Predicted temperature and precipitation values were generated throughout the state of Massachusetts using a stochastic weather generator (SWG) model to develop various climate change scenarios (Steinschneider and Najibi, 2022a). This data release contains temperature and precipitation statistics (SWG_outputTable.csv) derived from the SWG model under the surface warming derived from the RCP 8.5 climate change emissions scenario at 30-year moving averages centered around 2030, 2050, 2070, 2090. During the climate modeling process, extreme precipitation values were also generated by scaling previously published intensity-duration-frequency (IDF) values from the NOAA Atlas 14 database (Perica and others, 2015) by a factor per degree expected warming produced from the SWG model generator (Najibi and others, 2022; Steinschneider and Najibi, 2022b, c). These newly generated IDF values (IDF_outputTable.csv) account for expected changes in extreme precipitation driven by variations in weather associated with climate change throughout the state of Massachusetts. The data presented here were developed in collaboration with the Massachusetts Executive Office of Energy and Environmental Affairs and housed on the Massachusetts climate change clearinghouse webpage (Massachusetts Executive Office of Energy and Environmental Affairs, 2022). References: Massachusetts Executive Office of Energy and Environmental Affairs, 2022, Resilient MA Maps and Data Center at URL https://resilientma-mapcenter-mass-eoeea.hub.arcgis.com/ Najibi, N., Mukhopadhyay, S., and Steinschneider, S., 2022, Precipitation scaling with temperature in the Northeast US: Variations by weather regime, season, and precipitation intensity: Geophysical Research Letters, v. 49, no. 8, 14 p., https://doi.org/10.1029/2021GL097100. Perica, S., Pavlovic, S., St. Laurent, M., Trypaluk, C., Unruh, D., Martin, D., and Wilhite, O., 2015, NOAA Atlas 14 Volume 10 Version 3, Precipitation-Frequency Atlas of the United States, Northeastern States (revised 2019): NOAA, National Weather Service, https://doi.org/10.25923/99jt-a543. Steinschneider, S., and Najibi, N., 2022a, A weather-regime based stochastic weather generator for climate scenario development across Massachusetts: Technical Documentation, Cornell University, https://eea-nescaum-dataservices-assets-prd.s3.amazonaws.com/cms/GUIDELINES/FinalTechnicalDocumentation_WGEN_20220405.pdf. Steinschneider, S., and Najibi, N., 2022b, Future projections of extreme precipitation across Massachusetts—a theory-based approach: Technical Documentation, Cornell University, https://eea-nescaum-dataservices-assets-prd.s3.amazonaws.com/cms/GUIDELINES/FinalTechnicalDocumentation_IDF_Curves_Dec2021.pdf. Steinschneider, S., and Najibi, N., 2022c, Observed and projected scaling of daily extreme precipitation with dew point temperature at annual and seasonal scales across the northeast United States: Journal of Hydrometeorology, v. 23, no. 3, p. 403-419, https://doi.org/10.1175/JHM-D-21-0183.1.

Led by the Massachusetts Executive Office of Energy and Environmental Affairs (EEA), in partnership with Cornell University, U.S. Geological Survey and Tufts University, the Massachusetts Climate and Hydrologic Risk Project (Phase 1) has developed new climate change projections for the Commonwealth. These new temperature and precipitation projections are downscaled for Massachusetts at the HUC8 watershed scale using Global Climate Models (GCMs) and a Stochastic Weather Generator (SWG) developed by Cornell University.

Stochastic weather generators provide a computationally efficient and complementary alternative to direct use of GCMs for investigating water system performance under climate stress. These models are configured based on existing meteorological records (i.e., historical weather) and are then used to generate large ensembles of simulated daily weather records that are similar to but not bound by variability in past observations. Once fit to historical data, model parameters can be systematically altered to produce new traces of weather that exhibit a wide range of change in their distributional characteristics, including the intensity and frequency of average and extreme precipitation, heatwaves, and cold spells.

The Phase 1 SWG was developed, calibrated, and validated across all HUC8 watersheds that intersect with the state of Massachusetts. A set of climate change scenarios for those watersheds were generated that only reflect mechanisms of thermodynamic climate change deemed to be most credible. These thermodynamic climate changes are based on the range of temperature projections produced by a set of downscaled GCMs for the region. The temperature and precipitation projections presented in this dashboard reflect a warming scenario linked to the Representation Concentration Pathway (RCP) 8.5, a comparatively high greenhouse gas emissions scenario.

