ches_bay_sst.rmd

# Chesapeake Bay Seasonal Sea Surface Temperature Anomaly {#ches_bay_sst}

**Description**: Chesapeake Bay Seasonal Sea Surface Temperature Anomaly

**Indicator family**: 

- [X] Oceanographic


**Contributor(s)**: Ron Vogel, Bruce Vogt

**Affiliations**: ?

```{r echo=FALSE}
knitr::opts_chunk$set(echo = F)
library(ecodata)
```
## Introduction to Indicator
Seasonal spatial anomaly maps represent the difference between a seasonal average sea surface temperature (SST) and a long-term average SST for that season. For the Chesapeake Bay, the long-term average is derived from the SST time series from 2007 to the year immediately prior to the current year (max(Year) - 1). This reference period serves as a benchmark for comparing current observations. Hence, the anomaly represents the degree to which the current seasonal average departs from historical average, either colder or warmer, indicating whether the current temperature conditions may be favorable or unfavorable for marine species.

## Key Results and Visualizations
For 2023, winter SST’s show conditions to be roughly 1 degree Celsius warmer than the prior 16-year average winter (2007-2022) throughout Chesapeake Bay. Spring conditions are average. Summer conditions are roughly 0.5 degree Celsius colder than the average summer. Fall conditions are mixed spatially but do not exceed 0.5 degree Celsius colder or warmer.

```{r plot_ches_bay_sstMAB}
# Plot indicator
ggplotObject <- ecodata::plot_ches_bay_sst(report='MidAtlantic')
ggplotObject
```


## Indicator statistics 
Spatial scale: Data from two satellite instruments, AVHRR at 1 km spatial resolution and VIIRS at 750 m spatial resolution, are co-gridded to an 830 m spatial grid. Overpasses from the two instruments for all current operational satellites are composited into a daily scene in order to maximize geographic coverage on a per-day basis, i.e. minimize data gaps from clouds. Seasonal averaging further increases geographic coverage.

Temporal scale: Only nighttime satellite overpasses are used in the seasonal averages, i.e. the data do not represent daytime solar heating of the water surface. Seasons for Chesapeake Bay are Dec-Feb (winter), Mar-May (spring), Jun-Aug (summer), and Sep-Nov (fall).

**Synthesis Theme**:

- [X] Multiple System Drivers
- [X] Regime Shifts
- [X] Ecosystem Reorganization


```{r autostats_ches_bay_sst}
# Either from Contributor or ecodata
```

## Implications
The warm water during the 2022-2023 winter were likely favorable to blue crabs (Callinectes sapidus) by reducing their overwintering mortality.

The average temperatures of the spring season indicated favorable spawning, feeding, growth and recruitment conditions for key species such as striped bass (Morone saxatilis) and oysters (Crassostrea virginica). 

The summer’s cooler than average conditions were likely favorable for striped bass by reducing temperature-driven stratification of the water that reduces oxygen solubility. Without the high stress of a stratified low-oxygen environment and temperatures that exceed suitability thresholds, striped bass may have experienced “normal” habitat occupancy, growth potential, and mortality. Similarly, cooler summer temperatures may have benefited Eelgrass (Zostera marina) which provide nursery habitats for many estuarine species (e.g., blue crab) by preventing heat-related die-backs of this critical foraging and nursery ground for many species. 

In the fall season, there were warmer-than-average temperatures in the Western Shore tributaries, but cooler-than-average temperatures on the Eastern Shore. Warmer conditions likely developed due to low precipitation, which leads to lower freshwater flow into the Bay. Relatively calm conditions may have contributed as well by reducing mixing. Warmer conditions on the Western Shore may have delayed migration of some species to marine waters.

## Get the data

**Point of contact**: [Ron Vogel (ronald.vogel@noaa.gov)](mailto:Ron Vogel (ronald.vogel@noaa.gov)){.email}

**ecodata name**: `ecodata::ches_bay_sst`

**Variable definitions**

1) sst: sea surface temperature 2023, Celsius
 2) sst_climatol: sea surface temperature climatology 2007-2022, Celsius
 
3) sst_anomaly: sea surface temperature anomaly 2023 minus 2007-2022, Celsius

```{r vars_ches_bay_sst}
# Pull all var names
vars <- ecodata::ches_bay_sst |>
   dplyr::select(Var) |>
   dplyr::distinct()

DT::datatable(vars)
```
**Indicator Category**:

- [X] Published Methods
- [X] Database pull with analysis


## Public Availability

Source data are NOT publicly available.

## Accessibility and Constraints

For seasonal SST anomaly data files (including the SST long-term climatology), and other inquiries, please contact Ron Vogel at ronald.vogel@noaa.gov The time series of daily SST, seasonal average SST, and other time intervals for 2007 – present, are available to the public at: https://www.star.nesdis.noaa.gov/pub/socd1/ecn/data/avhrr-viirs/sst-ngt More information about this SST data set is available at: https://eastcoast.coastwatch.noaa.gov/cw_avhrr-viirs_sst.php

**tech-doc link**
<https://noaa-edab.github.io/tech-doc/ches_bay_sst.html>