Statistics for Spatial Data.

The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset builds on previous approaches to ‘smart’ interpolation techniques and high resolution, long period of record precipitation estimates based on infrared Cold Cloud Duration (CCD) observations. The algorithm i) is built around a 0.05° climatology that incorporates satellite information to represent sparsely gauged locations, ii) incorporates daily, pentadal, and monthly 1981-present 0.05° CCD-based precipitation estimates, iii) blends station data to produce a preliminary information product with a latency of about 2 days and a final product with an average latency of about 3 weeks, and iv) uses a novel blending procedure incorporating the spatial correlation structure of CCD-estimates to assign interpolation weights. We present the CHIRPS algorithm, global and regional validation results, and show how CHIRPS can be used to quantify the hydrologic impacts of decreasing precipitation and rising air temperatures in the Greater Horn of Africa. Using the Variable Infiltration Capacity model, we show that CHIRPS can support effective hydrologic forecasts and trend analyses in southeastern Ethiopia.

/pdf/the-climate-hazards-infrared-precipitation-with-stations-a-2fzhj8nya2.pdf

The climate hazards infrared precipitation with stations--a new environmental record for monitoring extremes.

We present a European land-only daily high-resolution gridded data set for precipitation and minimum, maximum, and mean surface temperature for the period 1950-2006. This data set improves on previous products in its spatial resolution and extent, time period, number of contributing stations, and attention to finding the most appropriate method for spatial interpolation of daily climate observations. The gridded data are delivered on four spatial resolutions to match the grids used in previous products as well as many of the rotated pole Regional Climate Models (RCMs) currently in use. Each data set has been designed to provide the best estimate of grid box averages rather than point values to enable direct comparison with RCMs. We employ a three-step process of interpolation, by first interpolating the monthly precipitation totals and monthly mean temperature using three-dimensional thin-plate splines, then interpolating the daily anomalies using indicator and universal kriging for precipitation and kriging with an external drift for temperature, then combining the monthly and daily estimates. Interpolation uncertainty is quantified by the provision of daily standard errors for every grid square. The daily uncertainty averaged across the entire region is shown to be largely dependent on the season and number of contributing observations. We examine the effect that interpolation has on the magnitude of the extremes in the observations by calculating areal reduction factors for daily maximum temperature and precipitation events with return periods up to 10 years. Copyright 2008 by the American Geophysical Union.

/pdf/a-european-daily-high-resolution-gridded-data-set-of-surface-4p1onqfxwe.pdf

A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006

An extensive evaluation of 10 different satellite rainfall products was performed using station network over a complex topography, where elevation varies from below sea level to 4620 m. Evaluation was for two groups of products. The first group had low spatial (2.5°) and temporal (monthly) resolution and included the Global Precipitation Climatology Project (GPCP), the National Oceanographic and Atmospheric Administration Climate Prediction Center (NOAA-CPC) merged analysis (CMAP), and the Tropical Rainfall Measuring Mission (TRMM-3B43). The second group comprised products with relatively high spatial (0.1° to 1°) and temporal (3-hourly to 10-daily) resolution. These included the NOAA-CPC African rainfall estimation algorithm, GPCP one-degree-daily (1DD), TRMM-3B42, Tropical Applications of Meteorology using SATellite and other data (TAMSAT) estimates, and the CPC morphing technique (CMORPH). These products were aggregated to a 10-day total and remapped to spatial resolutions of 1°, 0.5° and 0.25°. TRMM-3B43 and CMAP from the first group and CMORPH, TAMSAT and TRMM-3B42 from the second group performed reasonably well.

https://www.tandfonline.com/doi/pdf/10.1080/01431160600954688

Validation of satellite rainfall products over East Africa's complex topography

The West African Sahel is well known for the severe droughts that ravaged the region in the 1970s and 1980s. Meteorological research on the region has flourished during the last decade as a result of several major field experiments. This paper provides an overview of the results that have ensued. A major focus has been on the West African monsoon, a phenomenon that links all of West Africa. The characteristics and revised picture of the West African monsoon are emphasized. Other topics include the interannual variability of rainfall, the atmospheric circulation systems that govern interannual variability, characteristics of precipitation and convection, wave activity, large-scale factors in variability (including sea-surface temperatures), and land-atmosphere relationships. New paradigms for the monsoon and associated ITCZ and for interannual variability have emerged. These emphasize features in the upper atmosphere, as well as the Saharan Heat Low. Feedback mechanisms have also been emphasized, especially the coupling of convection with atmospheric dynamics and with land surface characteristics. New results also include the contrast between the premonsoon and peak monsoon seasons, two preferred modes of interannual variability (a latitudinal displacement of the tropical rainbelt versus changes in its intensity), and the critical importance of the Tropical Easterly Jet.

/pdf/the-west-african-sahel-a-review-of-recent-studies-on-the-ylpi96xame.pdf

The West African Sahel: A Review of Recent Studies on the Rainfall Regime and Its Interannual Variability

Drought is one of the leading impediments to development in Africa. Much of the continent is dependent on rain-fed agriculture, which makes it particularly susceptible to climate variability. Monitoring drought and providing timely seasonal forecasts are essential for integrated drought risk reduction. Current approaches in developing regions have generally been limited, however, in part because of unreliable monitoring networks. Operational seasonal climate forecasts are also deficient and often reliant on statistical regressions, which are unable to provide detailed information relevant for drought assessment. However, the wealth of data from satellites and recent advancements in large-scale hydrological modeling and seasonal climate model predictions have enabled the development of state-of-the-art monitoring and prediction systems that can help address many of the problems inherent to developing regions. An experimental drought monitoring and forecast system for sub-Saharan Africa is described that is...