The statistics presented in this series of map layers are expressed as either a percent change or absolute change (see list of layers with units and definitions below). These changes are referenced to baseline values that are calculated based on the median value across the 50 model ensemble members associated with the 0°C temperature change scenario derived from observational data (1950-2013) from Livneh et al. (2015). The temperature projections derived from the downscaled GCMs for the region, which are used to drive the SGW, are averaged across 30 years and centered on a target decade (i.e., 2030, 2050, 2070). Projections for 2090 are averaged across 20 years.Definitions of climate projection metrics (with units of change):Total Precipitation (% change): The average total precipitation within a calendar year. Maximum Precipitation (% change): The maximum daily precipitation in the entire record. Precipitation Depth – 90th Percentile Storm (% change): The 90th percentile of non-zero precipitation. Precipitation Depth –99th Percentile Storm (% change): The 99th percentile of non-zero precipitation. Consecutive Wet Days (# days): The average number of days that exist within a run of 2 or more wet days. Consecutive Dry Days (# days): The average number of days that exist within a model run of 2 or more dry days. Days above 1 inch (# days): The number of days with precipitation greater than 1 inch. Days above 2 inches (# days): The number of days with precipitation greater than 2 inches.Days above 4 inches (# days): The number of days with precipitation greater than 4 inches.Maximum Temperature (°F): The maximum daily average temperature value in the entire recordAverage Temperature (°F): Daily average temperature.Days below 0 °F (# days): The number of days with temperature below 0 °F.Days below 32 °F (# days): The number of days with temperature below 32 °F.Maximum Duration of Coldwaves (# days): Longest duration of coldwaves in the record, where coldwaves are defined as ten or more consecutive days below 20 °F.Average Duration of Coldwaves (# days): Average duration of coldwaves in the record, where coldwaves are defined as ten or more consecutive days below 20 °F.Number of Coldwave Events (# events): Number of instances with ten or more consecutive days with temperature below 20 °F.Number of Coldstress Events (# events): Number of instances when a 3-day moving average of temperature is less than 32 °F. Days above 100 °F (# days): The number of days with temperature above 100 °F.Days above 95 °F (# days): The number of days with temperature above 95 °F.Days above 90 °F (# days): The number of days with temperature above 90 °F.Maximum Duration of Heatwaves (# days): Longest duration of heatwaves in the record, where heatwaves are defined as three or more consecutive days over 90 °F.Average Duration of Heatwaves (# days): Average duration of heatwaves in the record, where heatwaves are defined as three or more consecutive days over 90 °F.Number of Heatwave Events (# events): Number of instances with three or more consecutive days with temperature over 90 °F.Number of Heatstress Events (# events): Number of instances when a 3-day moving average of temperature is above 86 °F.Cooling Degree Days (# degree-day): Cooling degree days assume that when the outside temperature is below 65°F, we don't need cooling (air-conditioning) to be comfortable. Cooling degree-days are the difference between the daily temperature mean and 65°F. For example, if the temperature mean is 85°F, we subtract 65 from the mean and the result is 20 cooling degree-days for that day. (Definition adapted from National Weather Service).Heating Degree Days (# degree-day): Heating degree-days assume that when the outside temperature is above 65°F, we don't need heating to be comfortable. Heating degree days are the difference between the daily temperature mean and 65°F. For example, if the mean temperature mean is 25°F, we subtract the mean from 65 and the result is 40 heating degree-days for that day. (Definition adapted from National Weather Service).Growing Degree Days (# degree-day): A growing degree day (GDD) is an index used to express crop maturity. The index is computed by subtracting a base temperature of 50°F from the average of the maximum and minimum temperatures for the day. Minimum temperatures less than 50°F are set to 50, and maximum temperatures greater than 86°F are set to 86. These substitutions indicate that no appreciable growth is detected with temperatures lower than 50° or greater than 86°. (Adapted from National Weather Service).Please see additional information related to this project and dataset in the Climate Change Projection Dashboard on the Resilient MA Maps and Data Center webpage.

The Boston Water and Sewer Commission (BWSC) maintains collection sites throughout the city. Those collection sites are equipped with solar powered rain gauges on top of public buildings which log measurements of precipitation and which report data every five minutes. Here you find the link to the Boston Water and Sewer Commission’s interface to the rainfall data, which is updated continually. You can search for rainfall data going as far back as 1999, depending on the year of installation for the various gauges.

The average rainfall chart shows the average amount of total rainfall, or amount of all liquid precipitation in millimetres (mm) such as rain, drizzle, freezing rain, and hail, observed at the location for each month of the specified year. Precipitation is measured using vertical depth of water (or water equivalent in the case of solid forms) which reaches the ground during a stated period.

