Dominic Kniveton

Satellite Rainfall Estimation Using Combined Passive Microwave and Infrared Algorithms

Abstract The development of a combined infrared and passive microwave satellite rainfall estimation technique is outlined. Infrared data from geostationary satellites are combined with polar-orbiting passive microwave estimates to provide 30-min rainfall estimates. Collocated infrared and passive microwave values are used to generate a database, which is accessed by a cumulative histogram matching approach to generate an infrared temperature–rain-rate relationship. The technique produces initial estimates at 30-min and 12-km resolution ready to be aggregated to the user requirements. A 4-month case study over Africa has been chosen to compare the results from this technique with those of some existing rainfall techniques. The results indicate that the technique outlined here has statistical scores that are similar to other infrared/passive microwave combined algorithms. Comparison with the Geostationary Operational Environmental Satellite (GOES) precipitation index shows that while these algorithms result...

Results of WetNet PIP-2 Project

The second WetNet Precipitation Intercomparison Project (PIP-2) evaluates the performance of 20 satellite precipitation retrieval algorithms, implemented for application with Special Sensor Microwave/Imager (SSM/I) passive microwave (PMW) measurements and run for a set of rainfall case studies at full resolution‐instantaneous space‐timescales. The cases are drawn from over the globe during all seasons, for a period of 7 yr, over a 608N‐ 178S latitude range. Ground-based data were used for the intercomparisons, principally based on radar measurements but also including rain gauge measurements. The goals of PIP-2 are 1) to improve performance and accuracy of different SSM/I algorithms at full resolution‐instantaneous scales by seeking a better understanding of the relationship between microphysical signatures in the PMW measurements and physical laws employed in the algorithms; 2) to evaluate the pros and cons of individual algorithms and their subsystems in order to seek optimal ‘‘front-end’’ combined algorithms; and 3) to demonstrate that PMW algorithms generate acceptable instantaneous rain estimates. It is found that the bias uncertainty of many current PMW algorithms is on the order of 630%. This level is below that of the radar and rain gauge data specially collected for the study, so that it is not possible to objectively select a best algorithm based on the ground data validation approach. By decomposing the intercomparisons into effects due to rain detection (screening) and effects due to brightness temperature‐rain rate conversion, differences among the algorithms are partitioned by rain area and rain intensity. For ocean, the screening differences mainly affect the light rain rates, which do not contribute significantly to area-averaged rain rates. The major sources of differences in mean rain rates between individual algorithms stem from differences in how intense rain rates are calculated and the maximum rain rate allowed by a given algorithm. The general method of solution is not necessarily the determining factor in creating systematic rain-rate differences among groups of algorithms, as we find that the severity of the screen is the dominant factor in producing systematic group differences among land algorithms, while the input channel selection is the dominant factor in producing systematic group differences among ocean algorithms. The significance of these issues are examined through what is called ‘‘fan map’’ analysis. The paper concludes with a discussion on the role of intercomparison projects in seeking improvements to algorithms, and a suggestion on why moving beyond the ‘‘ground truth’’ validation approach by use of a calibration-quality forward model would be a step forward in seeking objective evaluation of individual algorithm performance and optimal algorithm design.

Come rain or shine: An analysis of conflict and climate variability in East Africa

Previous research on environment and security has contested the existence, nature and significance of a climate driver of conflict. In this study, we have focused on small-scale conflict over East Africa where the link between resource availability and conflict is assumed to be more immediate and direct. Using the parameter of rainfall variability to explore the marginal influence of the climate on conflict, the article shows that in locations that experience rebel or communal conflict events, the frequency of these events increases in periods of extreme rainfall variation, irrespective of the sign of the rainfall change. Further, these results lend support to both a ‘zero-sum’ narrative, where conflicting groups use force and violence to compete for ever-scarcer resources, and an ‘abundance’ narrative, where resources spur rent-seeking/wealth-seeking and recruitment of people to participate in violence. Within the context of current uncertainty regarding the future direction of rainfall change over much of Africa, these results imply that small-scale conflict is likely to be exacerbated with increases in rainfall variability if the mean climate remains largely unchanged; preferentially higher rates of rebel conflict will be exhibited in anomalously dry conditions, while higher rates of communal conflict are expected in increasingly anomalous wet conditions.

A Combined Satellite Infrared and Passive Microwave Technique for Estimation of Small-Scale Rainfall

Abstract There are numerous applications in climatology and hydrology where accurate information at scales smaller than the existing monthly/2.5° products would be invaluable. Here, a new microwave/infrared rainfall algorithm is introduced that combines satellite passive microwave (PMW) and infrared (IR) data to account for limitations in both data types. Rainfall estimates are produced at the high spatial resolution and temporal frequency of the IR data using rainfall information from the PMW data. An IRTb–rain rate relationship, variable in space and time, is derived from coincident observations of IRTb and PMW rain rate (accumulated over a calibration domain) using the probability matching method. The IRTb–rain rate relationship is then applied to IR imagery at full temporal resolution. MIRA estimates of rainfall are evaluated over a range of spatial and temporal scales. Over the global Tropics and subtropics, optimum IR thresholds and IRTb–rain rate relationships are highly variable, reflecting the co...

