,
Graciela R. Sobierajski [aut] ,
Leticia L. Martins [aut] ,
Adam H. Sparks [aut] | Title: | Improves the Interpretation of the Standardized Precipitation Index Under Changing Climate Conditions |
|---|---|
| Description: | Improves the interpretation of the Standardized Precipitation Index under changing climate conditions. The package uses the nonstationary approach proposed in Blain et al. (2022) <doi:10.1002/joc.7550> to detect trends in rainfall quantities and to quantify the effect of such trends on the probability of a drought event occurring. |
| Authors: | Gabriel Constantino Blain [aut, cre]
,
Graciela R. Sobierajski [aut] ,
Leticia L. Martins [aut] ,
Adam H. Sparks [aut] |
| Maintainer: | Gabriel Constantino Blain <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.1.0.9000 |
| Built: | 2025-03-08 05:18:58 UTC |
| Source: | https://github.com/gabrielblain/spichanges |
Daily rainfall amounts recorded in millimetre in Campinas state of Sao Paulo, Brazil.
CampinasRainCampinasRain
CampinasRainA dataframe with 2 columns and 16071 rows:
Date
Daily rainfall amounts recorded in millimetre in Campinas state of Sao Paulo, Brazil
...
This dataset provides coordinates for Brazil at a spatial resolution of 0.5 x 0.5 degrees.
lonlatlonlat
lonlatA matrix with 2841 rows and 2 columns:
Longitude in decimal degrees
Latitude in decimal degrees
...
Data generated using information from the Instituto Brasileiro de Geografia e Estatística (IBGE). For more information, visit: https://www.ibge.gov.br/
This dataset provides the changes (in percentage) in Moderate to Extreme, Severe to Extreme, and Extreme Drought events across Brazil
for the four seasons (Summer, Autumn, Winter, and Spring) over the period 1980–2024.
The data were generated using the SPIChanges() function applied to rainfall data from NOAA PSL.
MapMap
MapA matrix with 2841 rows and 18 columns:
Longitude in decimal degrees
Latitude in decimal degrees
Percentage change in moderate drought events in Summer
Percentage change in severe drought events in Summer
Percentage change in extreme drought events in Summer
The selected gamma-based model in Summer
Percentage change in moderate drought events in Autumn
Percentage change in severe drought events in Autumn
Percentage change in extreme drought events in Autumn
The selected gamma-based model in Autumn
Percentage change in moderate drought events in Winter
Percentage change in severe drought events in Winter
Percentage change in extreme drought events in Winter
The selected gamma-based model in Winter
Percentage change in moderate drought events in Spring
Percentage change in severe drought events in Spring
Percentage change in extreme drought events in Spring
The selected gamma-based model in Spring
...
Generated using the SPIChanges() function applied to rainfall data obtained from NOAA PSL (https://psl.noaa.gov/).
Rainfall amounts aggregated using TSaggreg(). Campinas state of Sao Paulo, Brazil.
rainTS4rainTS4
rainTS4A matrix with 4 columns and 576 rows:
Year
Month
Four quasi-weekly periods in each month
Rainfall amounts aggregated at TS equal to four
...
Detect trends and quantify their effect on the probability of SPI values occurring
SPIChanges(rain.at.TS, only.linear = "Yes")SPIChanges(rain.at.TS, only.linear = "Yes")
rain.at.TS |
A 4-column matrix generated with
|
only.linear |
A character string value ( |
A list object with:
The Rainfall amounts, SPI, cumulative probability of the SPI values under the stationary approach, cumulative probability of the SPI values under the non-stationary approach, and the changes in the frequency of below zero SPI values caused by the changes in rainfall patterns.
The generalized additive model that best fits the rainfall series
changes in the frequency of zero precipitation, moderate to extreme, severe to extreme and extreme drought events,as categorized by the SPI classification system, caused by the changes in rainfall patterns. Changes in the precipitation amounts associated describing normal conditions is also shown.
Year to year changes in the expected frequency of moderate to extreme, severe to extreme and extreme drought events.
The Rainfall amounts, SPI, cumulative probability of the SPI values under the stationary approach, cumulative probability of the SPI values under the non-stationary approach, and the changes in the frequency of below zero SPI values caused by the changes in rainfall patterns.
The generalized additive model that best fits the rainfall series
changes in the frequency of zero precipitation, moderate, severe and extreme drought events, as defined by the SPI classification system, caused by the changes in rainfall patterns. Changes in the precipitation amounts associated describing normal conditions is also shown.
Year to year changes in the expected frequency of moderate, severe and extreme drought events.
rainTS4 <- rainTS4 Changes_SPI <- SPIChanges(rain.at.TS=rainTS4, only.linear = "yes")rainTS4 <- rainTS4 Changes_SPI <- SPIChanges(rain.at.TS=rainTS4, only.linear = "yes")
Aggregates daily rainfall totals at quasi-week time scales
TSaggreg(daily.rain, start.date, TS = 4L)TSaggreg(daily.rain, start.date, TS = 4L)
daily.rain |
Vector, 1-column matrix or data frame with daily rainfall totals. |
start.date |
Date at which the aggregation should start. Preferred formats are “YYYY-MM-DD”, “YYYY/MM/DD” but most any valid date format should work. |
TS |
Time scale on the quasiWeek basis (integer values between 1 and 96). Default is 4, which corresponds to the monthly time scale. |
A matrix with rainfall amounts aggregated at the time scale selected by the user
daily.rain <- CampinasRain[,2] rainTS4 <- TSaggreg(daily.rain=daily.rain,start.date="1980-01-01",TS=4)daily.rain <- CampinasRain[,2] rainTS4 <- TSaggreg(daily.rain=daily.rain,start.date="1980-01-01",TS=4)