Morocco MA: Average Precipitation in Depth data was reported at 346.000 mm/Year in 2014. This stayed constant from the previous number of 346.000 mm/Year for 2012. Morocco MA: Average Precipitation in Depth data is updated yearly, averaging 346.000 mm/Year from Dec 1962 (Median) to 2014, with 12 observations. The data reached an all-time high of 346.000 mm/Year in 2014 and a record low of 346.000 mm/Year in 2014. Morocco MA: Average Precipitation in Depth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Morocco – Table MA.World Bank.WDI: Land Use, Protected Areas and National Wealth. Average precipitation is the long-term average in depth (over space and time) of annual precipitation in the country. Precipitation is defined as any kind of water that falls from clouds as a liquid or a solid.; ; Food and Agriculture Organization, electronic files and web site.; ;

This excel contains data for Chapter 2 “Precipitation” of the 2017 State of Narragansett Bay & Its Watershed Technical Report (nbep.org). It includes the raw data behind Figure 1, “Annual precipitation at Providence, RI,” (page 64); Figure 2, “Annual precipitation at Worcester, MA,” (page 64); Figure 3, “Annual Palmer Drought Severity Index (PDSI) for Rhode Island,” (page 65); Figure 4, "Annual Palmer Drought Severity Index (PDSI) for Massachusetts," (page 65); Figure 5, "Climate model projection of winter total precipitation in RI or MA to 2100," (page 67); and Figure 6, "Climate model projection of winter annual snowfall in RI or MA to 2100," (page 67). For more information, please reference the Technical Report or contact info@nbep.org. Original figures are available at http://nbep.org/the-state-of-our-watershed/figures/.

Meteorological data daily averages and daily fluxes for stations located at Governor's Academy and MBL Marshview Farm, Newbury, MA. Data includes air temeprature, precipitation, relative humidity, solar radiation, PAR, wind and air pressure measurements. Years 2000 to 2007 the station was located at Governor's Academy, Newbury, MA and was moved July 30, 2007 to the MBL Marshview Farm field station property where it is currently located.

Year 2017 meteorological measurements at MBL Marshview Farm of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

Land cover (%) and climatic data (mean annual temperature, mean annual rainfall and xerothermic index) of the three areas (TC: Tyrrhenian Coast, MA: Maremma, CP: Central plains).

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

This map layer shows polygons of average annual precipitation in the contiguous United States, for the climatological period 1961-1990. Parameter-elevation Regressions on Independent Slopes Model (PRISM) derived raster data is the underlying data set from which the polygons and vectors were created. PRISM is an analytical model that uses point data and a digital elevation model (DEM) to generate gridded estimates of annual, monthly and event-based climatic parameters.

The Corps Water Management System (CWMS) includes four interrelated models to assist with water management for the basin:

• GeoHMS (Geospatial Hydrologic Modeling Extension)
• ResSIM (Reservoir System Simulation)
• RAS (River Analysis System)
• FIA (Flood Impact Analysis)

The Blackstone River Basin is located within the states of Massachusetts and Rhode Island. Of the 547 square miles that make up the basin, 147 square miles, or 27% of the basin, is in Rhode Island. About 400 square miles or 73% of the basin is located in Massachusetts. The basin is heavily urbanized characterized by a hilly terrain comprised of lakes and ponds. Elevations within the Blackstone River Basin range from 1200 feet in the northwest to about 3 feet above mean sea level at the mouth of the Seekonk River.

The coastal location of the Blackstone River basin exposes it to the effects of cyclonic disturbances and coastal storms in the region, resulting in periods of heavy precipitation. On an average, this basin receives approximately 48 inches of rainfall annually. The average annual snowfall in Worcester, MA is about 64 inches, which is representative of the headwaters of the Blackstone River Basin.The average annual snowfall in Providence, RI near the mouth of the Seekonk River is 346 inches.

Blackstone River extends from its headwaters in Worcester MA to its confluence with Abbott Run in Central Falls RI creating the Seekonk River. The Seekonk River discharges into the Providence River eventually draining into the Narragansett Bay. Some of the major tributaries to the Blackstone River include Quinsigamond River, Mumford River, West River, Branch River, Mill River and Peters River The key inflow gages in the Blackstone River basin include Kettle Brook at Rockland Street near Auburn MA, Quinsigamond River at North Grafton MA, Mumford River at Uxbridge MA, West River below West Hill Dam near Uxbridge MA, Branch River at Forestdale RI, Mill River at Harris PD Outlet at Woonsocket RI, Peters River RT 114 Bridge at Woonsocket RI and Abbott Run at Valley Falls RI.

There are two USACE dams located within the Blackstone River Basin. They include the West Hill Dam on the West River and Woonsocket Falls on the Blackstone River. West Hill Dam is a dry reservoir that is typically run of river. Channel capacity of Mill Creek in this area is 425 cfs. Woonsocket Falls Dam was modified with tainter gates to control reservoir stages. A hydropower facility pulls water from the reservoir and discharges the same flow back into the Blackstone River channel downstream of the Woonsocket Falls gates.

