Reconstructing paleosalinity from δ18O: coupled model simulations of the Last Glacial Maximum, Last Interglacial and Late Holocene

Reconstructions of salinity are used to diagnose changes in the hydrological cycle and ocean circulation. A widely used method of determining past salinity uses oxygen isotope (δOw) residuals after the extraction of the global ice volume and temperature components. This method relies on a constant relationship between δOw and salinity throughout time. Here we use the isotope-enabled fully coupled General Circulation Model (GCM) HadCM3 to test the application of spatially and time-independent relationships in the reconstruction of past ocean salinity. Simulations of the Late Holocene (LH), Last Glacial Maximum (LGM), and Last Interglacial (LIG) climates are performed and benchmarked against existing compilations of stable oxygen isotopes in carbonates (δOc), which primarily reflect δOw and temperature. We find that HadCM3 produces an accurate representation of the surface ocean δOc distribution for the LH and LGM. Our simulations show considerable variability in spatial and temporal δOw-salinity relationships. Spatial gradients are generally shallower but within ∼50% of the actual simulated LH to LGM and LH to LIG temporal gradients and temporal gradients calculated from multi-decadal variability are generally shallower than both spatial and actual simulated gradients. The largest sources of uncertainty in salinity reconstructions are found to be caused by changes in regional freshwater budgets, ocean circulation, and sea ice regimes. These can cause errors in salinity estimates exceeding 4 psu. Our results suggest that paleosalinity reconstructions in the South Atlantic, Indian and Tropical Pacific Oceans should be most robust, since these regions exhibit relatively constant δOw-salinity relationships across spatial and temporal scales. Largest uncertainties will affect North Atlantic and high latitude paleosalinity reconstructions. Finally, the results show that it is difficult to generate reliable salinity estimates for regions of dynamic oceanography, such as the North Atlantic, without additional constraints.

Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

High-precision measurements of the co-polar correlation coefficient: non-Gaussian errors and retrieval of the dispersion parameter µ in rainfall

The co-polar correlation coefficient (ρhv) has many applications, including hydrometeor classification, ground clutter and melting layer identification, interpretation of ice microphysics and the retrieval of rain drop size distributions (DSDs). However, we currently lack the quantitative error estimates that are necessary if these applications are to be fully exploited. Previous error estimates of ρhv rely on knowledge of the unknown "true" ρhv and implicitly assume a Gaussian probability distribution function of ρhv samples. We show that frequency distributions of ρhv estimates are in fact highly negatively skewed. A new variable: L = -log10(1 - ρhv) is defined, which does have Gaussian error statistics, and a standard deviation depending only on the number of independent radar pulses. This is verified using observations of spherical drizzle drops, allowing, for the first time, the construction of rigorous confidence intervals in estimates of ρhv. In addition, we demonstrate how the imperfect co-location of the horizontal and vertical polarisation sample volumes may be accounted for. The possibility of using L to estimate the dispersion parameter (µ) in the gamma drop size distribution is investigated. We find that including drop oscillations is essential for this application, otherwise there could be biases in retrieved µ of up to ~8. Preliminary results in rainfall are presented. In a convective rain case study, our estimates show µ to be substantially larger than 0 (an exponential DSD). In this particular rain event, rain rate would be overestimated by up to 50% if a simple exponential DSD is assumed.

The use of remotely sensed rainfall for managing drought risk: a case study of weather index insurance in Zambia

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere.

Mechanisms Associated with Large Daily Rainfall Events in Northeast Brazil

The mechanisms resulting in large daily rainfall events in Northeast Brazil are analyzed using data filtering to exclude periods longer than 30 days. Composites of circulation fields that include all independent events do not reveal any obvious forcing mechanisms as multiple patterns contribute to Northeast Brazil precipitation variability. To isolate coherent patterns, subsets of events are selected based on anomalies that precede the Northeast Brazil precipitation events at different locations. The results indicate that at 10 degrees S, 40 degrees W, the area of lowest annual rainfall in Brazil, precipitation occurs mainly in association with trailing midlatitude synoptic wave trains originating in either hemisphere. Closer to the equator at 5 degrees S, 37.5 degrees W, an additional convection precursor is found to the west, with a spatial structure consistent with that of a Kelvin wave. Although these two sites are located within only several hundred kilometers of each other and the midlatitude patterns that induce precipitation appear to be quite similar, the dates on which large precipitation anomalies occur at each location are almost entirely independent, pointing to separate forcing mechanisms.