Migration and climate change: towards an integrated assessment of sensitivity

This paper sets out a new approach to understanding the relationship between migration and climate change. Based on the understanding that migration is a significant, growing, but also complex phenomenon, this approach seeks to address the sensitivity of existing migration drivers in specific contexts to climate change. In contrast to existing approaches which have sought to generate global-level estimates of the numbers of ‘climate migrants’, this integrated assessment approach seeks instead to understand how and why existing flows from and to specific locations may change in the future, and provide a practical tool for climate adaptation planning. Examples of the application of this approach are provided for Ghana and Bangladesh.

Algorithms for the Retrieval of Rainfall from Passive Microwave Measurements.

The retrieval of rainfall intensity from radiances measured by spaceborne microwave radiometers can be understood in terms of well established physics. At frequencies below about 40 GHz over an ocean background the relationship between the rainfall and the observations is particularly well understood. In this part of the spectrum, the radiances are principally determined by the liquid hydrometeors with only a modest amount of ambiguity. In very intense convection, ice aloft may increase this ambiguity somewhat. At high frequencies, such as the 85.5 GHz channel of the SSM/I, scattering by the frozen hydrometeors becomes more significant and quantitative rainfall retrieval becomes more problematic. In spite of the ambiguities, the use of the higher frequencies is desirable on a number of counts including: applicability over land, spatial resolution and dynamic range. A total of 16 algorithms were submitted for the PIP‐1. These include algorithms that are based on high frequency (scattering) measurements and low frequency (emission) measurements with a few combinations and variations on these themes. The calibration of the algorithms varies from mostly empirical to essentially first principles with most falling somewhere in‐between. All of the algorithms retrieved rainfall and one also retrieved a profile of the liquid and frozen hydrometeors.

Changes in cloud cover associated with Forbush decreases of galactic cosmic rays

The results of a study to quantify the relationship between cloud cover and short-term Forbush decreases (FD) of galactic cosmic ray flux are presented. Using an extensive record of global satellite-derived cloud products from the International Satellite Cloud Climatology Project (ISCCP) D1 data series, epoch superposition analysis of a sample of FD events is conducted. This analysis is conducted at a range of spatial scales from global, through 5° geomagnetic latitude bands to a global grid with 2.5° resolution. Resulting cloud anomalies are tested for significance using a randomized Monte Carlo experiment. The results indicate a small but significant (at 0.001 probability level) decline in the global proportion of cloud cover (of up to 1.4%) immediately prior to and following FD events. Analysis of data averaged over geomagnetic latitude (φ) bands reveals that significant cloud anomalies are concentrated in the high latitudes. A substantial (small) decline in cloud cover occurs at Southern (Northern) Hemisphere polar latitudes and is accompanied by a small but significant increase near φ = 30°N. The high-latitude anomalies occur largely in the high-level cloud and are particularly pronounced (up to −30%) in the uppermost cloud (occurring at 10–180 mbar) over Antarctica. In contrast, analysis using a sample of FD events associated with solar proton events shows no statistically significant cloud anomalies. A discussion of possible explanations of the results is provided.

The Lancet Countdown on health and climate change: from 25 years of inaction to a global transformation for public health

The Lancet Countdown tracks progress on health and climate change and provides an independent assessment of the health effects of climate change, the implementation of the Paris Agreement, 1 and th ...

The first WetNet precipitation intercomparison project (PIP‐1): interpretation of results

The first WetNet Precipitation Intercomparison Project (PIP‐1) was designed as part of the activity of WetNets Precipitation Working Group, and intended to advance the science of global rainfall monitoring primarily through evaluations of existing passive microwave algorithms, both in relation to each other and also against conventional (rain gauge) data sets. In PIP‐1, intercomparisons of global rainfall estimates for August, September, October and November 1987 have been undertaken for 15 algorithms based on passive microwave DMSP‐SSM/I image data, one based on passive microwave NOAA‐MSU vertical profile data, one infrared image‐based algorithm, one combined passive‐based microwave/infrared imager algorithm, and one numerical weather prediction model, plus rainfall observations from continental rain gauges and from Pacific Atoll rain gauges. This paper begins by summarising the objectives of PIP‐1, the problems facing it, and its resulting intercomparison strategy. It then describes, exemplifies, and discusses results obtained by both qualitative and quantitative means for global, continental, and oceanic regions, before setting out some conclusions and recommendations for further studies. No single method of global rainfall estimation was found to be always better than all others, but several methods were each generally better over some major regions of the world. In view of the relatively short history of development of rainfall algorithms based on passive microwave imagery, and the relatively infrequent data presently available to support such types of approach, some passive microwave image‐based algorithms are already remarkably successful for estimating monthly global rainfall, and will benefit from on‐going developments in both related science and technology. Further global intercomparison projects should be designed to build on the many lessons learned by participants in PIP‐1. At the same time, more effort must be directed towards the acquisition of independent, in situ data sets for better calibration and validation of the satellite‐based results.

On the relationship of cosmic ray flux and precipitation

This paper evaluates whether there is empirical evidence to support the hypothesis that solar variability is linked to the Earths climate through the modulation of atmospheric precipitation processes. Using global data from 1979–1999, we find evidence of a statistically strong relationship between cosmic ray flux (CRF), precipitation (P) and precipitation efficiency (PE) over ocean surfaces at mid to high latitudes. Both P and PE are shown to vary by 7–9% during the solar cycle of the 1980s over the latitude band 45–90°S. Alternative explanations of the variation in these atmospheric parameters by changes in tropospheric aerosol content and ENSO show poorer statistical relationships with P and PE. Variations in P and PE potentially caused by changes in CRF have implications for the understanding of cloud and water vapour feedbacks.