A Drought Monitoring and Forecasting System for Sub-Sahara African Water Resources and Food Security

This study investigates the accuracy of various precipitation products for the Sahel. A first set of products is made of three ground-based precipitation estimates elaborated regionally from the gauge data collected by Centre Regional Agrometeorologie–Hydrologie–Meteorologie (AGRHYMET). The second set is made of four global products elaborated by various international data centers. The comparison between these two sets covers the period of 1986–2000. The evaluation of the entire operational network of the Sahelian countries indicates that on average the monthly estimation error for the July–September period is around 12% at a spatial scale of 2.5° × 2.5°. The estimation error increases from south to north and remains below 10% for the area south of 15°N and west of 11°E (representing 42% of the region studied). In the southern Sahel (south of 15°N), the rain gauge density needs to be at least 10 gauges per 2.5° × 2.5° grid cell for a monthly error of less than 10%. In the northern Sahel, this den...

https://hal-insu.archives-ouvertes.fr/insu-00382037/document

Rainfall Estimation in the Sahel. Part II: Evaluation of Rain Gauge Networks in the CILSS Countries and Objective Intercomparison of Rainfall Products

Rainfall estimation in semiarid regions remains a challenging issue because it displays great spatial and temporal variability and networks available for monitoring are often of low density. This is especially the case in the Sahel, a region of 3 million km2 where the life of populations is still heavily dependent on rain for agriculture. Whatever the data and sensors available for rainfall estimation—including satellite IR and microwave data and possibly weather radar systems—it is necessary to define objective error functions to be used in comparing various rainfall products. This first of two papers presents a theoretical framework for the development of such an error function and the optimization of its parameters for the Sahel. A range of time scales—from rain event to annual—are considered, using two datasets covering two different spatial scales. The mesoscale [Estimation des Pluies par Satellite (EPSAT)-Niger (E-N)] is documented over a period of 13 yr (1990–2002) on an area of 16 000 km2 covered by 30 recording rain gauges; the regional scale is documented by the Centre Regional Agrometeorologie–Hydrologie–Meteorologie (AGRHYMET) (CRA) dataset, with an annual average of between 600 and 650 rain gauges available over a period of 8 yr. The data analysis showed that the spatial structure of the Sahelian rain fields is markedly anisotropic, nonstationary, and dominated by the nesting of two elementary structures. A cross-validation procedure on point rainfall values leads to the identification of an optimal interpolation algorithm. Using the error variances computed from this algorithm on 1° × 1° and 2.5° × 2.5° cells, an error function is derived, allowing the calculation of standard errors of estimation for the region. Typical standard errors for monthly rainfall estimation are 11% (10%) for a 10-station network on a 2.5° × 2.5° (1° × 1°) grid, and 40% (30%) for a single station on a 2.5° × 2.5° (1° × 1°) grid. In a companion paper, this error function is used to investigate the differences between satellite rainfall products and how they compare with ground-based estimates.

https://hal-insu.archives-ouvertes.fr/insu-00382039/document

Rainfall Estimation in the Sahel. Part I: Error Function

Areal rainfall estimation from ground sensors is essential as a direct input to various hydrometeorological models or as a validation of remote sensing estimates. More critical than the estimation itself is the assessment of the uncertainty associated with it. In tropical regions knowledge on this topic is especially scarce due to a lack of appropriate data. It is proposed here to assess standard estimation errors of the areal rainfall in the Sahel, a tropical region of notoriously unreliable rainfall, and to validate those errors using the data of the EPSAT–Niger experiment. A geostatistical framework is considered to compute theoretical variances of estimation errors for the event-cumulative rainfall, and rain gauge networks of decreasing density are used for the validation. As a result of this procedure, charts giving the standard estimation error as a function of the network density, the area, and the rainfall depth are proposed for the Sahelian region. An extension is proposed for larger tim...

Rainfall Estimation in the Sahel: What Is the Ground Truth?

The occurrence of rainfall in the semiarid regions is notoriously unreliable and characterized by great spatial variability over a large spectrum of timescales. Based on analytical considerations, an integrated approach is presented here in order to describe the spatial structure of rain fields for timescales used in climatological studies, that is from the daily to the seasonal scales and beyond to the interannual scale. At the scale of the rain event, two factors determine the spatial structure of rain fields. One is the spatial variability of the conditional rainfall H* (H > 0), represented by its variogram γ*e. The other is the intermittency, its spatial structure being described by the indicator variogram γ1. It is shown that the spatial structure of rain fields for time steps larger than the event may be analytically derived from γ*e and γ1, taking into account the anisotropy and nonstationarity that may affect either of these two functions, which are thus two timescale invariants of the ra...

https://journals.ametsoc.org/doi/pdf/10.1175/1525-7541%282003%29004%3C0996%3AIITSSO%3E2.0.CO%3B2

Abou Amani

Papers

A Drought Monitoring and Forecasting System for Sub-Sahara African Water Resources and Food Security

Rainfall Estimation in the Sahel. Part II: Evaluation of Rain Gauge Networks in the CILSS Countries and Objective Intercomparison of Rainfall Products

Rainfall Estimation in the Sahel. Part I: Error Function

Rainfall Estimation in the Sahel: What Is the Ground Truth?

Invariance in the Spatial Structure of Sahelian Rain Fields at Climatological Scales