Administrations recognise that current land use is not sustainable and that there is now an unprecedented opportunity to define a better land strategy that responds fully to the interconnected challenges of climate change, biodiversity loss and sustainable development. This paper presents evidence from three pathways (current trends, sustainable medium ambition, and sustainable high ambition) to mid-century that were co-created with UK policymakers. The pathways were applied to a national integrated food and land-use model (the FABLE calculator) to explore potential synergies and trade-offs between achieving multiple sustainability targets under limited land availability and constraints to balance food supply and demand at national and global levels. Results show that under the Current Trends pathway all unprotected open natural land would be converted to urban, agriculture and afforested land, with the consequence that from 2030 onwards tree planting targets could not be met. In contrast, the two sustainable pathways illustrate how dietary change, agricultural productivity improvements and waste reduction can free up land for nature recovery and carbon sequestration. This enables a transition to a sustainable food and land-use system that provides a net carbon sink with up to 44% of land able to support biodiversity conservation. We highlight key trade-offs and synergies, which are important to consider for designing and implementing emerging national policies. These include the strong dependence of climate, food and biodiversity targets on dietary shifts, sustainable improvements in agricultural productivity, improved land-use design for protecting and restoring nature, and rapid reductions in food loss and waste.

Abstract:

Despite continuous improvements, precipitation forecasts are still not as accurate and reliable as those of other meteorological variables. A major contributing factor to this is that several key processes affecting precipitation distribution and intensity occur below the resolved scale of global weather models. Generative adversarial networks (GANs) have been demonstrated by the computer vision community to be successful at super-resolution problems, that is, learning to add fine-scale structure to coarse images. Leinonen et al. (2020, https://doi.org/10.1109/TGRS.2020.3032790) previously applied a GAN to produce ensembles of reconstructed high-resolution atmospheric fields, given coarsened input data. In this paper, we demonstrate this approach can be extended to the more challenging problem of increasing the accuracy and resolution of comparatively low-resolution input from a weather forecasting model, using high-resolution radar measurements as a “ground truth.” The neural network must learn to add resolution and structure whilst accounting for non-negligible forecast error. We show that GANs and VAE-GANs can match the statistical properties of state-of-the-art pointwise post-processing methods whilst creating high-resolution, spatially coherent precipitation maps. Our model compares favorably to the best existing downscaling methods in both pixel-wise and pooled CRPS scores, power spectrum information and rank histograms (used to assess calibration). We test our models and show that they perform in a range of scenarios, including heavy rainfall.

Abstract:

There is an urgent need for countries to transition their national food and land-use systems toward food and nutritional security, climate stability, and environmental integrity. How can countries satisfy their demands while jointly delivering the required transformative change to achieve global sustainability targets? Here, we present a collaborative approach developed with the FABLE—Food, Agriculture, Biodiversity, Land, and Energy—Consortium to reconcile both global and national elements for developing national food and land-use system pathways. This approach includes three key features: (1) global targets, (2) country-driven multi-objective pathways, and (3) multiple iterations of pathway refinement informed by both national and international impacts. This approach strengthens policy coherence and highlights where greater national and international ambition is needed to achieve global goals (e.g., the SDGs). We discuss how this could be used to support future climate and biodiversity negotiations and what further developments would be needed.