Can the Deforestation Breeze Change the Rainfall in Amazonia? A Case Study for the BR-163 Highway Region

The authors simulated the effects of Amazonian mesoscale deforestation in the boundary layer and in rainfall with the Brazilian Regional Atmospheric Modeling System (BRAMS) model. They found that both the area and shape (with respect to wind incidence) of deforestation and the soil moisture status contributed to the state of the atmosphere during the time scale of several weeks, with distinguishable patterns of temperature, humidity, and rainfall. Deforestation resulted in the development of a three-dimensional thermal cell, the so-called deforestation breeze, slightly shifted downwind to large-scale circulation. The boundary layer was warmer and drier above 1000-m height and was slightly wetter up to 2000-m height. Soil wetness affected the circulation energetics proportionally to the soil dryness (for soil wetness below similar to 0.6). The shape of the deforestation controlled the impact on rainfall. The horizontal strips lined up with the prevailing wind showed a dominant increase in rainfall, significant up to about 60 000 km(2). On the other hand, in the patches aligned in the opposite direction (north-south), there was both increase and decrease in precipitation in two distinct regions, as a result of clearly separated upward and downward branches, which caused the precipitation to increase for patches up to 15 000 km(2). The authors` estimates for the size of deforestation impacting the rainfall contributed to fill up the low spatial resolution in other previous studies.

Precipitation diurnal cycle and summer climatology assessment over South America: An evaluation of Regional Climate Model version 3 simulations

Regional Climate Model version 3 (RegCM3) simulations of 17 summers (1988-2004) over part of South America south of 5 degrees S were evaluated to identify model systematic errors. Model results were compared to different rainfall data sets (Climate Research Unit (CRU), Climate Prediction Center (CPC), Global Precipitation Climatology Project (GPCP), and National Centers for Environmental Prediction (NCEP) reanalysis), including the five summers mean (1998-2002) precipitation diurnal cycle observed by the Tropical Rainfall Measuring Mission (TRMM)-Precipitation Radar (PR). In spite of regional differences, the RegCM3 simulates the main observed aspects of summer climatology associated with the precipitation (northwest-southeast band of South Atlantic Convergence Zone (SACZ)) and air temperature (warmer air in the central part of the continent and colder in eastern Brazil and the Andes Mountains). At a regional scale, the main RegCM3 failures are the underestimation of the precipitation in the northern branch of the SACZ and some unrealistic intense precipitation around the Andes Mountains. However, the RegCM3 seasonal precipitation is closer to the fine-scale analyses (CPC, CRU, and TRMM-PR) than is the NCEP reanalysis, which presents an incorrect north-south orientation of SACZ and an overestimation of its intensity. The precipitation diurnal cycle observed by TRMM-PR shows pronounced contrasts between Tropics and Extratropics and land and ocean, where most of these features are simulated by RegCM3. The major similarities between the simulation and observation, especially the diurnal cycle phase, are found over the continental tropical and subtropical SACZ regions, which present afternoon maximum (1500-1800 UTC) and morning minimum (0900-1200 UTC). More specifically, over the core of SACZ, the phase and amplitude of the simulated precipitation diurnal cycle are very close to the TRMM-PR observations. Although there are amplitude differences, the RegCM3 simulates the observed nighttime rainfall in the eastern Andes Mountains, over the Atlantic Ocean, and also over northern Argentina. The main simulation deficiencies are found in the Atlantic Ocean and near the Andes Mountains. Over the Atlantic Ocean the convective scheme is not triggered; thus the rainfall arises from the grid-scale scheme and therefore differs from the TRMM-PR. Near the Andes, intense (nighttime and daytime) simulated precipitation could be a response of an incorrect circulation and topographic uplift. Finally, it is important to note that unlike most reported bias of global models, RegCM3 does not trigger the moist convection just after sunrise over the southern part of the Amazon.

