Weather and climate forecasts

Overview

Weather and climate forecasts address the ubiquitous desire to know what the weather (temperature, precipitation, winds, cloud cover, etc.) will be like over the coming hours, days, weeks, and months. Weather forecasts refer to forecast periods of 14 days or less, a time frame over which the evolution of the current atmospheric pattern can be more directly predicted, and very specific and high-resolution (in time and space) predictions of weather variables can be made. The skill of weather forecasts over mid-latitude continental areas like the Colorado River Basin is very high for the first 1-2 days, lower for the next 3-4 days, and then drops off dramatically.

Climate forecasts or outlooks are for longer periods (14 days to several months or more), and what is typically forecasted is tendencies towards anomalies (warmer/cooler temperatures; higher/lower precipitation) rather than specific quantities. Both the spatial and temporal resolution of the climate forecasts are lower than for weather forecasts. The sources of predictability for climate forecasts are more diverse than for weather forecasts, which depend mainly on capturing the initial conditions and patterns of the atmosphere. The skill of climate forecasts is much lower than for weather forecasts in all parts of the world, and this is true also in the Colorado River Basin.

Incomplete knowledge about future weather conditions is a major uncertainty in streamflow forecasts; most of the forecast error in April 1st seasonal streamflow forecasts is due to the weather during the April-July streamflow forecast period turning out to be different from what was assumed in the most-probable streamflow forecast (the average of past April-July temperature and precipitation).

Figure 1. CBRFC forecast evolution plot showing the multiple probabilistic forecasts of April-July Lake Powell inflows that were made at each stage of the 2020 forecast season as the snowpack evolved. Image: CBRFC; Annotations: Jeff Lukas.

Relevance

Weather forecasts (out to 10 days) are routinely used by stakeholders across the basin for guiding short-term operational decision-making, such as in agriculture, recreation, and transportation, and water resource management. NOAA Colorado Basin River Forecast Center (CBRFC) incorporates weather forecasts (out to 10 days) into their short-term streamflow forecasts and peak runoff forecasts, and also into their Seasonal streamflow forecasts.

Climate forecasts and outlooks are consulted by stakeholders, including agricultural producers and water managers, but because of their relatively low forecasts accuracy/skill it is challenging to use them to support planning and decision-making like how weather forecasts and seasonal streamflow forecasts are used. Reclamation and CBRFC are currently exploring ways to incorporate climate forecasts into basin runoff and reservoir outlooks.

Weather forecasts

Weather forecasts have relatively high skill, and continue to improve. In the Western U.S., the typical forecast of daily high temperature (T_max) made 5 days in advance has a mean error of 3-4 °F, and the probability-of-precipitation (PoP) forecast at that same 5-day lead time is far more accurate than just assuming the average PoP for that season and location. In general, today's 5-day weather forecast is as skillful as the 4-day forecast was 10 years ago, or the 3-day forecast 20 years ago.

The main source of predictability and skill for weather forecasts is the accurate description of the initial conditions of the atmosphere by global networks of observations from land and ocean stations, satellites, and aircraft. Once initialized with those observations, a weather forecast model simulates the evolution of the large-scale weather patterns. The skill of weather forecasts declines as the lead time lengthens, because the information contained in the initial patterns is gradually lost to unpredictable chaotic motions of the atmosphere.

Weather forecast models are massively complex physics-based simulation models that are run on supercomputers. They divvy up the globe into a 3-D grid and calculate changes in each gridbox over time using fundamental equations, similar to Global climate models (GCMs). For weather forecasts for the U.S., the NOAA National Weather Service relies mainly on the NOAA GFS (Global Forecast System) model, supplemented with the primary European and Canadian global forecast models, and higher-resolution U.S. regional models. Forecasters at the local NWS offices use the forecast model output as guidance in constructing the familiar twice-daily NWS official forecasts, in consideration of their knowledge of local weather and the strengths and weaknesses of the models.

The primary weather forecasting challenge for the Colorado River Basin pertaining to water resources is predicting the track and strength of the low-pressure systems (i.e., mid-latitude cyclones) coming off the Pacific that provide the vast majority of October-May precipitation. Once these systems reach the West Coast (usually 1-3 days before affecting the basin), they can be better monitored and forecasted.

Sub-seasonal climate forecasts

Sub-seasonal climate forecasts, those made for conditions 2 weeks to 3 months ahead, are a relatively recent development leveraging advances in the understanding of climate-system processes at those timescales. Slotting into the gap in between weather forecasts and seasonal climate forecasts, sub-seasonal forecasts essentially blend the methods and sources of predictability used in both (Figure 1). Like seasonal climate forecasts, official NOAA sub-seasonal forecasts are expressed probabilistically, as the likelihood of anomalous conditions.

Sub-seasonal forecasts are mainly based on the output of two overlapping classes of models: (1) weather forecast models, such as GFS and ECMWF, being run out for a longer period, and (2) climate models (including GCMs), which have coarser temporal and spatial resolution but include more components, processes, and interactions, such as ocean currents and soil-atmosphere feedbacks. Several climate models are run in a coordinated fashion to make sub-seasonal predictions through both the North American Multi-model Ensemble (NMME; 7 models) and the Subseasonal Experiment (SubX; 7 models, including 4 also in NMME); these model predictions are used in research and, increasingly, for operational forecasting.

U.S. operational forecasts at sub-seasonal scales are issued by NOAA NWS through the Climate Prediction Center (CPC). They offer an official week 3-4 (15-28-days out) probabilistic temperature forecast, an experimental weeks 3-4 probabilistic precipitation forecast, and official 1-month (1-30 days out) forecasts for both temperature and precipitation. All of these forecasts identify areas where there are tendencies towards above-normal or below-normal conditions, much like their seasonal climate forecasts (below).

The skill of climate forecasts, including sub-seasonal forecasts, is much more variable regionally and seasonally than the skill of weather forecasts, and generally much lower. Skill in

Additional Resources

State of the Science Report

Chapter 8 of the State of the Science report covers many aspects of Streamflow Forecasting in greater detail; Section 8.4 is specific to mid-range forecasts (seasonal and longer). Chapter 6, on Hydrologic Modeling, has a detailed description of the CBRFC forecast model framework in Section 6.3, under National Weather Service Models.

New and Notable Research (2020-present)

Summary