The Blackstone River basin land use is largerly characterized by forest land (52% of the basin area) and residential development (22% of the basin area) with significant industrial development along the Blackstone River in Worcester MA, Woonsocket RI, Pawtucket RI and Central Falls RI. Much of the water-powered industrial development along the rivers in the Blackstone River basin stemmed from the first successful textile mill in America, the Slater Mill in Pawtucket RI constructed in 1793.Less than 2% of the basin’s land use is considered cropland or agricultural.

The NCEP operational Global Forecast System analysis and forecast grids are on a 0.25 by 0.25 global latitude longitude grid. Grids include analysis and forecast time steps at a 3 hourly interval from 0 to 240, and a 12 hourly interval from 240 to 384. Model forecast runs occur at 00, 06, 12, and 18 UTC daily. For real-time data access please use the NCEP data server [http://www.nco.ncep.noaa.gov/pmb/products/gfs/].

New proxy records from deep‐sea sediment cores from the northwestern continental margin of Western Australian reveal a 5.3 million‐year (Ma) history of aridity and tropical‐monsoon activity in northwestern Australia. Following the warm and dry early Pliocene (~5.3 Ma), the northwestern Australian continent experienced a gradual increase in humidity peaking at about 3.8 Ma with higher than present‐day rainfall. Between 3.8 and about 2.8 Ma, climate became progressively more arid with more rainfall variability. Coinciding with the onset of the northern hemisphere glaciations and the intensification of the northern hemisphere monsoon, aridity continued to increase overall from 2.8 Ma until today, with greater variance in precipitation and an increased frequency of large rainfall events. We associate the observed large‐scale fluctuations in Australian aridity with variations in Indian Ocean sea‐surface temperatures (SST), which largely control the monsoonal precipitation in northwestern Australia.

Year 2003 meteorological measurements at Governor's Academy of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

Year 2007 meteorological measurements at Governor's Academy and MBL Marshview Farm of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

Tropical biodiversity overshadows the number of species inhabiting other regions. Age, area, and stability constitute three classical ideas used to explain the higher richness in these warm and humid zones. In this study, we measured the global dynamics of tropical, arid, temperate, cold, and polar climate zones over the last 5 million years (Ma). We aimed to evaluate whether the age, area, and stability of these climate zones contribute to explaining the observed differences in species richness. We classified the paleoclimatic layers generated by the PALEO-PGEM climatic emulator – temperature and precipitation for the last 5 Ma at 1,000-year intervals – into the main Köppen-Geiger climate zones: tropical, arid, temperate, cold, and polar. We then calculated three variables: age, area, and stability. Age represents the duration that each map cell has remained within its current climate zone since its last change (map cell-based measure). Area quantifies the total extent of each climate ..., Climate data We focused on the last 5 Ma, encompassing the Pliocene (5.3-2.6 Ma), Pleistocene (2.6-0.01 Ma), and Holocene (0.01 Ma ago to the present day; Cohen et al., 2021). This period started with a subtle warming trend in the early Pliocene (until 3.2 Ma), continuing with successive cooling pulses that culminated with the establishment of continental northern hemisphere glaciations (Zachos et al., 2001). Moreover, orographic and tectonic events occurred during this period, such as the gradual uplift of the Andes (Gregory-Wodzicki, 2000). To examine how these climatic changes influence biogeographic patterns, we used the high-resolution climate emulator PALEO-PGEM (Holden et al., 2019), which provides global temperature and rainfall monthly data with 1,000-year temporal resolution and 0.5º spatial resolution (Fig. 1). Using monthly mean temperature (°C) and total rainfall (mm) data from PALEO-PGEM, we created 10,002 arrays representing each time step over the past 5 Ma (two arrays o..., , # Data for: Classic hypotheses of area, time, and climatic stability fall short in explaining high tropical species richness

https://doi.org/10.5061/dryad.h70rxwdv4

Description of the data and file structure

Code and data files for running the analyses of the article "Classic Hypotheses of Area, Time, and Climatic Stability Fall Short in Explaining High Tropical Species Richness". This repository includes area and richness data, climate classification arrays, landmass shapefiles, species presence/absence databases, and the R script used for processing and analysing.

Files and variables

File: Area_databases.zip

Description:Â

• "Total_area_global.csv": Global area (km²) of climate zones across all time steps.
  • "class": climate zone (1 = Tropical; 2 =Â Arid; 3 = Temperate; 4 = Cold; 5 = Polar).
  • "value": area in square kilometres (km2).
  • "layer": Time step (from present as "Time 1", to 5 million years as "Time 5,00...,