Precipitation variability in Sao Paulo State, Brazil

The State of Sao Paulo is the richest in Brazil, responsible for over 30% of the Brazilian gross rate. It has a population of around 30 million and its economy is based on agriculture and industrial products. Any change in climate can have a profound influence on the socio-economics of the State. In order to determine changes in total and extreme rainfall over Sao Paulo State, climate change indices derived from daily precipitation data were calculated using specially designed software. Maps of trends for a subset of 59 rain gauge stations were analysed for the period 1950-1999 and also for a subset of this period, 1990-1999, representing more recent climate. A non-parametric Mann-Kendall test was applied to the time series. Maps of trends for six annual precipitation indices (annual total precipitation (PRCPTOT), very heavy precipitation days (R20mm), events greater than the 95th percentile (R95p), maximum five days precipitation total (RX5day), the length of the largest wet spell (CWD) and the length of the largest dry spell (CDD)) were analysed for the entire period. These exhibited statistically significant trends associated with a wetter climate. A significant increase in PRCPTOT, associated with very heavy precipitation days, were observed at more than 45% of the rain gauge stations. The Mann-Kendall test identified that the positive trend in PRCPTOT is possibly related to the increase in the R95p and R20mm indices. Therefore, the results suggest that there has been a change in precipitation intensity. In contrast, the indices for the more recent shorter time series are significantly different to the longer term indices. The results indicate that intense precipitation is becoming concentrated in a few days and spread over the period when the CDD and R20mm indices show positive trends, while negative ones are seen in the RX5day index. The trends found could be related to many anthropogenic aspects such as biomass burning aerosols and land use.

Are Reanalysis Data Useful for Calculating Climate Indices over South America?

Precipitation and temperature climate indices are calculated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and validated against observational data from some stations over Brazil and other data sources. The spatial patterns of the climate indices trends are analyzed for the period 1961-1990 over South America. In addition, the correlation and linear regression coefficients for some specific stations were also obtained in order to compare with the reanalysis data. In general, the results suggest that NCEP/NCAR reanalysis can provide useful information about minimum temperature and consecutive dry days indices at individual grid cells in Brazil. However, some regional differences in the climate indices trends are observed when different data sets are compared. For instance, the NCEP/NCAR reanalysis shows a reversal signal for all rainfall annual indices and the cold night index over Argentina. Despite these differences, maps of the trends for most of the annual climate indices obtained from the NCEP/NCAR reanalysis and BRANT analysis are generally in good agreement with other available data sources and previous findings in the literature for large areas of southern South America. The pattern of trends for the precipitation annual indices over the 30 years analyzed indicates a change to wetter conditions over southern and southeastern parts of Brazil, Paraguay, Uruguay, central and northern Argentina, and parts of Chile and a decrease over southwestern South America. All over South America, the climate indices related to the minimum temperature (warm or cold nights) have clearly shown a warming tendency; however, no consistent changes in maximum temperature extremes (warm and cold days) have been observed. Therefore, one must be careful before suggesting an), trends for warm or cold days.

Frequency of extreme rainfall events in Southern Brazil modulated by interannual and interdecadal variability

The frequency of extreme rainfall events in Southern Brazil is impacted by Ell Nino - Southern Oscillation (ENSO) episodes, especially in austral spring. There are two areas in which this impact is more significant: one is on the coast, where extreme events are more frequent during El Nino (EN) and the other one extends inland, where extreme events increase during EN and decrease during La Nina (LN). Atmospheric circulation patterns associated with severe rainfall in those areas are similar (opposite) to anomalous patterns characteristic of EN (LN) episodes, indicating why increase (decrease) of extreme events in EN (LN) episodes is favoured. The most recurrent precipitation patterns during extreme rainfall events in each of these areas are disclosed by Principal Component Analysis (PCA) and evidence the separation between extreme events in these areas: a severe precipitation event generally does not occur simultaneously in the coast and inland, although they may Occur inland and in the coastal region in sequence. Although EN predominantly enhances extreme rainfall, there are EN years in which fewer severe events occur than the average of neutral years, and also the enhancement of extreme rainfall is not uniform for different EN episodes, because the interdecadal non-ENSO variability also modulates significantly the frequency of extreme events in Southern Brazil. The inland region, which is more affected, shows increase (decrease) of extreme rainfall in association with the negative (positive) phase of the Atlantic Multidecadal Variability, with the negative (positive) phase of the Pacific Multidecadal Variability and with the positive (negative) phase of the Pacific Interdecadal Variability. Copyright (C) 2008 Royal Meteorological Society

On the development of summer thunderstorms in the city of Sao Paulo: Mean meteorological characteristics and pollution effect

