Reliable and detailed climate information is essential in the design of effective strategies for managing risks and adapting to climate variability and change.
It helps farmers to adequately plan for the agricultural season.
Their planning, however, depends on the availability of high quality, long-term observations on the adequacy of climate predictions from numerical models to depict future regional climate conditions, and on a thorough understanding and appreciation of the uncertainties and constraints associated with the use of both data and national, regional and global models.
There must be a two-way interaction or dialogue between the information providers, in this case, the Meteorological Services Department (Met Office), and the users in government and public/private sectors.
If the World Climate Research Programme, the Global Climate Observing System and the World Meteorological Organisation have teamed up to demonstrate key elements of an effective climate risk management strategy for East Africa, the Met office can also do the same given that our economy is agriculture-based.
It is sad that it appears climate information to the farmers is “truncated”, making it difficult for them to plan for the farming season. If anything, SeedCo and Panner Seeds among other seed houses, have assumed the role of the Met Office by disseminating information that could assist farmers to adapt to climate variability.
But what has happened to the Met Office? Apart from their banal forecast: “it will be sunny in the morning; partly cloudy by day and we can expect some thunderstorm and rain later in the day in some parts of the country”. Daily — This is unsustainable!
The Met Office should move a step further than this and promote understanding and dialogue amongst providers and users of climate information as well as build confidence in observations and models.
They should promote fuller understanding of climate information for more effective communication of information to decision-makers; “mainstream” climate change into the planning and activities of government, and rescue, digitise, and quality-control existing data records and utilise re-analyses to fill gaps in time series.
The country should also develop sector-specific indices of particular value to the region, share national data for regional analyses and strengthen the capacity of the Met Office in downscaling to develop and analyse climate scenarios for national, regional and other assessments.
This will entail that the Met Office uses the latest techniques in downscaling climate models, including multiple-model ensembles, to improve the quality and accuracy of projections and form partnerships between national agencies that provide and use climate information to produce climate scenarios that are the most relevant to the region and sectors of interest.
Given the prevailing dry conditions that have developed so far this year with many parts of the country receiving less than a quarter of their usual rainfall for the September–December period, lack of strategies to manage climate inconsistency could have adverse impact on agriculture and water supply in the country.
Hence, reanalysis would provide a coherent multivariate reconstruction of the global atmosphere over an extended period of time, based on information from a wide range of observations.
The reconstructions could be created with model-based data assimilation methods similar to those employed for numerical weather prediction. Agreed, reanalysis rely on a forecast model to propagate information in space and time, and to impose physically meaningful constraints on the estimates produced.
In this way it is possible, for example, to extract useful information about rainfall from satellite observations of temperature and humidity, or to infer large-scale features of the global circulation in the early 20th century from surface pressure observations available at the time.
Since first produced in the 1980s, reanalysis data have been widely used for research in the atmospheric sciences.
Reanalysis is a rapidly evolving field; successive generations of products have improved in quality and diversity, reflecting major advances in modelling and data assimilation achieved in recent decades.
New reanalysis products additionally benefit from improvements in the observations and other required input datasets, such as specifications of sea surface temperature and sea-ice concentration.
These are the result of ongoing efforts in data reprocessing and recalibration by satellite agencies and other data providers, as well as recovery and digitisation of early instrumental data that have not previously been used.