This study investigates how the summer thunderstorms developed over the city of Sao Paulo and if the pollution might affect its development or characteristics during the austral summer (December-January-February-March, DJFM months). A total of 605 days from December 1999 to March 2004 was separated as 241 thunderstorms days (TDs) and 364 non-thunderstorm days (NTDs). The analyses are performed by using hourly measurements of air temperature (T), web-bulb temperature (Tw), surface atmospheric pressure (P), wind velocity and direction, rainfall and thunder and lightning observations collected at the Meteorological Station of the University of Sao Paulo in conjunction with aerosol measurements obtained by AERONET (Aerosol Robotic Network), and the NCEP-DOE (National Centers for Environmental Prediction Department of Energy) reanalysis and radiosondes. The wind diurnal cycle shows that for TDs the morning flow is from the northwest rotating to the southeast after 16: 00 local time (LT) and it remains from the east until the night. For the NTDs, the wind is well characterized by the sea-breeze circulation that in the morning has the wind blowing from the northeast and in the afternoon from the southeast. The TDs show that the air temperature diurnal cycle presents higher amplitude and the maximum temperature of the day is 3.2 degrees C higher than in NTDs. Another important factor found is the difference between moisture that is higher during TDs. In terms of precipitation, the TDs represent 40% of total of days analyzed and those days are responsible for more than 60% of the total rain accumulation during the summer, for instance 50% of the TDs had more than 15.5mm day(-1) while the NTDs had 4 mm day(-1). Moreover, the rainfall distribution shows that TDs have higher rainfall rate intensities and an afternoon precipitation maximum; while in the NTDs there isn`t a defined precipitation diurnal cycle. The wind and temperature fields from NCEP reanalysis concur with the local weather station and radiosonde observations. The NCEP composites show that TDs are controlled by synoptic circulation characterized by a pre-frontal situation, with a baroclinic zone situated at southern part of Sao Paulo. In terms of pollution, this study employed the AERONET data to obtain the main aerosol characteristics in the atmospheric column for both TDs and NTDs. The particle size distribution and particle volume size distribution have similar concentrations for both TDs and NTDs and present a similar fine and coarse mode mean radius. In respect to the atmospheric loading, the aerosol optical depth (AOD) at different frequencies presented closed mean values for both TDs and NTDs that were statistically significant at 95% level. The spectral dependency of those values in conjunction with the Angstrom parameter reveal the higher concentration of the fine mode particles that are more likely to be hygroscopic and from urban areas. In summary, no significant aerosol effect could be found on the development of summer thunderstorms, suggesting the strong synoptic control by the baroclinic forcing for deep convective development. (C) 2010 Published by Elsevier B. V.

Satellite Rainfall Estimates Over South America - Possible Applicability to the Water Management of Large Watersheds1

This work analyzes high-resolution precipitation data from satellite-derived rainfall estimates over South America, especially over the Amazon Basin. The goal is to examine whether satellite-derived precipitation estimates can be used in hydrology and in the management of larger watersheds of South America. High spatial-temporal resolution precipitation estimates obtained with the CMORPH method serve this purpose while providing an additional hydrometeorological perspective on the convective regime over South America and its predictability. CMORPH rainfall estimates at 8-km spatial resolution for 2003 and 2004 were compared with available rain gauge measurements at daily, monthly, and yearly accumulation time scales. The results show the correlation between satellite-derived and gauge-measured precipitation increases with accumulation period from daily to monthly, especially during the rainy season. Time-longitude diagrams of CMORPH hourly rainfall show the genesis, strength, longevity, and phase speed of convective systems. Hourly rainfall analyses indicate that convection over the Amazon region is often more organized than previously thought, thus inferring that basin scale predictions of rainfall for hydrological and water management purposes have the potential to become more skillful. Flow estimates based on CMORPH and the rain gauge network are compared to long-term observed average flow. The results suggest this satellite-based rainfall estimation technique has considerable utility. Other statistics for monthly accumulations also suggest CMORPH can be an important source of rainfall information at smaller spatial scales where in situ observations are lacking.

Texture analysis based on maximum contrast walker

Recently, the deterministic tourist walk has emerged as a novel approach for texture analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional texture analysis methods in the classification of a set of Brodatz textures and their rotated versions, thus confirming the potential of the method as a feasible texture analysis methodology. (C) 2010 Elsevier B.V. All rights reserved.

Algorithms for Maximum Independent Set in Convex Bipartite Graphs

A bipartite graph G = (V, W, E) is convex if there exists an ordering of the vertices of W such that, for each v. V, the neighbors of v are consecutive in W. We describe both a sequential and a BSP/CGM algorithm to find a maximum independent set in a convex bipartite graph. The sequential algorithm improves over the running time of the previously known algorithm and the BSP/CGM algorithm is a parallel version of the sequential one. The complexity of the algorithms does not depend on |W|.

Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.